Thesis (Vu_2009_02Thesis)

Transcription

Bioaffinity Fourier Transform
Ion Cyclotron Resonance Mass Spectrometry
for Direct Screening of Natural Product Extracts
Submitted in fulfilment of the requirements of the degree of
Doctor of Philosophy
By
HOAN VU
(M.Chem. Eng., Post Gra.Dip. Sc.)
School of Science
Griffith University
May, 2008
DECLARATION
I declare that this work has not previously been submitted for a degree or diploma in
any university. To the best of my knowledge and belief, the thesis contains no
material previously published or written by another person except where due
reference is made in the thesis itself.
Hoan Vu
Date
i
ii
ACKNOWLEDGEMENTS
Firstly, I would like to express my sincere appreciation to Professor Ron Quinn for
his advice and encouragement, sharing his enthusiasm with me throughout my PhD
studies. Ron offered invaluable guidance, yet allowed me the necessary
independence and flexibility to pursue my own research priorities and
methodologies.
I would like to thank Dr. Sally-Ann Poulsen for giving me the chance to start the
project on the FTICR-MS instrument. Many technical problems with the instrument
were encountered and overcome. In the process, I acquired mechanical and electrical
knowledge relevant to the operation of the instrument, as well as important, complex
and varied application techniques.
I am grateful to Dr. Ngoc Pham for the indispensable advice and assistance with
NMR instrument techniques and the elucidation of natural products compound
structures.
I acknowledge the financial support of AstraZeneca Scholarship and also the funding
by the Australian Research Council for equipment support.
Finally I would like to express my thanks to my family and friends for all their love
and support. Very special thanks to Ngoc, who has always supported and encouraged
my work.
iii
ABBREVIATIONS
ALIS
automated ligand identification system
AMP
adenosine-5’-monophosphate
ANG
human angiogenin
bCA II
bovine carbonic anhydrase A
CID
collision induced dissociation
CRM
charge residue mechanism
DNA
deoxyribonucleic acid
ECD
electron capture dissociation
ECP
eosinophil cationic protein
EDN
eosinophil-derived neurotoxin
EI
electron impact ionization
ESI-MS
electrospray ionization mass spectrometry
FAB
fast atom bombardement
FFD
fractional factorial design
FKBP
FK506 binding protein
FP
fluorescence polarization
FRET
fluorescence resonance energy transfer
FTICR
Fourier transform ion cyclotron resonance
HAT
human alpha thrombin
HEWL
hen egg-white lysozyme
HIV
human immunodeficiency virus
HPLC
high performance liquid chromatography
HSA
human serum albumin
HTS
high throughput screening
ICR
ion cyclotron resonance
i.d.
internal diameter
IEM
ion evaporation mechanism
IRMPD
infrared multiphoton dissociation
LC
liquid chromatography
MALDI
matrix assisted laser desorption ionization
MHz
mega hertz
iv
MM
molecular mass
MMCO
molecular mass cut-off
MS
n
multistage mass spectrometry
NAG
N-acetylglucosamine
NCE
new chemical entities
NH4OAc
ammonium acetate
NMR
nuclear magnetic resonance
o.d.
outer diameter
PBS
phosphate buffered saline
PD
plasma desorption
PEEK
polyetheretherketone
PPACK
D-Phe-Pro-Arg-chloromethylketone
Ras-GDP
ras-guanosine diphosphate
Ras-GTP
ras-guanosine triphosphate
RF
radio frequency
RNA
ribonucleic acid
RNase A
ribonuclease A
SDS
sodium dodecylsulphate
SDS-PAGE
sodium dodecyl sulphate polyacrylamide gel
SEC
size exclusion chromatography
SORI
sustained off resonance irradiation
SPA
scintillation proximity assay
S/N
signal to noise ratio
SWIFT
stored waveform inverse Fourier transform
TFA
trifluoro acetic acid
TR-FRET
time resolved fluorescence resonance energy transfer
v
vi
ABSTRACT
The search for new drugs in natural products involves the screening of
natural product extracts on therapeutic targets for the presence of active compounds
and subsequent investigation of their biological activities. Towards this end, a rapid
and effective strategy to identify the noncovalent interactions between active ligands
from natural product extracts with therapeutic protein targets without false positive
or negative results is critical. The current thesis presents the outcomes of research
exploring a novel approach of biological screening of natural product extracts using
bioaffinity ESI-FTICR-MS as a detection means.
A research plan containing three major steps has been undertaken in this
study. Step one examines the current challenges in identifying protein complexes by
ESI-MS and developing optimized conditions for ESI-FTICR-MS. Step two involves
the development of methods for identifying complexes of targets with various
molecular mass values (600 – 66,000 Da) in the setting of crude extracts. Step three
uses these methods to screen natural product extracts and identify active natural
product compound – protein complexes, obtaining accurate molecular mass of active
compounds and their mass fingerprint. On this basis, a mass-directed purification
experiment was performed to isolate the identified active compounds. The binding of
the pure active compounds with the protein target was then confirmed by
competition experiments with a specific inhibitor of the protein.
The procedure to achieve the optimal ESI-MS condition for detecting protein
- small molecule complex has been successfully developed using bCA II as the test
target protein and fractional factorial design (FFD) approach. Key instrumental
factors controlling the desolvation process, as well as the interactions between these
factors, have been identified using FFD experiment. It has been found that flow rate,
nebulizer gas pressure and drying gas flow rate are factors that greatly affect the
sensitivity of the complex detection. Capillary exit voltage also has a great effect on
the desolvation in vacuum and on the preservation of the complex. These factors
have been found to interact with each other and contribute to the final response, and
therefore, have been incorporated in a second FFD experiment which focuses on
minimum moment aberration. It has been found that the best condition is achieved
vii
when the capillary exit voltage is at the highest setting, and the flow rate, drying gas
flow rate and nebulizing gas are at medium settings.
The development of ESI-FTICR-MS methods for identifying noncovalent
complexes in the environment of crude extracts has been accomplished using targets
with various molecular mass values. In particular, ESI-FTICR-MS has been used to
successfully detect hemin (< 1 kDa) and its complex with artemisinin. Accurate
mass for artemisinin has been deduced with high resolution (deviation from
theoretical value of less than 5 ppm). Screening 50 plant and marine sponge biota
with hemin returned four active extracts. One of the four active natural product
compounds had the molecular mass very close to artemisinin (Δ = 0.002 Da). The
artemisinin identity of the active component has been confirmed using the MS2
pattern of artemisinin and the suspect artemisinin active component.
A flavonoid was also detected in one of the active extracts and the structure
elucidation of this active flavonoid has been proposed by comparing its diagnostic
fragmentation patterns in multiple stage MS with those of other flavonones and
flavonols. The first MS3 fragment ions of these 4 flavones and 2 flavonols are also
presented in this study. The third and fourth active compounds have been isolated
based on their accurate mass information using mass-directed purification. Their
structures have also been determined by NMR. They are diacarnoic acids and are
epi-isomers at position 3. MS2 experiments have been performed and can
discriminate between these two compounds.
Methods have also been developed for proteins having higher molecular
masses using three target proteins ranging from 13 to 66 kDa. Using these methods,
ESI-FTICR-MS or SEC-FTICR-MS have successfully identified these proteins and
their complexes in a clean matrix, as well as in a natural product extract matrix. The
use of microdialysis and SEC has been found to be a suitable method for protein
desalting and buffer exchange, and for natural product extract filtering. The results
support the conclusion that the ability of FTICR-MS to give accurate molecular mass
of the inhibitors represents a powerful means for screening natural product extracts
in a drug discovery process of finding diversified small molecule inhibitors.
The methods developed for both direct infusion and online SEC-FTICR-MS
have been successfully employed to screen 85 raw methanolic plant extracts with
bCA II. A noncovalent complex has been detected and the active compound which
viii
binds to bCA II is identified. The specificity of the binding has also been confirmed
by competition experiments with a specific inhibitor of the target protein. The
outcomes of this work have been reported in the Journal of Biomolecular Screening
(first published online on March 18, 2008). One of the key advantages of using ESIFTICR-MS and associated methods is that the screening of the crude extracts is
carried out without any preparation work such as pre-chromatographed, or prepurification steps, thus avoiding any contamination which may lead to false positive
or negative results. Information on the exact mass of the active compound also
provides insights into the chemical composition or structural class of the compounds,
thus shortening the long process of lead identification and allowing rapid massdirected purification to isolate the active compounds. The demonstration of a
coupled SEC-ESI-FTICR-MS procedure is superior to a batch method assay,
whereby crude extracts are fractionated and subsequently bio-assayed until the active
compound is found. Furthermore, this approach yields molecular masses in real time
allowing subsequent mass-directed purification.
ix
TABLE OF CONTENTS
Page
Chapter one Introduction ― A new approach to identify noncovalent
complexes between natural product extracts and proteins using bioaffinity
mass spectrometry
1.1
Small molecule – protein complexes
1
1.2
Mass spectrometry – a method to identify noncovalent complexes
3
1.2.1
History of mass spectrometry in biological applications
4
1.2.2
Bioaffinity MS in the identification of noncovalent complex
5
and potential drugs
1.3
Natural products – an infinite source of medicines
6
1.4
Rapid and effective screening of natural products – the challenges
9
1.5
Objectives
10
1.6
Research Plan
11
1.7
References
12
Chapter two Mass spectrometry technique and its approaches in drug screening
- Perspectives and challenges for screening natural product extracts
2.1
Mass spectrometry background
15
2.1.1
Maldi-MS
16
2.1.2
ESI-MS
17
2.1.3
ESI-MS and conformational changes in protein
21
2.2
Identifying active compounds via detection of noncovalent complexes 22
by ESI-MS
2.2.1
Indirect noncovalent complex screening methods
2.2.1.1 Indirect size exclusion - reversed phase liquid chromatography-
23
24
mass spectrometry method
2.2.1.2 Indirect ultrafiltration mass spectrometry method
25
2.2.1.3 Indirect frontal affinity chromatography mass spectrometry method
26
2.2.2
27
Direct noncovalent complex screening method
2.2.2.1 Desalting and buffer exchange equilibrium dialysis
28
2.2.2.2 Desalting and buffer exchange -gel filtration
28
x
2.3
Direct identification of noncovalent complex using ESI-FTICR-MS
29
2.4
FTICR-MS
30
2.4.1
From ICR-MS to FTICR-MS
30
2.4.2
FTICR-MS background theory
31
2.4.3
FTICR-MS instrumentation
33
2.4.4
ESI-FTICR-MS
34
2.4.5
Instrument used in this thesis
35
2.4.5.1 ESI source
36
2.4.5.2 Ion transfer line
38
2.4.5.3 ICR cell
39
2.4.6
Time sequence for ESI-FTICR-MS experiments
41
2.4.7
Liquid chromatography-FTICR-MS (LC-FTICR-MS)
42
2.5
Challenges for screening natural product extracts
42
using ESI-FTICR-MS
2.6
References
43
Chapter three Optimization strategy for mass spectrometry in the observation
of noncovalent complexes
3.1
Introduction
51
3.2
Materials and methods
54
3.2.1
Materials
54
3.2.2
Instrument
55
3.3
Results and discussion
55
3.3.1
Step1: Assay buffer condition
55
3.3.2
Step 2: Experimental value region for ESI-MS parameters
56
3.3.3
Step 3: Interaction between instrumental factors
61
3.3.3.1 Main factors
63
3.3.3.2 Parameter interactions
65
3.3.4
Step 4: Fractional Factorial Design for Optimum Condition
73
3.4
Summary
75
3.5
References
75
xi
Chapter four FTICR-MS as a detector for small complex (<2000 Da)
and ligand structure recognition tool - a study for fragmentation patterns
of active ligands in the binding of natural product extracts to hemin
4.1
Introduction
79
4.1.1
Natural products as a source of antimalarial drugs
80
4.1.2
MS as a detector of complexes formed with hemin in a search for
82
antimalarial drugs
4.1.3
Ligand structure recognition– A strategic approach to speed up the
84
identification of new drugs in natural products
4.1.3.1 Accurate mass
84
4.1.3.2 Multistage MS
86
4.2
88
4.2.1
Materials
88
4.2.2
Sample preparation
89
4.2.3
Mass spectrometry
89
4.2.4
Extraction and purification
90
4.3
92
4.3.1
Identification of hemin and hemin-artemisinin complex
92
4.3.2
Identification of active extracts via complexes formed with hemin
93
4.3.3
Confirmation of artemisinin existence in crude extract
97
by fragmentation patterns
4.3.3.1 MS2 optimisation – artemisinin patterns
97
4.3.3.2 Active compound for QID027261 – MS2 fragmentation –Confirmed
98
artemisinin
4.3.4
Hemin - QID015773 complex
100
4.3.4.1 MS2 for flavones and flavonols – Background
101
4.3.4.2 Analysis of flavone and its recognition patterns using FTICR-MS
101
4.3.4.3 Analysis of flavonol and its recognition patterns using FTICR-MS
109
4.3.5
115
Structure determination of an active component in crude extract
QID015773
4.3.6
Hemin - QID10644 and Hemin - QID2280289 complexes
4.3.6.1 Active compounds isolated from marine sponge extracts
xii
120
120
4.3.6.2 Purification of active compounds
121
4.3.6.3 MS2 fragmentation pattern of active components of QID16044
121
2
4.3.6.4 MS fragmentation pattern of active component 35 of QID2280289
123
4.4
Summary
125
4.5
References
126
Chapter five Mass spectrometry in the recognition of intact protein complex
from 13 KDa to 66 KDa – method development for protein complexes in
natural product extract matrix
5.1
Introduction
131
5.2
Ribonuclease A (MM ~ 13,700 Da)
132
5.2.1
133
5.2.1.1 Materials
133
5.2.1.2 Methods
133
5.2.1.3 Instrument conditions
134
5.2.2
MS characterization of RNase A
134
5.2.3
Identification of RNase A – inhibitor complex
136
5.2.4
Identification of RNase A –inhibitor complex in natura product
138
crude extracts
5.2.4.1 Increasing signal to noise by size exclusion liquid chromatography
138
5.2.4.2 Molecular mass of inhibitors
140
5.3
Human alpha thrombin (MM ~ 37 KDa)
146
5.3.1
Material and methods
147
5.3.1.1 Materials
147
5.3.1.2 Methods
147
148
5.3.1.4 Online microdialysis
148
5.3.2
Identification of HAT by ESI-FTICR-MS
149
5.3.2.1 HAT buffer exchange using online microdialysis
150
5.3.2.2 HAT desalting and buffer exchange using SEC
152
5.3.3
154
Identification of HAT–inhibitor complex
5.3.3.1 Observation of HAT - PPACK complex using online microdialysis- 154
ESI-FTICR-MS
xiii
5.3.3.2 Observation of HAT–dysinosine A complex using online
155
SEC-ESI-FTICR-MS
5.3.3.3 Observation of HAT – PPACK complex in natural product
156
crude extracts using online SEC-ESI-FTICR-MS
5.3.3.3 Observation of HAT-dysinosin A in a natural product crude
157
extract using online SEC-FTICR-MS
5.3.5
Molecular mass of inhibitor
158
5.3.5.1 Molecular mass of PPACK
158
5.3.5.2 Molecular mass of dysinosin A
159
5.4
Human serum albumin (HSA, MM ~ 67 kDa)
160
5.4.1
160
5.4.1.1 Materials
160
5.4.1.2 Methods
161
161
5.4.2
161
Identification of HSA by ESI-FTICR-MS
5.4.2.1 Direct infusion with HSA
161
5.4.2.2 Online SEC-ESI-FTICR-MS for HSA
163
5.4.3
164
Identification of HSA-warfarin complex
5.4.3.1 Direct infusion analysis
164
5.4.3.2 Online size exclusion chromatography
164
5.4.4
Identification of HSA-warfarin in crude extract
165
5.4.5
166
5.5
Summary
168
5.6
References
169
Chapter six
Direct screening of natural product extracts using mass spectrometry
6.1
Introduction
172
6.2
173
6.2.1
Materials
173
6.2.2
Natural product extracts
174
6.2.2.1 For bCA II-inhibitor in natural matrix experiments
174
6.2.2.2 For raw methanolic extract screening
174
6.2.3
175
ESI-FTICR-MS analysis
xiv
6.2.4
Other instruments
175
6.2.5
Extraction and isolation of the active natural product compound
176
6.2.6
6-(1S-hydroxy-3-methylbutyl)-7-methoxy-2H-chromen-2-one
176
(Compound 42)
6.3
176
6.3.1
Detection of protein by ESI-FTICR-MS in physiological pH
176
6.3.2
Detection of protein-inhibitor complex
178
6.3.3
Detection of complex formed between protein target and its ligand
179
in natural product extract matrix
6.3.3.1 Determination of ligand molecular mass from complex
181
in natural product extract matrix
6.3.3.2 Determination of dissociation constant
183
6.3.3.3 Sensitivity of the ESI-FTICR-MS screening methodology
187
6.3.4
188
Detection of protein-ligand noncovalent complex in crude extract
6.3.4.1 Method for screening raw methanolic extracts
188
6.3.4.2 Size exclusion chromatography
188
6.3.4.3 Determination of ligand mass
191
6.3.5
Structure elucidation of active compound from Rutaceae leisomia
192
6.3.6
Confirmation and characterization of the binding
194
6.3.7
Increasing high throughput
195
6.4
Summary
196
6.5
References
Conclusion
199
Appendix 1
202
Appendix 2
203
Appendix 3
207
xv
LIST OF FIGURES
Page
Figure 1.1
“Lock and Key” model
2
Figure 2.1
A flow chart of a typical mass spectrometer
16
Figure 2.2
A schematic of MALDI-MS
17
Figure 2.3
A schematic of ESI-MS
18
Figure 2.4
A diagram of an ESI source
19
Figure 2.5
A schematic of two proposed ESI mechanisms
20
Figure 2.6
Spectrum of ubiquitin at a denatured state (pH 3)
21
Figure 2.7
An illustration of conformational changes in protein
22
acquired by ESI-MS
Figure 2.8
A schematic of two ESI-MS approaches
23
Figure 2.9
A schematic of indirect SEC-MS method
24
Figure 2.10
A schematic of indirect ultrafiltration MS method
25
Figure 2.11
A schematic of FAC-MS method
26
Figure 2.12
A schematic of direct noncovalent complex screening
27
MS method
Figure 2.13
A schematic of protein buffer exchange
28
using equilibrium dialysis
Figure 2.14
A schematic of desalting and buffer exchange using gel
29
filtration technique
Figure 2.15
Movement of an ion in a homogenous magnetic field
31
Figure 2.16
A schematic of a typical FTICR-MS
34
Figure 2.17
ESI-FTICR-MS instrument, Bruker 4.7 Tesla
36
Figure 2.18
A schematic cutaway view of FTICR-MS instrument
36
Figure 2.19
ESI -Apollo source diagram
37
Figure 2.20
Xmass tune page for ESI source
39
Figure 2.21
A schematic of the ion transfer line
39
Figure 2.22
Electric potential values of the ion transfer optic line
40
Figure 2.23
Bruker Infinity cell
41
xvi
Figure 2.24
A standard sequence of an ESI-FTICR-MS experiment
42
Figure 2.25
HPLC coupled to ESI-FTICR-MS
42
Figure 3.1
bCA II-ethoxzolamide intensity in 10 mM
56
ammonium acetate and in 10mM ammonium bicarbonate buffer
Figure 3.2
A schematic of Apollo ESI-MS ion source
58
Figure 3.3
Mass spectra of the mixture of bCA II with ethoxyzolamide
60
under capillary exit voltages 100, 110, 120, 130, 140, 150, 160V
Figure 3.4
Mass spectra of the mixture of bCA II with ethoxyzolamide
60
undercapillary exit voltages 100, 90, 80, 70V
Figure 3.5
Effect of capillary exit voltage to the complex
61
Figure 3.6
Main effects plot for each parameter
64
Figure 3.7
Pearson product moment correlation coefficients
65
Figure 3.8
Interaction of flow rate on other parameters
66
Figure 3.9
Interaction of nebulizer pressure on other parameters
67
Figure 3.10
Interaction of drying gas on other parameters
68
Figure 3.11
Interaction of gas temperature on other parameters
69
Figure 3.12
Interaction of end plate voltage
70
Figure 3.13
Interaction of capillary voltage
70
Figure 3.14
Interaction of capillary exit voltage
71
Figure 3.15
Interaction of skimmer 1
72
Figure 3.16
Interaction of skimmer 2
72
Figure 4.1
A dual nebulizer Apollo ESI-source
86
Figure 4.2
Comparison of a product ion scan performed
87
by a space-based and a time-based instrument
Figure 4.3
Hemin and its complex with artemisinine
93
Figure 4.4
MS spectrum of QID027261 incubated with hemin, showing
94
a complex at m/z 898.3226
Figure 4.5
94
Figure 4.6
95
Figure 4.7
MS spectrum of QID02280289 incubated with hemin
showing a complex at m/z 1022.4841
xvii
95
Figure 4.8
MS spectrum of complex formed by
97
hemin-extract QID027261
Figure 4.9
MS2 fragment ions for artemisinin in FTICR-MS
98
Figure 4.10
MS2 fragment ions for active compound in QID027261
99
Figure 4.11
Fragmentation patterns of flavonoids
101
Figure 4.12
MS2 fragmentation of apigenin (27), using m/z 271
104
as the precursor
Figure 4.13
MS2 fragmentation of chrysin (28), using m/z 255
104
as the precursor
Figure 4.14
MS2 fragmentation of 7-hydroxyflavone (29),
105
using m/z 239 as the precursor
Figure 4.15
MS2 fragmentation of 5-hydroxy-7-methoxyflavone (30),
105
Figure 4.16
MS3 fragmentation of apigenin (27), using m/z 153
107
as the precursor
Figure 4.17
MS3 fragmentation of chrysin (28), using m/z 153
107
as the precursor
Figure 4.18
MS3 fragmentation of 7-hydroxyflavone (29),
108
Figure 4.19
MS3 fragmentation of 5-hydroxy-7-methoxyflavone (30),
108
Figure 4.20
MS2 pattern of 3,7-dihydroxyflavonol (31), using m/z 255
111
as the precursor
Figure 4.21
MS2 pattern of fisetin (32), using m/z 287 as the precursor
111
Figure 4.22
MS3 fragmentation of 3,7-dihydroxyflavonol,
112
1,3
+
using m/z 137 ([ A+H] ) as the precursor
Figure 4.23
MS3 fragmentation of fisetin, using m/z 137 ([1,3A+H]+) as
113
the precursor
Figure 4.24
MS3 fragmentation of 3,7-dihydroxyflavonol, using m/z 149
113
([0,2A+H]+) as the precursor
Figure 4.25
MS3 fragmentation of fisetin, using m/z 149 ([0,2A+H]+) as
114
the precursor
Figure 4.26
MS of complex of hemin with QID015773 crude extract
xviii
115
Figure 4.27
MS2 fragmentation of compound 33, using m/z 345
117
([M+H]+) as the precursor
Figure 4.28
MS3 fragmentation pattern of 33, using m/z 330
117
([M-CH3+H]+) as the precursor
Figure 4.29
MS4 fragmentation pattern of 33, using m/z 169 ([1,3A+H]+)
118
as the precursor
Figure 4.30
MS2 fragmentation of active compound 34
2
123
Figure 4.31
MS fragmentation of active compound 35
124
Figure 5.1
a) MS spectrum of RNase A in ammonium bicarbonate at
135
charge state 6+, 7+, 8+
b) Experimental isotopic spectrum of RNase A at
charge state 8+
c) Theoretical isotopic spectrum of RNase A at
charge state 8+
Figure 5.2
a) Experimental MS isotopic spectrum of RNase A and
137
RNase A-AMP complex in ammonium bicarbonate at
charge state 8+
b) Theoretical isotopic spectrum of RNase A - AMP complex
at charge state 8+
c) Experimental isotopic spectrum of RNase A - AMP complex
at charge state 8+
Figure 5.3
a) MS spectrum of RNase A in denaturing condition at
138
charge state 6+, 7+, 8+, 9 +, and 10+
b) MS spectrum of RNase A-AMP in denaturing condition at
charge state 6+, 7+, 8+, 9+, and 10+
Figure 5.4
a) Spectrum of RNase A - AMP in crude extract analyzed
139
by direct infusion ESI-FTICR-MS
b) Spectrum of RNase A - AMP in crude extract analyzed
by size exclusion ESI-FTICR-MS
Figure 5.5
Diagram of the online setup method using HPLC
140
Figure 5.6
MS spectrum of a complex at a charge state z
141
Figure 5.7
MS spectrum of RNase A-AMP complex
142
Figure 5.8
A schematic of trapping technique
143
xix
Figure 5.9
MS spectrum of a dissociated RNase A-AMP complex
144
Figure 5.10
Switching valve used for trapping technique
145
Figure 5.11
A photo of the microdialysis device used in this thesis
149
Figure 5.12
MS spectrum of HAT without desalting and buffer exchange 150
Figure 5.13
A diagram of the microdialysis cell used in
151
buffer-exchange step for HAT
Figure 5.14
MS spectrum of HAT desalting and buffer exchange using
152
online microdialysis
Figure 5.15
MS spectrum of HAT desalting and buffer exchange using
153
offline SEC
Figure 5.16
MS spectrum of HAT desalting and buffer exchange
154
using SEC
Figure 5.17
MS spectrum of HAT-PPACK using online microdialysis
155
Figure 5.18
MS spectrum of HAT-PPACK complexes
156
Figure 5.19
MS spectrum of HAT-PPACK in crude extracts
157
Figure 5.20
MS spectrum of HAT-dysinosin A in a crude extract
158
Figure 5.21
Mass spectrum of HSA acquired by direct infusion
163
(native condition)
Figure 5.22
Mass spectrum of HSA acquired by direct infusion under
163
denatured condition (pH 3)
Figure 5.23
MS spectrum of HSA-warfarin complex acquired by
165
SEC-FTICR-MS
Figure 5.24
MS spectrum of HSA-warfarin complex in natural product
166
crude extract acquired by SEC-FTICR-MS
Figure 5.25
Protein-ligand complex dissociated into protein and ligand
167
by using in source CID
Figure 5.26
MS spectrum of disrupted HSA-warfarin complex
168
using in source CID
Figure 6.1
MS spectra of bCA II-marine sponge extracts and
177
bCA II-spiked marine sponge extracts
Figure 6.2
Mass spectrum of bCA II acquired under denatured condition 177
Figure 6.3
Mass spectrum of bCA II-sulfanilamide (native condition)
Figure 6.4
Mass spectrum of bCA II-sulfanilamide (denatured condition) 179
xx
178
Figure 6.5
Spectra of bCA II-marine sponge extracts and bCAII-
180
inhibitor-marine sponge extracts
Figure 6.6
MS spectra of control bCA II, bCA II-ethoxzolamide
181
complex and bCA II-sulfanilamide complex
Figure 6.7
MS spectrum of bCA II in low resolution mode
182
Figure 6.8
MS spectrum of bCA II-ethoxzolamide complex in low
182
resolution mode
Figure 6.9
a) Isotopically resolved spectrum of bCA II-ethoxzolamide
183
complex obtained in high resolution mode
b) Isotopically resolved spectrum of bCA II-sulfanilamide
complex obtained in high resolution mode.
Figure 6.10
Titration of sulfanilamide in bCA II for the
186
determination of Kd
Figure 6.11
MS spectra of bCA II-extract with and
189
without size exclusion column
Figure 6.12
Isotopically resolved spectrum of complex bCA II- ligand
192
from active extract obtained in high resolution mode
Figure 6.13
MS spectrum of bCA II-42 complex
194
Figure 6.14
Competition experiment spectra
195
Figure 6.15
A working diagram of using ten-port switching valve
196
xxi
LIST OF TABLES
Page
Table 1.1
Timeline of biological mass spectrometry
5
Table 2.1
Timeline of FTICR-MS development
31
Table 3.1
Structure and binding constant of ethoxzolamide,
54
an inhibitor of bCA II
Table 3.2
Parameter levels for FFD
61
Table 3.3
Results of FFD for factor interactions
62
Table 3.4
Effects of factors on the MS response
63
Table 3.5
Fractional Factorial Design (FFD) experiment for optimum
74
condition
Table 4.1
List of plant biota
91
Table 4.2
List of marine sponge biota
91
Table 4.3
Molecular mass of active compounds from natural product
96
extracts
Table 4.4
Formula, observed mass, calculated mass, mass error (ppm)
98
and fragment scheme identity of fragment ions observed in the
MS2 spectrum of the sodiated artemisinin
Table 4.5
Formula, observed mass, calculated mass, mass error (ppm)
100
and fragment scheme identity of fragment ions observed
in the MS2 spectrum of the active compound in extract
QID027261
Table 4.6
FT-MS2 product ions obtained from the [M+H]+ ions
102
of compounds 27-30
Table 4.7
FTMS3 product ions obtained from the 1,3A+ ions
106
of compounds 27-30
Table 4.8
110
of compounds 31 and 32
Table 4.9
FT-MS3 product ions obtained from the 1.3A+ ions
112
of compounds 31-32
Table 4.10
FT-MS3 product ions obtained from the 0,2A+ ions
xxii
112
of compounds 31-32
Table 4.11
118
of compounds 33
Table 4.12
FTMS4 product ions obtained from the 1,3A+ ions
118
of compounds 33
Table 4.13
Formula of neutral loss, observed mass, calculated mass,
122
mass error (Da) and fragment identity observed in the MS2
spectrum of the active compound 34
Table 4.14
Formula of neutral loss, observed mass, calculated mass,
124
mass error (Da) and fragment identity observed in the MS2
spectrum of the active compound 35
Table 5.1
Result of m/z AMP detected by SEC-FTICR-MS
142
Table 5.2
List of flow rates trialed with HAT
152
Table 5.3
m/z values of HAT-PPACK complex, HAT at 11+charge
157
state and average molecular mass of PPACK
Table 5.4
Signal intensity for HSA by direct infusion analysis
162
Table 5.5
Signal intensity for HSA and HSA-warfarin complex using
164
SEC-FTICR-MS analysis
Table 6.1
Structures and binding constants of the bCA II inhibitors
174
used in this study
Table 6.2
Concentration of ligand free and protein complex
185
Table 6.3
Results for the determination of Kd and its curve fitness
186
(calculated from Prism, v. 3.0)
Table 6.4
Properties of the size exclusion resins tested for this study
190
Table 6.5
NMR data for compound 42 in DMSO-d6
193
xxiii
LIST OF CHARTS/SCHEMES
Page
Chart 1.1
Research Plan
11
Scheme 4.1
Strategy for early detection of known drugs
80
or known structural class of active compounds
Scheme 4.2
Proposed mechanism for MS3 fragment ions
of precursor ion
Scheme 4.3
1,3
109
+
A of compounds 27-30
Proposed mechanism for MS3 fragment ions of
114
precursor ion 0,2A+ of compounds 31 (similarly for
compound 32)
Scheme 4.4
119
precursor ion [M+H]+ of compound 33
Scheme 4.5
120
precursor ion 1,3A+ of compound 33
Scheme 4.6
Proposed fragment ions for compound 34
122
Scheme 4.7
125
Scheme 6.1
Screening work-flow
183
xxiv
LIST OF PUBLISHED WORKS IN THE COURSE OF THE RESEARCH
Direct screening of natural product extracts using mass spectrometry
Hoan Vu, Ngoc B. Pham, and Ronald J. Quinn, Journal of biomolecular screening,
2008, 13: 265-275.
CONFERENCE POSTERS PRESENTED
1)
Electrospray ionization fourier transform ion cycloton resonance mass
spectrometry as an affinity screen to detect noncovalent complexes from
natural product extracts
Presented at the Australian New Zealand Society for Mass Spectrometry (ANZSMS
20) conference at Adelaide 30th January 2005
2)
Bioaffinity
Fourier
transform
ion
cyclotron
resonance
mass
spectrometry for direct screening of natural product extracts
Presented at the international mass spectrometry conference (IMSC 2006) at Prague
27th August 2006
xxv
xxvi
Chapter one
CHAPTER ONE
INTRODUCTION ― A NEW APPROACH TO IDENTIFY ACTIVE
COMPOUNDS FROM NATURAL PRODUCT EXTRACTS USING
BIOAFFINITY MASS SPECTROMETRY
Abstract:
This chapter presents an overview of the concept of noncovalent
complexes, including the binding products of small molecule drugs and their
therapeutical targets. In a similar fashion, natural product crude extracts, a rich
source of small molecules with high chemical diversity that occupy a more drug-like
chemical space than synthetic sources, form noncovalent complexes with targets.
Identifying such complexes is a precondition for a drug discovery program and as
such an efficient, effective and accurate method is critically required. Mass
spectrometry, particularly coupled with electrospray ionization technique (ESI-MS),
is a promising analytical tool in biological research for a wide variety of
biomolecules such as small molecular mass compounds (<600 Da), DNA, RNA and
proteins. Bioaffinity mass spectrometry, characterized by its speed and sensitivity,
offers a desirable approach for the identification of these noncovalent complexes
1.1
SMALL MOLECULE – PROTEIN COMPLEXES
Paul Ehrlich introduced the concept of the interaction of physiologically
active substances with specific receptors into immunology throughout his works
during the 1880s and 1890s.1 Its application has expanded to histology,
haematology, and cell physiology and resonates in today’s biomedical science. The
key point of this concept is the recognition of chemically based receptors where the
binding of a chemical molecule (i.e. the ligand) to a biological target (i.e. the
receptor) mediates most physiological functions. This concept of a receptor
germinated in 1877 when Ehrlich studied the effect of dyes on a variety of tissues
and under a variety of conditions. In his publication,1 he proved that tissue staining
reactions are purely chemical rather than physical and certain dyes react
preferentially with certain cells or structures. This implied that the dye attaches to
some sort of receptor, based upon ionic charge or other characteristics. He also found
that different groups attached to the aniline core of the dye affected not only the
1
Chapter one
molecular charge, but also the solubility and strength of the attachment. Thus, the
chemical diversity of a core defined its biological function. The comprehension of
the concept of a receptor and a ligand has been improved by the ‘lock and key’
theory. Being introduced by Emil Fischer2 at the same time with the concept of
chemically based receptors, the ‘lock and key’ is a model for the basic scientific
explanation of the binding between a ligand and a receptor. In this theory, the ‘key’
symbolizes the small molecule or inhibitor and the ‘lock’ represents the enzyme,
protein or other biological targets. The lock and key theory proposes that only the
correct geometrically sized key fits into the keyhole (active site) of the lock. Wrong
key sizes (smaller or bigger sizes or sizes of incorrect geometry) will fail this
analogy and thus binding cannot occur. The two concepts have put together the
foremost requirement for a physiological effect between a small molecule and its
receptor: the suited core group of the small molecule together with its substitution
diversity. As a result of the binding, a small molecule - protein complex is formed.
Figure 1.1
“Lock and Key” model: the red key (ligand) has the right shape for
the lock (protein) and can interact with the protein to form a ligand - protein
complex. The blue key with unsuitable shape for the lock cannot fit and thus no
complex is formed.
The study of small molecule – protein interactions is but a subset of the
broader field of important interactions in which proteins participate. A chemical
2
Chapter one
bond between a molecule and a protein can be classified as covalent or noncovalent.
In a covalent bond, there is a new chemical bond formed by sharing pairs of
electrons between atoms of the two molecules. In a noncovalent bond, there are
different types of interaction responsible for the binding.3 These noncovalent
interactions include ionic bonds, hydrophobic interactions, hydrogen bonds, van der
Waals forces and dipole-dipole bonds. When a noncovalent bond is formed between
two biomolecules, the new entity is called a noncovalent complex. Most of the drugs
on the market now elicit physiological effects by forming a noncovalent complex
with a biological therapeutic target.4
A binding equilibrium of a small molecule - protein complex is expressed as
kon
PL
P+L
koff
where
•
P stands for protein, L for ligand or small molecule and PL for complex
•
kon is a bimolecular rate constant that is a measure of probability of
productive encounters between unbound protein and ligand (kon is
diffusion controlled and is limited to a rate 107 -108 M-1s-1).
•
koff is a unimolecular rate constant that is inversely proportional to τ, the
lifetime of the complex.
The binding affinity is calculated by equilibrium dissociation constant
Kd = [P][L]/[PL] = koff/kon
As a rough approximation, a tight binding characterized by a slow exchange rate will
have a Kd in the low μM range. A weak binding or fast exchange will have a Kd in
the high μM range. Both tight and weak binding can be detected by mass
spectrometry techniques.5-9
1.2
MASS
SPECTROMETRY
–
A
METHOD
TO
IDENTIFY
NONCOVALENT COMPLEXES
Mass spectrometry (MS) is a useful analysis tool in a wide range of scientific
fields since it is a versatile instrument. It can provide qualitative and quantitative
information about the isotopic, elemental and molecular composition of organic and
inorganic samples. These samples can be analyzed in the gas, solution or solid phase.
3
Chapter one
The analyzed masses can range from several Da (single atom),10 to 1 MDa (human
immunoglobulin M).11 Compared with traditional techniques of determining
biomolecule mass such as SDS-PAGE (sodium dodecyl sulphate polyacrylamide gel
electrophoresis) and gel permeation chromatography, MS can offer a mass accuracy
of better than 0.01%.12 Although MS does not provide as high resolution structures
of biomolecules as NMR or X-ray diffraction, MS has the advantages of speed,
sensitivity and accuracy when used for studying noncovalent complexes.
1.2.1
History of mass spectrometry in biological applications
The first mass spectrometer was constructed in 1907 by J. J. Thomson.13 It
was primarily to study the atomic mass of the elements, and was improved by F.W.
Aston to discover naturally occurring isotopes and measure relative isotope
abundances of most of the elements.14 These early instruments were later used for
studying heavy isotopes in different biological systems.15 In the early 1940s a mass
spectrometer was developed to analyze simple organic compounds, primarily
petroleum hydrocarbons.16,17 During the 1950s, a broad applicability of mass
spectrometric analysis for a wide range of organic compounds was introduced.18 In
1959 mass spectrometry was first used to sequence peptides.19 Routine structural
analysis of large peptides and very small proteins was not possible until 1981 with
the use of plasma desorption ionization (PD)20 and fast atom bombardement
ionization (FAB).21 The advent of two ionization techniques, matrix assisted laser
desorption ionization (MALDI, 1984) and electrospray ionization (ESI, 1988),
marked the beginning of a new era in biological applications for mass spectrometry.
These ESI and MALDI techniques further improved the ability of ionizing large
molecules, thus making MS an essential tool in characterizing structures of
nucleotides, proteins and noncovalent complexes.22 This growing importance of MS
was recognized in 2002 when the Nobel Prize for Chemistry was awarded to John
Fenn and Koichi Tanaka, who invented the ESI and MALDI techniques,
respectively, to be used for the study of bio-macromolecules.
4
Chapter one
Table 1.1
Timeline of biological mass spectrometry
Time
Use
1907-1940
Atomic mass-heavy isotopes
1940-1958
Organic compounds
1959-1980
Peptide sequencing
1981 till now
Protein, large molecules
1.2.2
Bioaffinity mass spectrometry in the identification of noncovalent
complex and potential drugs
The use of mass spectrometry to identify noncovalent complexes is called
bioaffinity mass spectrometry. Under well-controlled ESI-experimental conditions,
the weak specific-noncovalent interaction in a physiological solution can be
preserved and transferred intact into the gas phase.23 This nondenaturing ESI-MS has
identified many small molecule-protein noncovalent complexes. Ganem et al
24
first
reported the use of nondenaturing ESI-MS to detect noncovalent receptor-ligand
complexes formed between the immunosuppressive agents, FK506 and rapamycin,
with their naturally-occurring cytoplasmic receptor FKBP, a member of the
immunophilin family of immunosuppressive binding proteins. In another report
Ganem et al25 detected noncovalent enzyme-substrate and enzyme-product
complexes formed by hen egg-white lysozyme (HEWL) and various Nacetylglucosamine (NAG) oligosaccharides under physiological condition (NH4OAc
buffer, pH 5). Ganguly et al26 detected the ras-guanosine diphosphate (ras-GDP)
and ras-guanosine triphosphate (ras-GTP) complexes under physiological condition
(2 mM NH4OAc, pH 5.2) by ESI-MS. These complexes were important to the study
of abnormal cell growth, as well as to the development of anticancer drugs. More
studies about small molecule - protein noncovalent complexes were reviewed
extensively by Loo and Ashcroft.27,28 Nondenaturing ESI-MS has been used not
only to identify noncovalent complexes but also characterize them. Features of
noncovalent binding such as specificity, stoichiometry, association constant and
binding sites have been studied by nondenaturing ESI-MS.6,29-31
The identification of potential drugs that bind to a therapeutic target with
high affinity and selectivity requires screening libraries of compounds. The progress
in robotic techniques has allowed the development of high throughput screening
5
Chapter one
(HTS) which can process large numbers of compounds (more than 100,000
compounds per screen). The assays which are frequently used in HTS are
scintillation proximity assay (SPA),32 fluorescence resonance energy transfer
(FRET),33 time resolved fluorescence resonance energy transfer (TR-FRET),34 and
fluorescence polarization (FP).35 They are the first choices for HTS since they allow
automation and assay miniaturization. However, relying on cascade assays HTS
suffers from a lack of direct reading of the interaction between active compounds
and targets, which limits the ability to distinguish specific binding from non-specific
binding. For example, in FRET assay, HTS cannot discriminate between inhibition
and fluorescence quenching by an inner-filter effect of the test substance, which then
might lead to false-positive readings. This observable fact is very common in natural
product screening since a natural product extract contains a diverse pool of unknown
compounds of which the chance of being fluorescent is high. As a result of this
disadvantage a high number of false positives generates a considerable amount of
unnecessary work.
In response to this limitation, nondenaturing ESI-MS has been introduced as
a complement to HTS campaigns. Nondenaturing ESI-MS utilizes the soft ionization
technique to detect intact small (< 2000 Da) or large (up to 66,000 Da) noncovalent
complexes. Nondenaturing ESI-MS can provide the direct reading of the small
molecule drug - protein interaction. MS signals of unbound proteins and protein
complexes are observed and can be differentiated. The visualization of the protein
complex MS signal is the advantage of the nondenaturing ESI-MS technique in
which false positive readings can be minimized.
1.3
NATURAL PRODUCTS – AN INFINITE SOURCE OF MEDICINES
Natural products have historically been invaluable as a source of therapeutic
agents and traditional medicines. An impressive number of drugs have come from
natural sources. Well-known examples include erythromycin (1) and its derivatives
as antibiotics, cyclosporine A (2) and tacrolimus (3) as immunosuppressive agents,
doxorubicin (4) as antitumor agent, lovastatin (5) and derivatives as the best selling
anticholestoremic agents, reserpine (6) as an antihypertensive agent, ephedrine (7) as
an anti-asthma agent, aspirin (8) a derivative of natural products as an anti-
6
Chapter one
inflammatory agent, morphine (9) as an analgesic agent, and quinine (10) and its
derivatives for antimalarial agents.
Ο
O
O
OH
O
ΗΝ
O
Ν
OH O
OH
O
HO
Ο
ΟΗ
O
H
Ο
O
Ο
Ο
Ν
Ν
Η
Ο
N
Ν
Ο
Ο
OH
O
HO
HO
Ο
O
Ο
Η
Ν
Ν
Ο
O
O
ΗΟ
Ν
Ο
N
O
Ν
Ν
Η
O
O
H
O
HO
O
O
(1)
O
(2)
OH
HO
O
(3)
O
OH
OH
O
O
O
N
N
H
H
O
H
O
O
O
OH
H
O
H
O
OCH3
O
OCH3
H3COOC
OCH3
NH2OH
(4)
(5)
OCH3
(6)
OH
HO
N
O
OH
OH
H
N
N
O
O
N
H
CH3
(7)
O
O
HO
(8)
(9)
(10)
The rapid progress in genomics-based technologies yielding new potential
therapeutic targets,36 coupled with the high capacity of screening hundreds of
thousands of compounds in high throughput screening (HTS) on large libraries of
compounds have led many pharmaceutical companies to lean towards the massproduced combinatorial libraries, and cut back on their natural product research
programs.37 However, HTS of combinatorial compounds did not produce the
expected surge in the number of New Chemical Entities (NCE). For the twenty five
year period, from 1981 to 2006, there is only one synthetic combinatorial NCE
approved as cancer drug (sorafenib from Bayer, 2005).38 In contrast, the total
number of commercial drugs from natural products is much higher. From 1981 to
2002, products from the natural world have provided leads for 60% of the anticancer
7
Chapter one
drugs and 75% of the anti-infectious disease drugs.39 In 2004, of 24 NCE, 28% of
these were natural products. In 2005, 24% of 54 NCE were natural products or
natural product derived.
Nature has designed a remarkable diversity of core structures and functional
groups for specific biological activities in the course of evolution. Natural products
are diverse in chemical structures and show a variety of biological activities. Taxol
(11), a compound with complex structure, shows anticancer activities.40 Vancomycin
(12), an antibiotic with a complicated structure, is useful in the treatment of Grampositive bacterial infections.41,42 Histamine (13), a simple compound, shows wellcharacterized activities such as bronchocontriction, vasodilation, gastric acid
secretion and neurotransmission.43
The chemical diversity of natural products is illustrated in a significant
number of different core structures and in various combinations of functional groups.
Compared with synthetic compounds, natural products generally have a higher
number of stereogenic centres and more architectural complexity. These functional
groups or the precursors to such groups play a critical role in biological activity. For
example, the unsual trisulphide and quinone in two antitumour antibiotics,
calicheamicin (14)44 and dynemicin (15)45 are redox–activated triggers that initiate
aromatization cascades leading to the formation of diradical intermediates that
damage the DNA.
Structural analysis of collections of natural products also shows that they are
more similar to the chemical space occupied by drug molecules than synthetic
compounds.46,47 Beyond doubt, natural products are rich in terms of chemical
diversity and occupy both different and larger chemical spaces than that which the
products of synthetic chemistry can offer,48 and have proven their potential as an
infinite source of medicines.
8
Chapter one
OH
O
O
HO
H
N
OH
HO
OH
NH
O
O
HN
Cl
O
O
HO
OH
O
H
N
O
O
O
HO
O
NH2
O
O
O
OH HO
O
O
O
O
O
O
Cl
O
NH
NH
O
HO
O
NH
H
N
OH
O
HO
O
H2N
N
NH2
HN
(11)
(12)
(13)
O
O
HN
O
OH
O
O
C
HO
O
O
HO
I
O
O
O
S
O
OH
O
N
H
S
S
OH
OH
O
HN
O
OH
C
O
O
HN
OH
(14)
1.4
O
C
O
O
O
C
S
O
OH
(15)
RAPID AND EFFECTIVE SCREENING OF NATURAL PRODUCTS –
THE CHALLENGES
Recognizing a noncovalent complex formed between a biologically active
natural product and a therapeutical target, typically a protein is a key task in a drug
discovery program. A current popular way of searching for new drugs in natural
products is screening natural product extracts on therapeutic targets for the presence
of active compounds and subsequent investigation of their biological activities.49
This process involves bioassay-guided fractionation, which includes fractionating an
active extract and resubmitting each individual fraction to the high throughput
biological assay. This practice is time and labor intensive, as these steps have to be
repeated until the active compound is found. Bioassay-guided fractionation
screening of natural products also has a high rate of false positives and false
negatives due to the complex nature of natural product extracts. It prompts a
requirement for a quicker, simpler, more sensitive and effective method to screen
9
Chapter one
natural product extracts. The new method should have the capacity to detect the true
binder within a complex crude extract and give as much information as possible
about the active constituent, such as molecular mass for a rapid isolation of the
active constituent. One of the approaches is to use nondenaturing ESI-MS as a
screening tool because the analysis can provide the speed and sensitivity as well as
insightful information on ligand compositions and structures.
1.5
OBJECTIVES
The screening of natural product crude extracts for possible therapeutic
compounds is a complex process. It involves the identification of the noncovalent
complex formed by the interactions between the active components (ligands) in the
extract and a protein target. The challenges facing us, to date, are not only the false
positive and false negative results, but also the extensive time and labour required
for the identification and purification of those active components.
This thesis aims at developing an optimal strategy to: (i) detect the
noncovalent complex using nondenaturing ESI-MS; and (ii) provide molecular mass
of the active components. Once the ligand mass information is known, mass–
directed purification can replace the traditional bioassay guided fractionation, thus
time for the isolation of active component from crude extracts will be shortened.
To achieve these objectives, the following tasks must be fulfilled:
•
a successful direct reading of protein in native form by ESI-MS;
•
a successful direct reading of noncovalent complex by ESI-MS;
•
a successful direct reading of noncovalent complex in natural product crude
extract; and
•
a successful deduction of ligand mass information from noncovalent complex
mass information.
Additional information on chemical structure information of the ligand can
also be used as an early identification of known drugs or known class of drugs. This
information can be used in a screening program to avoid the reinvention of the
known drugs or to prioritize projects.
10
Chapter one
1.6
RESEARCH PLAN
This research has recognized natural products as invaluable sources of
biological active components and the advantages of electrospray ionization mass
spectrometry (ESI-MS) for the identification of small molecule - protein complexes.
With an aim to identify noncovalent complexes and to obtain chemical information
of active compounds at the screening stage, a research plan containing 3 major steps
has been undertaken in this study (Chart 1.1). Step one includes examining the
current challenges in identifying protein complexes by nondenaturing ESI-MS
(Chapter 2) and developing optimized conditions for electrosparay ionization Fourier
transform ion cyclotron resonance mass spectrometry (ESI-FTICR-MS) (Chapter 3).
Step two involves the developing of methods for identifying complexes of targets at
various molecular mass values (600 – 66,000 Da) in the setting of crude extracts
(Chapter 4 and 5). Step three aims at using these methods to screen natural product
extracts and identify noncovalent complexes formed by active natural product ligand
and protein targets, obtaining accurate molecular mass of active components and
their mass fingerprint. The active ligands are then purified. The binding of the pure
compounds with proteins is validated to confirm the accomplishment of the research
project (Chapter 4 and 6).
Chart 1.1
Research Plan
11
Chapter one
1.7
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Sharma J, Besanger TR, Brennan JD: Assaying small-molecule-receptor interactions by
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Nelson RW, Dogruel D, Williams P: Detection of human IgM at m/z approximately 1 MDa.
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Thomson JJ: Rays of positive electricity and their application to chemical analysis. London,
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Budzikiewicz H, Grigsby RD: Mass spectrometry and isotopes: A century of research and
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Chapter one
16.
Washburn HW, Wiley HF, Rock SM: The mass spectrometer as an analytical tool. Ind. Eng.
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Washburn HW, Wiley HF, Rock SM, Berry CE: Mass spectrometry. Ind. Eng. Chem., Anal.
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McLafferty FW: Mass spectrometric analysis. Broad applicability to chemical research. Anal
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19.
Biemann K, Gapp F, Seibl J: Application of mass spectrometry to structure problems. I.
Amino acid sequence in peptides. J Am Chem Soc 1959; 81: 2274-2275.
20.
Torgerson DF, Skowronski RP, Macfarlane RD: New approach to the mass spectroscopy of
nonvolatile compounds. Biochem. Biophys. Res. Commun. 1974; 60: 616-621.
21.
Barber M, Bordoli RS, Sedgwick RD, Tyler AN: Fast atom bombardment of solids as an ion
source in mass spectrometry. Nature (London, U K) 1981; 293: 270-275.
22.
McLafferty FW, Fridriksson EK, Horn DM, Lewis MA, Zubarev RA: Biochemistry.
Biomolecule mass spectrometry. Science (Washington, D. C.) 1999; 284: 1289-1290.
23.
Smith RD, Bruce JE, Wu Q, Lei QP: New mass spectrometric methods for the study of
noncovalent associations of biopolymers. Chem Soc Rev 1997; 26: 191-202.
24.
Ganem B, Li YT, Henion JD: Detection of noncovalent receptor-ligand complexes by mass
spectrometry. J Am Chem Soc 1991; 113: 6294-6296.
25.
Ganem B, Li YT, Henion JD: Observation of noncovalent enzyme-substrate and enzymeproduct complexes by ion-spray mass spectrometry. J Am Chem Soc 1991; 113: 7818-7819.
26.
Ganguly AK, Pramanik BN, Huang EC, Tsarbopoulos A, Girijavallabhan VM, Liberles S:
Studies of the ras-GDP and ras-GTP noncovalent complexes by electrospray mass
spectrometry. Tetrahedron 1993; 49: 7985-7996.
27.
Loo JA: Studying noncovalent protein complexes by electrospray ionization mass
spectrometry. Mass Spectrom Rev 1997; 16: 1-23.
28.
Ashcroft AE: Recent developments in electrospray ionisation mass spectrometry:
noncovalently bound protein complexes. Nat Prod Rep 2005; 22: 452-464.
29.
Griffey RH, Hofstadler SA, Sannes-Lowery KA, Ecker DJ, Crooke ST: Determinants of
aminoglycoside-binding specificity for rRNA by using mass spectrometry. Proc Natl Acad
Sci U S A 1999; 96: 10129-10133.
30.
Kempen EC, Brodbelt JS: A method for the determination of binding constants by
electrospray ionization mass spectrometry. Anal Chem 2000; 72: 5411-5416.
31.
Sannes-Lowery KA, Griffey RH, Hofstadler SA: Measuring dissociation constants of RNA
and aminoglycoside antibiotics by electrospray ionization mass spectrometry. Anal Biochem
2000; 280: 264-271.
32.
Udenfriend S, Gerber LD, Brink L, Spector S: Scintillation proximity radioimmunoassay
utilizing 125I-labeled ligands. Proc Natl Acad Sci U S A 1985; 82: 8672-8676.
33.
Selvin PR: The renaissance of fluorescence resonance energy transfer. Nat Struct Biol 2000;
7: 730-734.
13
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34.
Pope AJ, Haupts UM, Moore KJ: Homogeneous fluorescence readouts for miniaturized
high-throughput screening: theory and practice. Drug Discov Today 1999; 4: 350-362.
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Nasir MS, Jolley ME: Fluorescence polarization: an analytical tool for immunoassay and
drug discovery. Comb Chem High Throughput Screening 1999; 2: 177-190.
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Lenz GR, Nash HM, Jindal S: Chemical ligands, genomics and drug discovery. Drug Discov
Today 2000; 5: 145-156.
37.
McDonald LA: The challenge of using natural products as leads in modern drug discovery.
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MO, United States, November 7-10 2007: GENERAL-337.
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Cragg GM, Newman DJ: Natural product sources of drugs: plants, microbes, marine
organisms, and animals. Compreh Med Chem II 2006; 1: 355-403.
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Newman DJ, Cragg GM: Natural products as sources of new drugs over the last 25 years. J
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Wani MC, Taylor HL, Wall ME, Coggon P, McPhail AT: Plant antitumor agents. VI.
Isolation and structure of taxol, a novel antileukemic and antitumor agent from Taxus
brevifolia. J Am Chem Soc 1971; 93: 2325-2327.
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Sheldrick GM, Jones PG, Kennard O, Williams DH, Smith GA: Structure of vancomycin
and its complex with acetyl-D-alanyl-D-alanine. Nature 1978; 271: 223-225.
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Williamson MP, Williams DH: Structure revision of the antibiotic vancomycin. Use of
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Lee MD, Dunne TS, Chang CC, Siegel MM, Morton GO, Ellestad GA, McGahren WJ,
Borders DB: Calicheamicins, a novel family of antitumor antibiotics. 4. Structure elucidation
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Am Chem Soc 1992; 114: 985-997.
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Konishi M, Ohkuma H, Tsuno T, Oki T, VanDuyne GD, Clardy J: Crystal and molecular
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112: 3715-3716.
46.
Henkel T, Brunne RM, Muller H, Reichel F: Statistical investigation into the structural
complementarity of natural products and synthetic compounds. Angew Chem, Int Ed 1999;
38: 643-647.
47.
Feher M, Schmidt JM: Property distributions: Differences between drugs, natural products,
and molecules from combinatorial chemistry. J Chem Inf Comput Sci 2003; 43: 218-227.
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Harvey AL: Natural products as a screening resource. Curr Opin Chem Biol 2007; 11: 480484.
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Koehn FE, Carter GT: The evolving role of natural products in drug discovery. Nat Rev
Drug Discovery 2005; 4: 206-220.
14
CHAPTER TWO
MASS SPECTROMETRY TECHNIQUE AND ITS APPROACHES IN DRUG
SCREENING – PERSPECTIVES AND CHALLENGES FOR SCREENING
NATURAL PRODUCT EXTRACTS
Abstract: An overview about MS, ESI-MS, and ESI-MS screening approaches for
finding active drug compounds is presented. Background of Fourier transform ion
cyclotron resonance mass spectrometry (FTICR-MS) technique and the FTICR-MS
instrument used in this work are described. ESI-FTICR-MS direct detection of
noncovalent complexes is the approach chosen for this thesis. Significant challenges
still exist in the application of this method for natural product crude extracts.
2.1
MASS SPECTROMETRY BACKGROUND
Mass spectrometry is an analytical technique used to separate ions according
to their mass to charge ratio. In general, a typical mass spectrometer comprises of
three main parts, the ion source, the analyzer and the detector (Figure 2.1). Ions are
produced in an ion source, separated in a mass analyzer, and then detected and
transformed into a usable signal by a detector. The mass spectrometer must have a
good vacuum system to maintain the pressure far below the atmospheric pressure
(<10-6 mbar). A computer system is required to control and vary the analyzing
electric fields, introduce samples, create ions from the sample, transfer them into the
analyzer, and collect the analyzed ions; and display or record the results. Within
these shared requirements, different sources of samples, modes of ionization, and
types of analyzers have resulted in a broad set of different mass spectrometers. For
biologically related applications, MALDI and ESI have been the ionization
techniques of choice.
15
Chapter two
Ion source
Ion source
ESI
MALDI
Computer
Figure 2.1
2.1.1
Membrane
Denatured
protein
Native
protein
Vacuum
System
Membrane
Denatured
protein
Native
protein
Vacuum
System
Membrane
Denat red
A flow chart of a typical mass spectrometer
MALDI-MS
MALDI was developed by Tanaka et al.1 The analyte sample is co-
crystallized with a chemical matrix.2-4 A laser pulse results in the sublimation of the
matrix carrying the analyte into the gas phase (Figure 2.2).1,5,6 Ions are formed
during this process due to a combination of different mechanisms.7 MALDI-MS is
mostly used for protein sequencing. One of the most popular techniques is peptide
mass fingerprinting. In this technique, the protein is first digested and the masses of
the proteolytic peptides are obtained by MALDI-MS. The sequence of the protein is
determined by comparing these peptide masses with the fragment database obtained
from over 50,000 proteins.8-10 Small molecule-protein noncovalent complexes can
not be observed with the standard method of MALDI-MS since the protein is
denatured under the acidic matrix condition. However there have been reports of
using modified procedures to successfully analyze some protein-protein noncovalent
complexes by MALDI-MS.11
16
Chapter two
Mass Analyzer
Desorbed ion
Laser pulse
Matrix
Sample
Sample Plate
Figure 2.2
2.1.2
A schematic of matrix assisted laser desorption ionization (MALDI)
ESI-MS
The concept of coupling an ESI to a MS analyzer was first introduced in
1968 by Dole et al12 However, successful generation and detection of biomolecule
ions came later in 1984.13,14 Completely desolvated analyte ions acquired from the
ionization, evaporation and/or desorption processes in the ESI source are delivered
to MS analyzer under a force created by a combination of the electric field and the
pressure gradient. Ions of different mass, velocity and charge are moved differently
by the electrical field(s). If the field is carefully controlled, ions of different masses
and charges can be separated and categorized according to mass, charge and
abundance (Figure 2.3)
17
Chapter two
transfer
capillary
skimmer
Mass analyzer
flow rate
atmospheric pressure
vacuum
stage 1
Figure 2.3
vacuum
stage 2
vacuum
stage 2
A schematic of ESI-MS showing different vacuum transfer stages
(pressure gradient) and electric field between the spray needle and the mass analyzer.
The ESI source can be considered as an electrolytic cell (Figure 2.4). A high
potential of 2-5kV is generally applied to one side, the ESI emitter or the MS
entrance, and the other grounded. In positive ESI mode, the emitter is the anode
(oxidation) and the MS entrance the cathode (reduction). An electrolyte solution is
introduced into the emitter. The electric field provokes the separation of the positive
and negative charges in the solution. The positive charges accumulate at the emitter
tip and on the liquid surface. If the electric field is strong enough, a Taylor cone will
protrude from the emitter. A small liquid jet is then formed, from which charged
droplets are generated as a fine mist. The charged droplets produced by ESI are
situated in a hot atmosphere, which helps the evaporation of the solvent molecules of
the droplets. While traveling towards the entry of the mass spectrometer, the droplet
radius will decrease until the limiting radius of Rayleigh is reached, at which the
repulsive Coulombic force is equal to the surface tension force.15 The droplet
becomes unstable and produces smaller droplets, called offspring droplets. This
Coulomb fission process is repeated until there are small highly charged droplets.
The production of gas phase ions from these highly charged droplets is explained by
two theories; their mechanisms16 are illustrated in Figure 2.5.
18
Chapter two
Taylor cone
ESI droplets
Sample solution
mass analyzer
Oxidation
analyte ion
High voltage
power supply
Figure 2.4
A diagram of an ESI source
The first mechanism, the charge residue mechanism (CRM), was first
introduced by Dole et al. in 1968,12 and again in 1970.17 This mechanism proposes
that as the solvent evaporates, the offspring droplet decreases in size until the droplet
becomes unstable due to the large charge density on a small volume and large
surface tension of the droplet. When the repelling Coulombic forces come close to
their cohesion forces, the droplet divides into smaller droplets in order to get to a
stable state. The process continues until one droplet contains only one charged
molecule. This last droplet evaporates to give a completely desolvated ion.
The second mechanism, the ion evaporation mechanism (IEM), was
introduced by Iribarne and Thomson in 1975.18 It assumes that when a droplet is
highly charged, the electric field becomes large enough for the desorption of ions
from the surface to occur.
The major difference between CRM and IEM is that the final ion in CRM is
formed by evaporation of solvent from the droplet, whereas the final ion in IEM is
formed by desorption. The CRM is more likely to be valid for macromolecules,
whereas the IEM would be more plausible for small ions.19-23
19
Chapter two
a) Charge residue mechanism
ESI droplets
analyte ion
EVAPORATION
b) Ion evaporation mechanism
FISSION
DESORPTION
Figure 2.5
A schematic of two proposed ESI mechanisms a) charge residue
mechanism (CRM)
b) ion evaporation mechanism (IEM). Evaporation and fission
of droplets into smaller droplets leading to evaporation or desorption of analyte ion.
As a soft ionization technique, ESI transfers ions from a solution into the gas
phase in micro-droplets and produces a multi-charge effect for large molecules.24
The formation of ions is a result of the chemical process and of the accumulation of
charge in the droplets. The multiple charging effect in ESI brings the mass-to-charge
ratio (m/z) of large peptides and proteins within the nominal m/z upper limits for
mass analysis of 2000 to 5000 Da of most commonly availble mass analyzers. Of
particular importance for this thesis is that FTMS analyzer performance decreases
with increasing m/z, so the multiple charging effect of ESI is important to bring the
m/z of peptides and proteins into the range where FTMS has excellent performance.
Figure 2.6 shows a multi-charge effect obtained for ubiquitin (MM ~ 8,600 Da), with
the major ions produced being between 9+ to 13+.
20
Chapter two
Figure 2.6
Spectrum of ubiquitin at a denatured state (pH 3) with different
charge states. Spectrum was obtained by ESI on a Bruker FTICR-MS 4.7 Tesla
2.1.3
ESI-MS and conformational changes in protein
ESI mass spectra of a protein can reveal whether a protein remains in its
native folded state (pH = 7) or exists as a denatured state (pH = 1-3) in solution
phase. Figure 2.7 illustrates the correlation between the charge state of protein in the
gaseous phase and their folding structure in the original solution/solid phase. A
broad, low charge state protein mass spectrum (high m/z) is correlated to folded
(native) protein in solution, whereas a narrower, high charge state protein mass
spectrum (low m/z) corresponds to unfolded (denatured) protein.25
21
Chapter two
7+
a)
6+
8+
Membrane
Denatured
b)
15+
18+
13+
20+
Membrane
Denatured
m/z
Figure 2.7
An illustration of conformational changes in protein acquired by ESI-
MS. a) Charge states at high m/z for folded protein (in red) b) Charge states at low
m/z for unfolded protein (in green)
2.2
IDENTIFYING ACTIVE COMPOUNDS VIA DETECTION OF
NONCOVALENT COMPLEXES BY NONDENATURING ESI-MS
As described in the previous chapter, nondenaturing ESI-MS has been used
for detecting noncovalent complexes. The noncovalent complex ESI-MS screening
process consists of two steps. The first step is a formation of a complex using a
biological assay. In this step, a pure compound, mixture of compounds or a crude
extract is incubated with a biological target in which an active ligand then forms a
noncovalent interaction with the target and hence becomes a new entity together as a
complex. The second step is the detection of the formation of the noncovalent
complex by ESI-MS. There are two methods for this step. If the complex is detected,
the approach is called a direct method. If the active ligand is detected after the
dissociation of a complex, the method is called indirect.
22
Chapter two
DIRECT METHOD
Detection of active
cpds by recognising
noncovalent complex
INCUBATION
INTERACTION
Target + mixture of
compounds
Noncovalent complexes
(Target & active cpds)
SEPARATION
DISSOCIATION
OF
PROTEIN COMPLEX
protein complex
from
unbound compds
Step 1
Figure 2.8
Step 2
INDERCT METHOD
Detection of
active compounds
Step 3
A schematic of two ESI-MS approaches: direct (noncovalent complex
detection) and indirect (active compound detection)
2.2.1
Indirect noncovalent complex screening methods
This screening method is quite popularly applied in pharmaceutical industry
for screening combinatorial compound libraries. Traditional separation techniques
such as ultrafiltration, gel filtration or mobile separation techniques such as frontal
affinity chromatography can separate protein-ligand complexes from unbound
compounds (Figure 2.8). After being separated from unbound small molecule
compounds, the noncovalent complexes are dissociated by organic or acidic mobile
phase, then the small molecule ligands are analyzed by MS. The indirect approach is
widely used since it does not require a high-end MS technology. Any ESI mass
spectrometers such as quadrupole MS or time of flight MS can detect small
molecular ligands. However, this approach cannot see directly the noncovalent
complex or provide information about the stoichiometry of a complex. There are
other issues to be considered. Premature dissociation can happen in step 2 when the
complex is subjected to gel resins, ultrafiltration membranes or organic solvents. The
loss of protein complexes can give false negative results in step 3. Contaminations
can also happen at the separation stage between protein complexes and
inactive/unbound compounds (stage 2, Figure 2.8). The inactive/unbound compound
co-eluted with the protein complex in stage 2 can be detected as an active compound
by MS in stage 3, leading to false positive readings.
23
Chapter two
2.2.1.1 Indirect size exclusion - reversed phase liquid chromatography- mass
spectrometry method
Owing to a large difference in molecular mass between protein complex and
unbound small molecular mass ligands, physical separation of a complex from
unbound small ligands can be achieved on size-exclusion medium (Figure 2.9) After
being isolated, the complex is then dissociated. Several options are available for
ligand dissociation and the subsequent analysis. One of them is the dissociation of
bound compounds from the target protein directly on a reversed phase column
coupled to mass spectrometer for ligand determination.26 A simple alternative would
be the dissociation of a noncovalent complex by denaturing it with acidic organic
solvent.27 A large number of improvements for this technique have been reported by
pharmaceutical companies to screen large mixtures of compounds, such as
SpeedScreen by Novartis,28 and Automated Ligand Identification System (ALIS) by
Neogenesis.29 Different formats of gel columns from spin columns to well-plate gel
size-exclusion columns are used to improve the screening throughput.27,28,30 The
binding affinity can also be calculated from this method, as MS can be used as a
quantification technique to calculate the concentration of ligand bound to the target
protein.26,31
Figure 2.9
A schematic of indirect size exclusion reversed phase liquid
chromatography mass spectrometry method.
24
Chapter two
2.2.1.2 Indirect ultrafiltration mass spectrometry method
Ultrafiltration has been used for screening combinatorial compound libraries
and natural product extracts against protein targets such as adenosine deaminase,32
dihydrofolate reductase,33 cyclooxygenase-2,34 human serum albumin,35 and
estrogen receptors.36 The assay sample is placed in the ultrafiltration apparatus
which consists of two reservoirs separated by a molecular mass cut-off (MMCO)
membrane (Figure 2.10). Upon centrifugation, the free protein and complexes are
retained and concentrated in a small volume of retained solvent and free ligands with
solvent pass through the membrane. The complexes are then dissociated by either
organic or acidic solvents. Small molecule ligands formerly bound to the protein are
collected and identified by ESI-MS. In the ultrafiltration technique, excessive
centrifugation can cause false negative results and should be avoided. During
centrifugation, the dynamic equilibrium between protein and drug concentrations is
also disturbed. As the solvent with the free drug passes through the membrane, the
drug is depleted towards the right-hand side reservoir of the apparatus. As a result, a
re-establishment of the equilibrium between the protein and drug will happen in
favour of more discharge of free drugs. Thus the complex is further dissociated.
This effect is severe for weakly bound complexes.
Figure 2.10
A diagram of indirect ultrafiltration mass spectrometry method
25
Chapter two
2.2.1.3 Indirect frontal affinity chromatography mass spectrometry method
Frontal affinity chromatography has been used for screening combinatorial
compound libraries against protein targets such as epidermal growth factor
receptor,36 N-acetylglucosaminyltransferase V,37 estrogen receptor.38 This method
utilizes an affinity column. A protein target is covalently or noncovalently
immobilized on to the column beads. The compound mixture is continuously
pumped though the column (Figure 2.11). A mass spectrometer is connected to the
output of the column as a detector. A compound that has affinity for the immobilized
target will experience a delay in elution because it is retained, while a compound
with no affinity will elute quickly and will be in the void volume of the column. As
the flow rate through the column is known, the delay in elution of the bound
compound can be converted into a volume of the solution. The amount of the bound
compound in this volume is the amount interacting with the immobilized target at
equilibrium, the dissociation constant of ligand from target can be determined with
knowledge of the amount of target in the column.39 In this method large numbers of
compounds can be easily screened, the affinity column can be reused, throughput
can be increased with screening mixtures of compounds (up to 1000 components).37
However while being immobilized, the protein target can lose its biological function,
and therefore validation must be carried out to determine the protein function.
Figure 2.11
A schematic of frontal affinity chromatography mass spectrometry
method
26
Chapter two
2.2.2
Direct noncovalent complex screening method
A direct approach detects noncovalent complexes and looks at the molecular
mass of the noncovalent complex itself, from which the molecular mass of the active
bound ligand is deduced.40 This approach has the advantages of being able to
provide the stoichiometry of the complex,41 no sample contamination through
artefact binding with separation materials, and the ability to study the complex in
solution at physiologically relevant pH values.42 However, technical hurdles of this
direct screening has prevented the application of this method to all available
proteins. As proteins and complexes are normally preserved in detergents and
buffers such as Tris-buffer, phosphate buffers that are non-compatible with ESIMS,43,44 a buffer exchange process should be performed. The buffer exchange
method is critical in ESI-MS, and has been investigated extensively and is discussed
below. When a direct identification of a complex is coupled to a separation
technique for buffer exchange or semi-purification of unbound compounds, similar
shortcomings of the separation steps such as contaminations and premature
dissociation can occur. However, these aspects do not affect the readings of the
direct method as in the indirect method. For example, the unbound compounds can
elute together with the complexes. They might appear on the MS spectrum but since
they are not used as result readings the contamination effect can be ignored. As for
the premature dissociation, some considerations should be taken, for example the
separation setup should be validated on known complex models to test the complex
preservation capacity of the separation technique.
Figure 2.12
A schematic of direct noncovalent complex screening method
27
Chapter two
2.2.2.1 Desalting and buffer exchange - equilibrium dialysis
A MS incompatible, non-volatile buffer can be replaced with a MS
compatible, volatile buffer in a protein solution by a semi-permeable membrane.
This technique is known as equilibrium dialysis. The system consists of dialysis
tubing formed by a semi-permeable membrane, available in a wide range of MMCO.
This dialysis tubing is inserted in a larger volume container which holds the
exchanging buffer (volatile buffer). The protein in non-volatile buffer is introduced
into the dialysis tube. Large-sized protein which exceeds MMCO will remain inside
the tubing, small molecular mass volatile and non-volatile anions/cations will
transport in and out of the membrane. When the exchange reaches equilibrium, the
concentration of the non-volatile buffer outside and inside the tubing is equal. Over
time, the volatile buffer in the container will be renewed. At the end of the process,
the protein shall be in the volatile buffer, suitable for MS analysis. This method
requires time for the system to reach the equilibrium state and can only be performed
manually.
Figure 2.13
A schematic of buffer exchange using equilibrium dialysis
2.2.2.2 Desalting and buffer exchange - gel filtration
Gel filtration uses size exclusion to separate proteins from small molecules.
The separation takes place due to different access to the porous beads (gel filtration
media). Small molecules permeate to the pores of the gel filtration media, while
proteins are excluded from the pores and elute faster. Based on this characteristic,
28
Chapter two
gel filtration is used for the desalting and buffer exchanging of proteins in nonvolatile buffer. The gel column is first equilibrated with the volatile buffer. The
protein is introduced to the column with volatile buffer constantly passing through.
Small nonvolatile buffer molecules diffuse into the pores and elute later, whereas the
protein elute first together with the volatile buffer. There are many commercial gel
columns for desalting and buffer exchanging. The gel filtration process can be
automated, thus sample preparation time is shortened.
.
nonvolatile salt/buffer
protein coelute with
volatile slat/buffer
Gel
Figure 2.14
A schematic of desalting and buffer exchange using gel filtration
technique
2.3
DIRECT
IDENTIFICATION
OF
NONCOVALENT
COMPLEX
USING BIOAFFINITY ESI-FTICR-MS
Noncovalent complex identification is a complicated process. It deals with
multi-components in mass spectra, which generate a lot of difficulties in data
analysis and interpretation. A mass spectrometer, which performs with high
efficiency in making distinctions between different components, makes the task
easier. The performance of a mass spectrometer is determined by different factors,
such as:
- resolution: the capability to separate the peaks in the mass spectra.
- sensitivity: the ability to detect the lowest amount of the compound of interest.
- mass accuracy: the precision of molecular mass determination.
29
Chapter two
- dynamic range: the ratio of the most abundant ion intensity to the lowest abundant
ion intensity in a spectrum.
- speed: the time required to obtain a mass spectrum.
The ultra-high mass resolution, non-destructive detection, high sensitivity,
multistage MSn, and accurate mass-to-charge ratios (m/z) of ESI-FTICR-MS have
made it a valuable tool for the identification of noncovalent complexes. A successful
drug discovery and development program is heavily dependent on insightful
information about active small molecules early in the screening campaign. By this
standard, bioaffinity ESI-FTICR-MS as a screening method is increasingly attractive
in the pharmaceutical industry. Moreover, bioaffinity ESI-FTICR-MS also offers a
combination of techniques in which compositional, structural and thermodynamic
information on active ligands and ligand-protein complexes can be deduced.45-47
Therefore, this direct detection method is chosen in this thesis to identify
noncovalent complexes in natural products crude extracts.
2.4
FTICR-MS
2.4.1
From ICR-MS to FTICR-MS
The theory of ICR was first reported in the early 1930s by Lawrence and
Livingston.48 Ions which were excited simultaneously by a radio frequency electric
field and a uniform magnetic field, followed a spiral path in the analyzer chamber,
were detected sequentially by scanning the radio frequency or magnetic field. In the
late 1940s Hipple, Sommer, and Thomas built the first ion cyclotron resonance mass
spectrometer, the Omegatron, as a method to determine the Faraday constant.49 It
used a variable radio frequency field to excite the cyclotron motion of ions of
successive m/z to a radius at which they could collide with a collector plate as
detector. Wobschall introduced the marginal oscillator detector which measured the
ion resonant power absorption instead of counting ions on a collector plate.50 The
first commercialized marginal oscillator-type ICR-MS, was introduced in 1966 by
Varian.51 Until 1973 the marginal-oscillator detector was the most commonly
employed detection method for ICR-MS. This detection method was slow as it
required that the magnetic field be swept to bring ions of a single m/z at a time into
resonance with the marginal-oscillator frequency. In 1973 the concept of Fourier
transformation as the basis for ICR detection was introduced by Comisarow and
30
Chapter two
Marshall.52 With this idea, a whole spectrum of different m/z ions is excited and
detected at once. This development resulted in a new mass spectrometer, Fourier
transform ion cyclotron resonance mass spectrometer (FTICR-MS). FTICR-MS has
been continuously improved in mass range, mass resolving power and sensitivity.
Modern FTICR-MS has been extensively applied in various fields.53 Valaskovic et al
reported characterization of proteins (8-29 kDa) in low attomole concentration, with
a resolving power about 60000 and errors smaller than 1 Da.54 Resolving power of
8,000,000 was reported for molecular mass determination,55 and of 900,000 for
MS/MS sequencing of bovine ubiquitin (8.6 kDa).56 The molecular mass and
sequences of DNA and RNA verified with a mass error smaller than 10 ppm was
reported.57 These capabilities have made FTICR-MS an extremely powerful
analytical tool in analyzing noncovalent complexes in complicated matrices.
Table 2.1
Timeline of FTICR-MS development
Time
Author
Subject
1930
Lawrence & Livingstone
ICR theory
1940
Hipple, Sommer & Thomas
First ICR-MS
1965
Wobschall
Marginal oscillator
1966
Llewellyn
First commercial ICR-MS
1973
Marshall & Comisarow
FTICR-MS
2.4.2
FTICR-MS background theory
Figure 2.15
Movement of an ion in a homogenous magnetic field
FTICR-MS is based on the ICR principle. Ions generated by electron impact
ionization (EI), matrix assisted laser desorption ionization (MALDI), electrospray
ionization (ESI), or other ionization methods are trapped in the ICR cell which is
31
Chapter two
located in a homogenous magnetic field of a superconducting magnet. In the absence
of an electrical field, an ion with mass m and charge q moves in circular motion as a
result of the Lorentz force and the centrifugal force working on it in opposite
direction (Figure 2.15).
qvB = mv2/r
The angular frequency of this motion is given by:
ωc = v/r = qB/m
(1)
In which ωc is the cyclotron frequency in radians per second, B is the magnetic field
strength in Tesla, and m/q is the mass to charge ratio of the ions in kg/C.
The total charge on an ion can be described as:
q = ze
In which z is the net number of electronic charges on the ion and e is the charge per
electron in Coulomb (1e = 1.6022 x 10-19 C).
Equation (1) can be rewritten as:
fc = zeB/2πm = 15357 z B/m (2)
In which fc is the cyclotron frequency in Hertz, z is the charge state of the ion, and m
is the mass of the ion in Da (1 Da = 1.66054 x 10-27 kg)
Following (2) it is evident that ICR frequency is independent of ion velocity,
or of kinetic energy. Ions of a given mass will have the same ion cyclotron
frequency, regardless of the spread in the ions’ kinetic energy distribution. This
avoids the peak broadening and achieves ultra high mass resolution.
The equation (1) is the unperturbed cyclotron frequency in which there is
only a uniform magnetic field applied on the ICR cell. In reality an electrostatic DC
is applied to the trapping plate of the ICR cell to prevent the ions escaping along the
z axis. The combination of the magnetic field and the electrostatic field create three
motions in the cell: the axial trapping motion, the magnetron motion and the
cyclotron motion, and lead to the real cyclotron frequency which is smaller than that
of equation (1).
ωc real = ωc -ωm
in which ωm is the magnetron frequency.
To obtain high resolution and mass accuracy, the magnetron motion has to be
eliminated or minimized. High trap potentials and ion density increase the growth of
32
Chapter two
magnetron motion, whereas on-axis injection and longer injection times to increase
the symmetry of the trapped ion cloud minimize magnetron motion.
Coulomb interactions occur between an orbiting ion packet and other ion
packets or with the electrostatic trapping plates, cause frequency shifts and peak
coalescence effect (coupling of cyclotron frequencies) and affect the resolution and
mass accuracy. These so-called “space-charge” effects, which have been investigated
in recent years by a large number of research groups,58-64 can be generally avoided
by reducing the number of ions and using low trap voltages. Furthermore,
inhomogeneous electrostatic and magnetic fields can produce frequency shifts that
limit performance for FTICR-MS experiments.63,65 It is foreseen that the detection
of noncovalent complexes in crude natural product extracts will seriously impact on
the frequency shifts due to high ion population and complex mixture of high and low
abundant components.66,67
2.4.3
FTICR-MS instrumentation
A combination of ICR analyzer cell and FT methodology makes the FTICR-
MS available. The ICR analyzer cell is located inside a superconducting magnet with
fields of 3.0, 4.7, 7.0, 9.4, 12.0, and recently 15.0 Tesla. The higher the field, the
better the resolution and sensitivity.68 The ICR cell shown in Figure 2.16 is
composed of three opposed pairs of electrode: trapping, excitation and detection.
Ions generated from external ion sources, ESI or MALDI, are trapped inside by a
low DC potential applied to the trapping electrodes and by the axial magnetic field.
The applied trapping potentials will confine the ions in the axial direction, but it also
creates a potential hill in the radial direction to pull the ions away from the centre of
the trap in the radial plane. However, the axial magnetic field will prevent the ions
from hitting the cell wall because the Lorentz force on the ions forces them into a
circular orbit. All ions with different cyclotron frequencies (or different m/z) in the
cell are excited by applying a radio frequency (RF) sweep, over the range of
cyclotron frequencies of the ions, to the excitation electrodes parallel to the magnetic
field. Ions with the same m/z, which have the same frequency, are excited to a large
radius and form phase-coherent ion packets. These orbiting ion packets induce
charges or an imaged current on another pair of electrodes, detection electrodes. A
broadband amplifier magnifies this induced current which is a composite of the
33
Chapter two
cyclotron frequencies (or m/z) of all ions. Fast Fourier transform is applied to extract
the frequency and amplitude for each component by converting this induced current
from the time domain into the frequency domain. The frequency spectrum is
converted to the m/z spectrum by applying the cyclotron equation (2).53,69
Figure 2.16
A schematic of a typical FTICR-MS, from ion trapping, excitation,
detection and Fourier transformation (from time domain to frequency or mass
domain).
Excitation can be performed by using different wave form methods such as
single frequency chirp, correlated frequency chirp, or stored-waveform inverse
Fourier transform (SWIFT). Further ion excitation can be used to eject ions from the
trap in multistage MS (MSn) or to increase kinetic energy above the threshold
required for dissociation.
Image current detection is attractive for several reasons. First, the derived
signal increases linearly with ion number, which makes quantitation possible.70
Second, the non-destructive detection allows ion remeasurement contributing to
ultrahigh-resolution measurements and particularly for applications with scarce
sample.71,72 Finally, the signals from any m/z ratio can be detected simultaneously
and sorted out by Fourier transform giving FTICR-MS a multi-channel advantage
over scanning instruments.73
34
Chapter two
2.4.4
ESI-FTICR-MS
The coupling of electrospray ionization (ESI) to FTICR-MS has greatly
advanced the capabilities of mass spectrometry for biological applications.74 Due to
its high mass accuracy, and superior mass resolving power, many applications of
ESI-FTICR-MS involve the determination of the chemical composition of molecules
based on accurate mass.75,76 ESI-FTICR-MS is useful in dealing with complex
mixtures without prior separation,77 allowing the signals of two ions of similar mass
to charge (m/z) to be detected as distinct ions. The high resolution of FTICR-MS and
the multiple charging of ESI make ESI-FTICR-MS extremely useful in determining
accurately the mass of large biomolecules such as proteins or protein complexes.78
The exact stoichiometry of the complex can be deduced from this exact mass
information.41 Another advantage of using ESI-FTICR-MS for detecting intact
noncovalent complexes is that the parameters of desolvation process with ESIFTICR-MS, sufficient heating and activation for ion desolvation, can be adjusted to
preserve noncovalent complexes well.79
2.4.5
Instrument used in this thesis
A picture of the ESI-FTICR-MS used in this thesis is shown in Figure 2.17.
An actively shielded 4.7 Tesla superconducting magnet (Magnex Scientific Ltd.,
Oxford, U.K.) is cooled in a cryosystem by liquid helium to 4.2 Kelvin.
The
horizontal bore of the magnet is lined up with a metal frame supporting a vacuum
system, ion sources and a gas inlet system. Data acquisition and analysis is
performed using Xmass software running on a 1200 MHz Pentium III data station
under Windows 2000 operating system.
35
Chapter two
Figure 2.17
ESI-FTICR-MS instrument, Bruker 4.7 Tesla
A schematic cutaway view shows different pressure regions of the ESIFTICR-MS (Figure 2.18). The vacuum system has two regions, the ultra high
vacuum analyzer and the source vacuum. The ultra high vacuum system is capable
of sustaining a base pressure of below 4 × 10-10 mbar using two Alcatel
turbomolecular pumps backed by an Edwards rotary pump. The source vacuum
system has a base pressure of 10-6 mbar using also two turbomolecular pumps, one
Alcatel and the other Edwards, backed by an Edwards rotary pump.
Figure 2.18
A schematic cutaway view of FTICR-MS instrument (Bruker manual)
Besides a superconducting magnet and a good ultra high vacuum system, a
FTICR-MS instrument has three other main parts:
- External ion sources: any kind of existing ion sources such as ESI, MALDI where
the ions are generated.
36
Chapter two
- Ion transfer line: ion optics to transfer the ions through the differential pumping
restrictions to the cell.
- ICR cell: where the ions are trapped, excited and detected
2.4.5.1 ESI source
The ESI source of our FTICR-MS is called Apollo source (Figure 2.19). The
main components of this source are: the off-axis grounded nebulizer, high voltage
endplate, glass ion transport capillary, skimmer 1, pre-hexapole, skimmer 2, main
hexapole, and the trapping/extracting electrode.
Figure 2.19
ESI -Apollo source diagram (Bruker manual)
The nebulizer is off-axis and grounded. The distance from the nebulizer to
the end plate is about 1.5mmm. Sample solution is introduced into the spray chamber
through the nebulizer. A fine spray of charged droplets is generated by means of an
electrical field between the inner chamber wall and the end cap, with the assistance
of a nebulizer nitrogen gas. Heated drying nitrogen gas, flowing counter current to
37
Chapter two
the stream of the droplets, facilitates the desolvation and thus the ionization of the
droplets. Ions are attracted by the electric force towards the inlet glass capillary, 15
cm in length, 0.5 mm in diameter and platinum capping at both ends. The capillary is
the interface between the atmospheric pressure and the vacuum. Ions are transferred
through the capillary, out of the capillary exit and enter into the source vacuum.
Figure 2.19 illustrates that ions pass from the capillary exit through skimmer 1 and
enter into pre-hexapole which is biased at the same voltage as skimmer 2. After
streaming through the pre-hexapole and skimmer 2, ions are accumulated in the main
hexapole which is biased at a DC offset voltage. Ions are now trapped between the
skimmer 2 and the trap/extract electrode (the gate) by applying a positive voltage,
for positive ions, to the electrode. After a user pre-determined time (d1), the voltage
of the trap/extract electrode is dropped and ions emerge from the hexapole. The gate
remains open for a user defined time (d2). At the end of the gate pulse, the voltage
applied to the trap/extract electrode is raised again and the next cycle of ion
accumulation in the hexapole begins. With this trap/extract setup, ions can be
injected in ion pulses from a continuous ESI source into the ICR cell.
Raising the potential difference between the transfer capillary exit and the
skimmer 1, the collisions convert the kinetic energy of the sample ions into internal
energy inducing fragmentation of the ions by which structural information can be
obtained. This process is called in source Collision Induced Dissociation (CID). All
source parameters which control the desolvation and dissociation process such as
flow rate, desolvation nebulising gas pressure, drying gas, end plate voltage,
capillary voltage, temperature, capillary exit voltage, skimmer 1, and skimmer 2 can
be accessed within Xmass tune page shown in Figure 2.20.
38
Chapter two
Figure 2.20
Xmass tune page for ESI source
2.4.5.2 Ion transfer line
The electrostatic ion transfer line is a combination of deflection plates: PL1,
PL2 and PL4, high acceleration voltage: XDFL and YDFL, and Einzel lens: FOCL1,
PL9 and FOCL2 (Figure 2.21). Ions which are produced from the ESI source are
focused through differential pumping restrictions by accelerating them to high
potential energy. A high energy ion beam can be focused more tightly than a lower
energy beam. Ions are then de-accelerated to facilitate ion capture in the analyzer or
trapping cell.
Figure 2.21
A schematic of the ion transfer line (Bruker Manual)
39
Chapter two
The values of the electric field potentials, which can be plotted against the
transfer optic coordinate, show the acceleration and de-acceleration of the ions
towards the analyzer cell (Figure 2.22).
Figure 2.22
Electric potential values of the ion transfer optic line (Bruker
manual). A decrease voltage value from +1 V to -2.5 kV helps to accelerate the ions.
An increase voltage from -2.5 kV to +1 V makes the ions slowly enter into the ICR
cell
2.4.5.3 ICR cell
The quest for higher resolution has led many researchers to explore different
FTICR-MS cell designs. Most cell designs are a compromise of resolution, mass
accuracy, ion capacity and complexity. Dozens of cell designs have been evaluated,
but the majority of cells in use today still are of the simple cubic or cylindrical
design. As shown in Figure 2.23, the Bruker analyzer ICR cell or Infinity cell has six
electrodes: two trap electrodes with trapping voltages PV1 and PV2, two excitation
electrodes and two detection electrodes. The Infinity cell has also two sidekick
electrodes which are used for sidekick trapping technique, which is very useful in
LC-FTICR-MS.80
40
Chapter two
Figure 2.23
a) a photo of Bruker Infinity cell
b) a drawing of Bruker Infinity
cell
2.4.6
Time sequence for ESI-FTICR-MS experiments
A standard ESI-FTICR-MS experimental time sequence is shown in Figure
2.24a. The experiment starts with a cell quench by applying a negative potential (15V for ESI positive mode) on the rear trapping so that all ions are surely ejected
from the ICR cell. The next step is the introduction of ions into the cell. Excitation of
the ions is carried out by frequency chirp excitation. The excitation is switched off
before the detection takes place.
The experimental time sequence of a MS2 experiment is illustrated in Figure
2.24b. After the ions are trapped in the cell, isolation of the ions of interest is
performed by correlated sweep or correlated shot excitation. The aim of the isolation
pulse is to eliminate all unwanted ions by exciting them to collide with the cell wall.
MS2 experiment begins with the pumping of argon gas into the cell. The selected
ions are collided with the argon gas, and activated by on resonance or sustained off
resonance irradiation (SORI). After a pumping delay to allow the ultra high vacuum
of the ICR cell to return to normal, the excitation and detection event of the
fragmented ions follows. Similarly the sequence of a MS3 experiment can be
designed by adding an isolation event and MS3 activation step. The results of MS2,
MS3, and MS4 experiments are described in Chapter 4.
Different fragmentation methods used for the MS2, MS3 or MSn experiments
are on resonance CID, SORI-CID, infrared multiphoton dissociation (IRMPD) and
electron capture dissociation (ECD). The advantage of SORI-CID, the method used
in this thesis (Chapter 4), has the advantage that it can use low activation energy for
multiple collisions between the selected ions and the inert gas (argon) for an efficient
fragmentation.
41
Chapter two
Figure 2.24
a) A standard time sequence of an ESI-FTICR-MS experiment b) A
time sequence of an ESI-FTICR-MS2 experiment using on-resonance CID or SORICID method.
2.4.7
Liquid chromatography-FTICR-MS (LC-FTICR-MS)
LC-FTICR-MS experiments are carried out by the coupling of an Agilent
1100 series HPLC (high performance liquid chromatography) with FTICR-MS
(Figure 2.25) The Agilent HPLC is controlled by Chemstation software. The Bruker
Xmass software for control of the FTICR-MS is triggered for data acquisition by a
contact closure connected to the Agilent HPLC autosampler. Xmass pulse
programming is adapted for running LC-FTICR-MS experiments and also for
unattended automated operations.
Figure 2.25
HPLC coupled to ESI-FTICR-MS
42
Chapter two
2.5
CHALLENGES
FOR
SCREENING
NATURAL
PRODUCT
EXTRACTS USING BIOAFFINITY ESI-FTICR-MS
ESI-FTICR-MS has proven to be a powerful tool in the study of noncovalent
complexes,81-83 particularly because the method is well suited for high throughput
affinity screening, and a variety of types of complexes are able to be analyzed. For
example RNA has been used as a target for drug discovery in an assay called multitarget affinity-specificity screening.84 Synthetic and natural products libraries are
screened in a robust manner by taking advantage of the high resolution and high
precision mass measurements of intact RNA-ligand complexes. With this assay, the
identity of the small molecules that bind, the RNA target to which it binds and the
compound-specific binding affinity can be determined in one set of rapid
experiments. Other examples of RNA binding include the determination of
stoichiometry and affinity with HIV-1 nucleocapsid protein,45 or the investigation of
binding modes and structural determinants of noncovalent complexes formed by
aminoglycoside antibiotics with Ψ-RNA.85 Protein-ligand complexes are also studied
by ESI-FTICR-MS for ligands including oligosaccharides,86 peptides,87 and other
proteins.88 A screening of a compound library of about 300 peptide compounds
against bovine carbonic anhydrase II using bioaffinity ESI-FTICR-MS was
performed by Gao et al89 Bioaffinity characterization mass spectrometry, a highly
sensitive and high resolution method using FTICR-MS, without the use of
separations has been reported by Bruce et al90 to support drug development.
Despite its strengths, in pursuit of the ultimate goal of the identification of
protein complexes in their physiological setting and in natural product extract
matrix, bioaffinity ESI-FTICR-MS is still in need of improvement. For example,
bioaffinity ESI-FTICR-MS still has technical limitations, particularly when ion
signals of the complexes (multicharged ions) exceed a few thousand m/z, which is
above the typical m/z range of FTICR-MS, and/or form large adduct clusters,76 or
when the sample matrix is complicated as in natural product crude extracts,23,91-93 or
when the sample preparation is intricate, such as protein with a nonvolatile buffer
which is incompatible with the ESI process.94 Problems of the same or a more
complicated nature will be undertaken in this research. For example, the challenge of
obtaining an optimal condition for the complex desolvation and preservation when
many instrumental factors control the whole process will be investigated in Chapter
43
Chapter two
3 and the problem of buffer unsuitability, buffer exchange and natural product matrix
will be examined in Chapter 5. Mass accuracy for ligands will be enhanced by the
use of dual spray ESI-source for internal calibration (Chapter 4) or by the use of
different methods such as the deduction from the MS spectrum method and the
trapping method with in source and SORI-CID dissociation technique (Chapter 5 and
Chapter 6). Application of different MS techniques such as SORI-CID and
multistage MS is employed for additional information on small ligands (Chapter 4).
2.6
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Xiang X, Grosshans PB, Marshall AG: Image charge-induced ion cyclotron orbital
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Gorshkov MV, Kouzes RT: Possible applications of an external resonant circuit in Fourier
transform ion cyclotron resonance. Rapid Commun Mass Spectrom 1995; 9: 317-321.
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Mitchell DW: Theory of trapped ion motion in the non-quadrupolar electrostatic potential of
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Nikolaev EN, Miluchihin N, Inoue M: Evolution of an ion cloud in a Fourier transform ion
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Mitchell DW, Hearn BA, DeLong SE: Excitation electric field inhomogeneities in a cubic
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Masselon C, Tolmachev AV, Anderson GA, Harkewicz R, Smith RD: Mass measurement
errors caused by "local" frequency perturbations in FTICR mass spectrometry. J Am Soc
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Kruppa G, Schnier PD, Tabei K, Van Orden S, Siegel MM: Multiple ion isolation
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FT-ICR
MS:
exact-mass
MSn
internal
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and
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Hendrickson CL, Drader JJ, Laude DA, Jr.: Simplified application of quadrupolar excitation
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4614-4624.
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Mendes MA, Souza BM, Marques MR, Palma MS: The effect of glycerol on signal
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Neth) 2004; 18: 339-345.
50
CHAPTER THREE
OPTIMIZATION STRATEGY FOR MASS SPECTROMETRY IN THE
OBSERVATION OF NONCOVALENT COMPLEXES
Abstract: An optimization strategy for ESI-MS in the identification of noncovalent
complexes is proposed. Two sets of three level fractional factorial designs were
employed using nine instrumental parameters to obtain a high signal to noise ratio
for protein complexes. Significant effects of factors were determined graphically and
statistically. An understanding of the parameters that are most influential and the
effects of these parameters on the mass spectrum is required for optimization. The
optimization route examined carbonic anhydrase complexed with ethoxzolamide as a
model.
3.1
INTRODUCTION
In the drug discovery process, the sensitivity of detection instruments is a
critical issue for a successful outcome. The response of instruments or methodology
is sometimes governed by many interdependent factors, of which the number of
factors can be up to 7.1 The complexity created by many influential factors on an
instrument has led to many studies on optimization methods. One of the methods
that has been greatly investigated in the last decade is fractional factorial design.
Compared with the old non-economical approach of varying one factor at a time,
fractional factorial design approach (FFD) is more efficient. FFD allows analyzing
major effects, determining main secondary interaction and confounding some
interactions on a small number of experiments.2-4 Mathematic algorithms have been
used to design sets of experiments to suit certain optimization objectives such as
factor screening, factor interaction and ultimately optimal conditions. These designs
have been applied in many scientific fields such as instrumental optimization,5,6 or
procedures in synthetic chemistry,7 or animal toxicity studies in pharmaceutical
industry,8 leading to useful savings of scientific resources.9-12
A FFD consists of a number of runs (N) and a number of factors (n),
represented as a N x n matrix. In this matrix, each run (treatment combination)
represented by row and each factor by column. A three-level FFD has each column
51
Chapter three
taking on three different value levels: low (-1), medium (0) and high (+1). If nine
parameters are investigated in three value levels (low, medium, and high), there
should be 39 or 19683 experiments to be performed to obtain the optimum tuning
condition for noncovalent protein complex ions. This difficult task can be eased
using FFD in which a smaller number of experiments can also accomplish the same
objective. Research by Xu13 on ranking FFDs using minimum aberration criterion
has provided a complete collection of designs with 27 runs. These models are
designed especially for optimization experiments in which factors are treated
equally. Another study by Xu, Cheng and Wu14 on projection and moment aberration
criterion has proposed designs for factor screening, projection and interaction
detection. These two sets of designs will be used in this study for determining the
optimum condition to detect bovine carbonic anhydrase (bCA II) protein complex by
ESI-FTICR-MS.
Two processes control the identification and the determination of a protein
complex by ESI-MS: the preservation of the protein complex and the desolvation of
complex ions. In the preservation process, proper solution conditions should be
determined to keep a protein complex in its folded and native state. Acidified
solutions containing a high proportion of an organic solvent (e.g., methanol,
acetonitrile) are typically used for ESI-MS. However, proteins and protein
complexes will be denatured in these organic solvents. Biological assays normally
use detergents, salts, or buffers as assay media. Detergents often used to extract
proteins from various organisms such as sodium dodecylsulfate (SDS), sodium
taurocholate, Triton X-100, n-dodecyl sucrose have been found to strongly decrease
ESI signals due partly to the contamination of the non-volatile properties.
Nonvolatile salts have been shown to rapidly accumulate on the surface of
electrospray source parts and degrade the MS detection sensitivity.15 Nonvolatile
materials also suppress the formation of small droplets, which in turn negatively
affects the production of gas phase analyte ions.16 Buffers, which have physiological
characteristics to preserve proteins, have been studied. To date, the volatile buffers
which have been mostly used with ESI-MS to investigate proteins in a
nondenaturing state are ammonium acetate and ammonium bicarbonate.17
Ammonium acetate and ammonium bicarbonate do not form extensive gas phase
adducts with the macromolecules. The background ion formation is also reduced
52
Chapter three
without significant reduction in protein ion formation. Buffer concentrations are
normally at the 5-50 mM concentration levels, but sometimes can be as high as 500
mM to maintain protein dimerization.18
In the desolvation process, an efficient and effective evaporation condition
for the ESI-generated droplets is the key factor for a successful MS ionization and
should be established. Parameters such as flow rate, nebulizing gas pressure, drying
gas, end plate voltage, capillary voltage, temperature, capillary exit voltage, skimmer
1, and skimmer 2 are the instrumental factors affecting the desolvation. These
mentioned 9 parameters provide energy for solvent evaporation along the path from
the atmospheric region to the high vacuum region, focusing the ions and at the same
time potentially causing complex dissociation. Although ESI-MS is a gentle
ionization process that can transfer intact noncovalent complexes from solution
phase into the gas phase, noncovalent complexes, however, can be disrupted under
harsh experimental conditions, if these parameters are not chosen properly. A
balanced distribution of energy by these parameters for complete desolvation, but
still preserving complex ions requires a study on the interactions among these
parameters. Knowledge of the main parameters is very significant towards the
achievement of optimum conditions for protein complex detection. The following
approach is proposed for identifying the optimal condition of protein complexes by
ESI-MS:
Step 1: Investigation of the MS response when protein complex interacted
with ammonium acetate or ammonium bicarbonate. Suitable assay buffer condition
is to be identified.
Step 2: A large range in values of a parameter is good for a general and broad
view of interactions between factors, but not without a sacrifice of experimental
resolution. Therefore, with the aim of achieving the optimum condition,
experimental values of factors are to be chosen in a moderately narrow region. In
step 2, experiments will be performed to determine the appropriate range for
capillary exit voltage, a factor known to control the dissociation of complexes.19
Step 3: Identification of main factors using FFD for factor screening and
interaction. The interaction and effect of these parameters will be investigated using
a FFD design by Xu, Cheng and Wu.14 Factors that are considered important will be
studied in the second FFD for optimal condition. (Step 4)
53
Chapter three
Step 4: The optimal condition is to be determined using FFD with minimum
aberration criterion. FFD will be applied to design experiments using the major
factors identified in Step 3 with three different levels in order to obtain the optimal
tuning condition for the observation of the noncovalent complex bCA IIethoxzolamide. Treating all these factors as being equally important, a twenty-sevenrun experiment at three levels with minimum aberration studied by Xu.13 is to be
employed.
3.2
MATERIALS AND METHODS
3.2.1
Materials
Bovine carbonic anhydrase II (bCA II, EC 4.2.1.1, MM 29089 Da) was
purchased from Sigma-Aldrich, and used without further purification. It was
dissolved in ammonium bicarbonate (10 mM, pH 8) to generate stock solution (34
µM). Ethoxzolamide (16) was also purchased from Sigma-Aldrich. It was dissolved
in methanol to generate stock solutions (400 µM).
Table 3.1
Structure and binding constant of ethoxzolamide, an inhibitor of bCA
II
Inhibitor name
Ethoxzolamide20,21
Inhibitor structure
C2H5O
Kd
0.25 x 10-9 M/
S
SO2NH2
0.15 x 10-9 M
N
(16)
3.2.2
Instrument
For step 1: Samples were injected directly by a Cole-Parmer syringe pump
with a flow rate of 2 μL per minute. The end plate voltage was biased at -4000V and
the capillary voltage at -4500V relative to the ESI needle during data acquisition. A
nebulizing N2 gas with a pressure of 50 psi and a counter-current drying N2 gas with
a flow of 30 L/min were employed. The drying gas temperature was maintained at
125°C for direct infusion analysis. The capillary exit voltage was tuned at 140 V,
and skimmer 1 voltage at 23.5 V, and skimmer 2 at 16 V.
54
Chapter three
For step 2: The parameters were the same as for step 1, except capillary exit
voltage values were varied from 70 to 160 V with an increment of 10 V.
For steps 3 and 4: Parameter values are listed in Table 3.2.
3.3
RESULTS AND DISCUSSION
3.3.1
Step 1: Assay buffer condition
For nondenaturing ESI-MS, the buffer pH and choice of buffer are two
important factors. The buffer pH must be the same as that of physiological condition
so that denaturing of protein does not occur and the formation of protein-ligand
complex can take place. In this case, the pH of the ammonium bicarbonate solution
was at 8.0 and of ammonium acetate was at 6.9. Both were in the range of
physiological condition needed for the protein to maintain in its native form Nonvolatile buffers which have been mostly used in biological process are not
compatible with ESI–MS as they interfere with the ESI process and cause loss of
sensitivity.22 The study using ammonium acetate and ammonium bicarbonate at 10
mM showed that protein complexes were observed at a good signal to noise ratio
(S/N). The S/N for the complex in acetate solution is 80,000/scan and for
bicarbonate solution is 120,000/scan. The results showed that both buffers were
suitable for the detection of protein complexes. However, there was a significant
increase of about 1.5 times in signal intensity of bCA II-ethoxzolamide complex
when 10 mM ammonium bicarbonate buffer was used, compared with 10 mM
ammonium acetate buffer under the same instrument tuning condition (Figure 3.1).
The better response observed when the complex was in ammonium bicarbonate can
be explained by its higher heat of vaporization. It is known that ion species in the
ESI source receive energy from the applied voltage at various steps in the ESI
source, part of this energy is used for this desolvation process. When the desolvation
is completed, the remaining energy is deposited as internal energy on the fully
desolvated ions. As this internal energy is the available energy for the dissociation of
protein complexes, the smaller the energy the better the preservation of complex ions
will be. Since the bicarbonate anion has higher hydration energy than the acetate, an
energy of 710 kJ/mol for bicarbonate anion and of 695 kJ/mol for acetate anion,23 a
greater amount of energy was needed for the desolvation of protein complexes
interacting with bicarbonate. After the desolvation step, it is obvious that the internal
55
Chapter three
energy deposited on complexes associated with bicarbonate buffer should be smaller
than the one deposited on complexes in acetate buffer. Therefore, in the
experimental conditions, protein complexes in ammonimum bicarbonate were
preserved better than in ammonimum acetate, as shown in Figure 3.1.
Ammonium bicarbonate has a good buffering capacity at pH 8, is stable at
room temperature, decomposing at temperature above 60 oC to form ammonia,
carbon dioxide and water. These physical and chemical properties make ammonium
bicarbonate compatible with MS. It is also noted that ammonium bicarbonate buffer
vaporizes rapidly in the MS source leaving no residues. Therefore the MS system
has no contamination and does not need frequent cleaning. Ammonium bicarbonate
was therefore chosen as a buffer for steps 2-4.
Figure 3.1
Difference in intensity of bCA II-ethoxzolamide in 10 mM
ammonium acetate and in 10 mM ammonium bicarbonate buffer
3.3.2
Step 2: Experimental value region for ESI-MS parameters
Figure 3.2 shows the diagram of the ESI-MS ion source used in this thesis.
Protein complexes are delivered into the ESI-MS spray chamber at a low flow rate
(normally 1-10 μL/min). This solution is sprayed into a limited space in the chamber
by nitrogen gas coaxially applied at a suitable flow rate. An electrospray of this
protein complex is produced if a strong electric field is applied with a potential
difference of 3-6 kV between the needle and the end plate. Charged droplets are then
created and also become desolvated in the spray chamber. These charged droplets
are channeled from the spray chamber at atmospheric pressure to the vacuum region
56
Chapter three
by a difference of potentials between end plate and capillary and gas flow. The
general differences are normally in the range of 500-700 V. In the region between
the end plate and the capillary, the sprayed complex ions are desolvated further by
the nitrogen drying gas. Heat is applied in this region to maintain the high rate of
evaporation because during evaporation there is a strong evaporative cooling of the
drop.24 The droplets and desolvated ions are moved completely by the gas flowing
from the atmospheric end or entrance of the capillary to the vacuum end or exit of
the capillary. The high potential on the capillary entrance is there to promote the ESI
process. The capillary exit needs to be at a lower potential to gently push the ions out
as they exit the capillary without fragmenting them. The potential difference
between the capillary exit and skimmer 1 pushes the ions in the same direction of the
gas flow. If this potential difference is increased, the ions can be pushed out faster
than the gas flow. As a result, energetic collisions between ions and background gas
occur, assisting in desolvation. If the capillary exit voltage is too high, then the
collisions are more energetic and fragmentation occurs. The source design is further
optimized by two closely coupled stages of differentially pumped skimmers. The
values of the voltages chosen for the skimmers are decisive in focusing complex ions
and repelling small-molecule ions (solvents) in the ion beam. It was known that the
higher the m/z complex ion value, the bigger skimmer 1 and the smaller skimmer 2
voltages should be.25
57
Chapter three
Figure 3.2
A schematic of Apollo ESI-MS ion source and typical potentials for
each portion of measurement in atmospheric pressure and in vacuum (Bruker
manual)
Based on previous studies on electrospray ionization process,26 independent
variables that impact the degree of collisional activation include the flow rate and
temperature of the countercurrent drying gas, desolvation capillary temperature,
capillary - skimmer potential difference, droplet size, and pressure in the region of
the supersonic expansion beyond the desolvation capillary.
However, it was
suggested in the study by Griffrey et al27 that the capillary - skimmer potential
difference has the main effect in protein complex preservation. In an ESI source with
an unheated desolvation capillary and a 165V capillary exit – skimmer potential
leads to complete desolvation of a 27-nucleotide RNA model of the 16S rRNA Asite. A decrease in this potential to 115V generates an ammonium adducted complex
ion. Another study showed the effect of temperature of a heated metal capillary
interface on the mass spectra.26 At a capillary temperature of 100 oC, ions for the
streptavidin homotetramer complex are poorly desolvated. Increasing the
temperature to 200 oC improved the desolvation process. However, the noncovalent
complex is extremely fragile in the gas phase state. Excess heat or high collision
energy in the atmospheric pressure or vacuum interface can dissociate complexes.2830
A few studies have suggested that weak complex signals are due to high
58
Chapter three
collisional activation that occurs along the path from the atmospheric region to the
high vacuum region. This effect is controlled primarily by the capillary exit voltage.
Therefore in this step, an experiment was performed to study the effect of the
capillary exit voltage on the complex signal. This experiment was conducted on the
approach of one–factor-at-a-time; it was not intended to fully investigate the effect
of the capillary exit voltage or to find the optimum value. The experiment was
planned to narrow the experimental region for this factor to a region where the
complexes are not dissociated due to excessively high voltage.
The value range of the capillary exit voltage was chosen in the range of 70 V
to 160 V. Noncovalent complexes formed by bCA II and its specific inhibitor were
observed when the capillary exit voltage values were from 70 V to 140 V. At values
of 150 and 160 V, the complex signals disappeared (Figure 3.3). Response signals
had highest intensity when the capillary exit voltage was held at 100 V. Raising it
above 100 V resulted in significant amounts of dissociation of the gas phase
complex (Figure 3.3); lowering it under 100 V resulted in significant loss of signal to
noise ratio due to incomplete desolvation (Figure 3.4). Figure 3.5 shows the relation
between the complex intensity and the capillary exit voltage. Under the instrument
setting, the higher the capillary exit voltage the lower the complex signals. The
complexes were preserved best at a voltage from 100 to 140 V.
Hence, for optimization steps, all of the above 9 parameters (flow rate,
nebulizing gas pressure, dry gas flow rate, temperature, end plate voltage, capillary
voltage, capillary exit, skimmer 1, skimmer 2)
known to be involved in the
ionization process are chosen for step 3. Moderate values for these parameters will
be used to construct three-level FFD to avoid protein complex dissociation. Based on
the results of this experiment, the parameter values used in this step are chosen as
medium level (level 0) for the next experiments. High and low level values are
selected on both sides of the medium level values. Values of capillary exit voltage
will be in the region of 100- 140 V (Table 3.2).
59
Chapter three
Figure 3.3
Mass spectra of the mixture of bCA II with ethoxzolamide under
capillary exit voltages 100, 110, 120, 130, 140, 150, 160V. *bCA II-ethoxzolamide
complex is dissociated under high capillary exit voltage
Figure 3.4
Mass spectra of the mixture of bCA II with ethoxzolamide under
capillary exit voltages 100, 90, 80, 70V.
The relative intensity of *bCA II-
ethoxzolamide complex was higher with capexit smaller than 100V, but the overall
spectra are poorer in sensitivity due to the sub-optimal desolvation of the sample
60
Relative intensity of
BCAII-Ethoxyzolamide
complex
Chapter three
0.75
0.50
0.25
0.00
90
100
110
120
130
140
150
160
170
Capillary exit voltage [Volt]
Figure 3.5
Effect of capillary exit voltage to the complex
Table 3.2
Parameter levels for FFD
Parameters
Low level (-1)
Medium level (0)
High level (+1)
Flow rate
1 μl/min
2 μl/min
3 μl/min
Nebulizing gas pressure
40 psi
50 psi
60 psi
Dry gas
20 L/min
30 L/min
50 L/min
Temperature
100 oC
125 oC
150 oC
End plate voltage
-4000 V
-3600 V
-3200 V
Capillary voltage
-4800 V
-4500 V
-4200 V
Capillary exit voltage
100 V
120 V
140 V
Skimmer 1
15 V
20 V
25 V
Skimmer 2
5V
8V
12 V
3.3.3
Step 3: Interaction between instrumental factors
In order to investigate the interaction between these nine factors, a fractional
factorial design was planned. The design (27x9) used in this section has been
proposed by Xu et al.13 It is based on its high eligibility and efficiency with a view
of interaction projection as the primary task. The experiment consisted of 27 runs
and 9 factors, represented as a 27x9 matrix, where each row corresponds to a run or
a treatment of combination of factors and each column a factor. They are three-level
FF designs as each column takes on 3 different values: low, medium and high. Three
levels were chosen, in the ranges, for flow rate from 1 μL/min to 3 μL/min,
nebulizing gas pressure from 40 psi to 60 psi, drying gas flow from 20 L/min to 50
61
Chapter three
L/min, drying gas temperature from 100°C to 150°C, capillary voltage from -4200 V
to -4800 V, end plate voltage from -3200 V to -4000 V, capillary exit voltage from
100 V to 140 V, skimmer 1 from 15 V to 25 V and skimmer 2 from 5 V to 12 V.
Results of this experiment are shown in Table 3.3. Intensity of complex signals
varied from 40,000 to 424,950 units.
Table 3.3
Results of FFD for factor interactions
Run
flow neb
gas
temp
end
capll
capexit
skim1 skim2 Intensity
1
1
40
50
150
-3600
-4800
140
20
8
286400
2
1
50
50
125
-3200
-4500
120
15
12
228860
3
1
60
20
150
-3200
-4800
100
25
12
129640
4
1
40
30
125
-4000
-4200
100
25
12
180000
5
1
50
30
100
-4000
-4500
140
15
8
396910
6
1
60
30
100
-3200
-4200
120
20
8
235980
7
1
40
20
100
-3600
-4800
120
15
5
230570
8
1
50
20
125
-3600
-4200
140
25
5
208160
9
1
60
50
150
-4000
-4500
100
20
5
340210
10
2
40
30
150
-4000
-4500
120
25
5
366370
11
2
50
20
150
-3600
-4500
120
20
12
195000
12
2
60
20
150
-4000
-4200
140
15
8
50000
13
2
40
50
125
-3200
-4200
140
20
5
380110
14
2
50
50
100
-4000
-4800
140
25
12
424950
15
2
60
50
100
-3600
-4200
100
15
12
195000
16
2
40
20
125
-3200
-4500
100
15
8
60000
17
2
50
30
100
-3200
-4800
100
20
5
300000
18
2
60
30
125
-3600
-4800
120
25
8
150000
19
3
40
20
100
-4000
-4200
120
20
12
100000
20
3
50
50
150
-3200
-4200
120
25
8
200000
21
3
60
50
125
-4000
-4800
120
15
5
250000
22
3
40
30
150
-3200
-4800
140
15
12
230000
23
3
50
20
125
-4000
-4800
100
20
8
40000
24
3
60
30
125
-3600
-4500
140
20
12
150000
25
3
40
50
100
-3600
-4500
100
25
8
220000
26
3
50
30
150
-3600
-4200
100
15
5
130000
27
3
60
20
100
-3200
-4500
140
25
5
90000
62
Chapter three
3.3.3.1 Main Factors
A graph was constructed on the data results to identify the main factors. A
mean was calculated for the 9 sets of runs exposed to high flow rate, for the 9 sets of
runs exposed to the medium level of flow rate, and for the 9 sets of runs exposed to
the low flow rate. These three mean values were plotted on a graph and connected
with a line. Next, a mean was calculated for each set of runs exposed to high,
medium and low levels of nebulizing gas pressure. These three means were plotted
next to the flow rate variable means. This procedure was continued for all the factors
included in this design. This graphing technique allowed the effects of each variable
to be compared with the effects of all other variables in a single graph. Using this
analysis, a steep slope of one line is an indicator that the parameter has a large effect.
Figure 3.6 shows the graph obtained and Table 3.4 shows the slopes of these lines
using linear regression. The slope calculation and graphing were performed using
Excel statistical analysis.
The graph and slopes calculated for each parameter reveal that the most
influential instrument parameters were flow rate (slope= -45,929) and drying gas
(slope= 79,009). Other factors such as nebulizing gas pressure, temperature, end
plate voltage, capillary voltage, capillary exit and skimmer 2 voltages were also
influential to the response but to a smaller extent. Skimmer 1 voltage showed the
least effect (slope= 10,988).
Table 3.4
Factors
Slope
Effects of factors on the MS response
Flow
Neb.
Dry
rate
Press.
gas
-45929
-25701
79009
Temp.
-14766
Endplate
-16325
63
Capll
-20128
Capll
Skim
exit
1
34538
10988
Skim 2
-25665
Chapter three
Effects of ESI-MS Factors
300000
Flow
Avg. MS response
280000
260000
Neb
240000
Drying gas
220000
Temp
200000
End
180000
Capll
160000
Capexit
140000
Skim1
120000
Skim2
100000
level
level
level
level
level
level
level
level
level
level
level
level
level
level
(-1)
(+1)
(0)
(-1)
(+1)
(0)
(-1)
(+1)
(0)
(-1)
(+1)
(0)
(-1)
(+1)
Factor Levels
Figure 3.6
Main effects plot for each parameter
Another analysis method to identify main factors in FFD is constructing a
correlation of each factor with the response is used to determine a relationship
between each factor with the MS response. Pearson product moment correlation
coefficients between these parameters with MS response were calculated using
Analysis Toolpak in Microsoft Excel (Figure 3.7). This analysis tool and its formulas
measure the relationship between two data sets that are scaled to be independent of
the unit of measurement (i.e. flow rate vs. response, drying gas vs. response…). The
population correlation calculation returns the covariance of two data sets divided by
the product of their standard deviations. The resulting correlation graph shows
whether the parameter has a positive or negative or unrelated (zero) correlation with
the MS response. Figure 3.7 shows that drying gas, capillary exit voltage and
skimmer 1 had positive correlations with the detection of the protein complexes; the
high values of these parameters would increase protein complex signals. On the
other hand, flow rate, nebulizing gas pressure, temperature, end plate voltage,
capillary voltage and skimmer 2 gave negative correlations. It is important to note
that under the chosen conditions the interactions between flow rate, dry gas flow and
nebulizing gas pressure were found significant, confirming that droplet size, solvent
amount, and evaporation method are critical in the desolvation process.
64
Chapter three
Relationship of MS Response and Factors
0.8
0.4
0.2
Intensity
1
it
2
Sk
im
Sk
im
-0.4
ca
pe
x
ca
pl
l
en
d
p
te
m
dr
y
-0.2
ne
b
0
f lo
w
Correlation
0.6
-0.6
Factors
Figure 3.7
Pearson product moment correlation coefficients
3.3.3.2 Parameter Interactions
An interaction graph of one factor versus the other factor was constructed
based on the average response observed for the two factors when they were at a
combination of two levels (+1) and (-1). The first point of the graph is the mean
intensity measured when both parameters are at levels +1. The second point is the
mean intensity when the first factor is at level (+1) and the second factor at level (1). The third point is when the factor value levels are in the order of (-1, +1), and the
fourth point is the intensity for the two factors at (-1, -1) levels. Steeply sloped lines
connecting these points indicate important interactions between two parameters.
(1) Flow rate
Figure 3.8 clearly shows that signal intensity had a high response when flow
rate was at 1 μL/min (level (-1)). At 3 μL/min, mean intensity was low, regardless of
other factors whether they are at their minimum or maximum levels. At high flow
rate, the amount of solvent needed to be evaporated was significantly large so that
none of the conditions could provide suitable energy for the desolvation. As the flow
rate was as low as 1 μL/min (level -1), the drying gas and the capillary exit values
still had to be at their highest levels (50 L/min and 140 V, respectively) to be able to
deliver a good response. At low flow rate level (-1), temperature, skimmer 1 and 2
values were preferably at low level. This is almost certainly due to the fact that at
low flow rate, the amount of ions getting into the capillary was not dense, the
65
Chapter three
cooling effect due to evaporation was less important, the temperature required for
this process is not important. When the concentration of ions was not high, the
aggregation or clustering of ions in the capillary was not vital; skimmer 1 and 2
values therefore were low.
Interaction of flow rate with other parameters
Mean intensity
350000
300000
flow-neb
250000
flow-dry
200000
flow-temp
150000
flow-end
100000
flow-capll
flow-capexit
50000
flow-skim1
0
(+1,+1)
(+1, -1)
(-1, +1)
(-1, -1)
flow-skim2
Levels
.
Figure 3.8
Interaction of flow rate on other parameters
(2) Nebulizing gas pressure:
The nebulizing gas in combination with applied high pressure was utilised to
assist droplet generation and solvent evaporation. In Figure 3.9, complex ions were
observed at low intensity when nebulizing gas pressure and the other factors at high
level (+1, +1). At high gas pressure value, small droplets might be sprayed out to the
chamber at high speed and out of the working space of heated drying gas where
desolvation can occur. This result showed that there was a loss of droplets at 60 psi
and also revealed that limited exposure of droplets to nitrogen gas was detrimental.
At high gas pressure, the migration time of remaining droplets from needle to end
plate was shortened, leading to the short exposure of droplets to nebulizing gas. The
desolvation carried out by the nebulizing gas was therefore not efficient. To
compensate for this short exposure, more gas should be applied and flow rate should
be a at low level. High mean responses at point (+1, +1) for nebulizing gas pressure
and dry gas flow and at point (+ 1, -1) for gas pressure and flow rate have confirmed
the importance of the exposure of complex ions to drying gas, as expected. Better
66
Chapter three
MS response was observed for low gas pressure and high values for drying gas,
temperature and capillary exit (-1, +1). It is interesting to note that when the gas
pressure was low, complex ions were intense at low skimmer 2, high skimmer 1 and
high capillary exit. These parameters were the ones that control the collisional
energy in low pressure region. At the mentioned values, ions received high energy
which facilitated the already slow solvent evaporation caused by limited exposure to
drying gas. The final step of desolvation inside the capillary and at skimmers 1 and 2
was then important in this case.
Mean intensity
Interaction of nebuliser pressure with other
parameters
350000
300000
250000
200000
150000
100000
50000
0
neb-dry
neb-temp
neb-end
neb-capll
neb-capexit
neb-skim1
neb-skim2
(+1,+1) (+1, -1)
(-1, +1) (-1, -1)
neb-flow
Levels
Figure 3.9
Interaction of nebulizer pressure with other parameters
67
Chapter three
(3) Drying gas flow
Figure 3.10 shows two distinct areas for the behaviour of drying gas flow at
low and high levels in atmospheric pressure region. The drying gas in ESI was used
to accelerate buffer desolvation, to increase sensitivity, and to avoid the entry of
undesirable ions into the MS. Drying gas with high value caused a better desolvation
in the atmospheric region. The experimental results indicated that the high drying
gas flow was the most important factor for buffer desolvation. All experiments with
the minimum level of drying gas flow showed very low MS responses. Accordingly,
all experiments with the maximum level of drying gas showed very high signals.
Mean intensity
Interaction of drying gas flow with other parameters
400000
350000
300000
250000
200000
150000
100000
50000
0
dry-temp
dry-end
dry-capll
dry-capexit
dry-skim1
dry-skim2
dry-flow
(+1,+1) (+1, -1)
(-1, +1) (-1, -1)
dry-neb
Levels
Figure 3.10
Interaction of drying gas with other parameters
(4) Drying gas temperature
Within the range of drying gas temperature from 100 oC to 150 oC, there was
no clear effect of the high or low levels on MS response (Figure 3.11). Low values
of flow rate, nebulizing gas pressure, end plate voltage, capillary voltage, skimmer 2
voltage were the preferred settings for both low and high gas temperature values.
This observation demonstrated that at chosen values temperature was not a major
factor in the desolvation, although it showed strong interactions with other
parameters.
68
Chapter three
Mean intensity
Interaction of gas temperature with other
parameters
350000
300000
temp-end
250000
temp-capll
200000
150000
100000
temp-capexit
temp-skim1
temp-skim2
50000
0
temp-flow
temp-neb
(+1,+1) (+1, -1)
(-1, +1) (-1, -1)
temp-dry
Levels
Figure 3.11
Interaction of gas temperature with other parameters
(5) End plate voltage:
The steep decrease in MS response in the interaction curve between end plate
voltage and dry gas flow at both high and low levels for this voltage factor was not
unexpected since drying gas was identified as a main effect of this experiment
(Figure 3.12). Decrease in response was observed when the end plate voltage was at
low level (-1) and capillary is at high level (+1). In other words, a low potential (200
V) between these two voltages was detrimental for MS response. At this low
potential difference between end plate and capillary, ion pulling into the vacuum
system was not efficient. The loss of ions led to weak complex signals. A low level
(-1) of end plate voltage was generally preferred.
69
Chapter three
Mean intensity
Interaction of end plate voltage with other
parameters
400000
350000
300000
250000
200000
150000
100000
50000
0
end-capll
end-capexit
end-skim1
end-skim2
end-flow
end-neb
(+1,+1) (+1, -1)
(-1, +1) (-1, -1)
end-dry
end-temp
Levels
Figure 3.12
Interaction of end plate voltage with other parameters
(6) Capillary voltage:
Figure 3.13 shows that the low level (-1) of capillary voltage gave a high
intensity signal. It was not surprising because at level (-1) the potentials created
between end plate and capillary tip and between capillary tip and capillary exit were
high. Due to these high potentials, better collision activation for complex ions was
created and the last step of solvent evaporation was, thus, more easily achieved.
Mean intensity
Interaction of capillary voltage with other
parameters
350000
300000
250000
200000
capll-capexit
capll-skim1
capll-skim2
150000
100000
50000
0
capll-flow
capll-neb
capll-dry
capll-temp
(+1,+1) (+1, -1)
(-1, +1) (-1, -1)
capll-end
Levels
Figure 3.13
Interaction of capillary voltage with other parameters
70
Chapter three
(7) Capillary exit voltage:
Figure 3.14 shows two clear areas for the behaviour of capillary exit at low
and high levels. High level of capillary exit voltage always gave high MS response.
This analysis agreed with the correlation analysis, which showed that this factor is an
important parameter in the low pressure of the ion source. The high setting of
capillary exit voltage was found in this experiment to be optimal, which also agrees
with observations for pesticides in water by Crescenzi et al.,31 and for synthetic
polymers by Hunt et al.32 In Hunt’s work, shifts in the relative intensities of
oligomer ions are found to accompany changes in cone potential or capillary exit
voltage in the ESI source. The effects of capillary exit voltage have been modeled
mathematically, from which it is concluded that capillary exit voltages exert a
focusing effect dependent on the m/z of ions. To the authors, this focusing effect
determines the dependence of oligomer ion intensities upon capillary exit voltage in
the ESI mass spectra of polymers.
Mean intensity
Interaction of capillary exit voltage with other
parameters
400000
350000
300000
250000
200000
150000
100000
50000
0
capexit-skim1
capexit-skim2
capexit-flow
capexit-neb
capexit-dry
capexit-temp
capexit-end
(+1,+1) (+1, -1)
(-1, +1) (-1, -1)
capexit-capll
Levels
Figure 3.14
Interaction of capillary exit voltage with other parameters
(8) Skimmer 1 and skimmer 2
At high capillary exit voltage, the complex ions have high internal energy.
When they leave the capillary exit to enter the skimmer 1-skimmer 2 zone, they
receive a kinetic energy caused by the potential difference between skimmer 1 and
skimmer 2. If the setting of skimmer 1 and skimmer 2 is (+1, -1), the high potential
71
Chapter three
difference will provide a large kinetic energy that might exceed the dissociation
threshold of the already high energy complex ions. As a result, small MS response
for the complex ions was observed. On the contrary, if the setting of skimmer 1 and
skimmer 2 is (+1,+1), the low potential difference, as in the experimental values,
was not detrimental to the complex ions.
Interaction of skim 1 with other parameters
Mean intensity
350000
300000
skim1-flow
250000
skim1-neb
200000
skim1-dry
150000
skim1-temp
100000
skim1-end
50000
skim1-capll
0
skim1-cape
(+1,+1) (+1, -1)
(-1, +1) (-1, -1)
skim1-2
Levels
Figure 3.15
Interaction of skimmer 1 with other parameters
Interaction of skim 2 with other parameters
Mean intensity
350000
300000
skim2-flow
250000
skim2-neb
200000
skim2-dry
150000
skim2-temp
100000
skim2-end
50000
skim2-capll
0
skim2-cape
(+1,+1) (+1, -1)
(-1, +1) (-1, -1)
Levels
Figure 3.16
Interaction of skimmer 2 with other parameters
72
skim2-skim1
Chapter three
3.3.4
Step 4: Fractional Factorial Design for Optimum Condition
When there is little or no information on the relative sizes of the effects, it is
common to choose a minimum aberration design because it has good overall
properties. The minimum aberration criterion,33 an extension of the maximum
resolution criterion,34 has been used explicitly or implicitly in the construction of
design tables in National Bureau of Standards.35 This study used a three-level
fractional design with 27 runs calculated by Xu13 with a minimum aberration
criterion. A new 27 run fractional factorial design was setup. According to the results
in step 3, all nine factors have contributions to the MS response of protein complex
of bCA II and ethoxzolamide. Thus, three levels of the nine factors were chosen for
the new FFD with the same value ranges as in step 3. Results for this FFD showed
that the intensity of the complex signal varied from 0 to 575,000 units with run 14
having the maximum absolute intensity of complex and therefore was selected as the
optimum tuning condition (Table 3.5).
It was confirmed in this experiment that the drying gas, which is used to
support the desolvation process, has a great impact on the intensity of the complex.
An increase of drying gas flow rate tended to increase the intensity of the complex.
The average intensity of the complex for drying gas at 20, 30 and 50 L/min in 27
experiments was 151,111, 254,444, and 341,666, respectively. The capillary exit
voltage was also found to be an important factor. It influenced the kinetic energy of
the complex ions during their transfer to the gas phase. The average intensity of the
complex for capillary exit at 100, 120 and 140 V in 27 experiments are 142,777,
246,111 and 358,333, respectively. Maintaining capillary exit voltage at 100 V while
changing other factors reduced the complex signal intensity from 260,000 to
230,000, 225,000, 160,000, 125,000, 120,000, 105,000, 60,000 and to 0
(experiments 15, 12, 18, 20, 23, 26, 7, 1, 4).
The optimal condition of parameters for the detection of carbonic anhydrase
complex is found to be in run 14 (flow rate: 2 μL/min, nebulizing gas pressure: 50
psi, drying gas flow rate: 30 L/min, drying gas temperature: 100 oC, end plate
voltage -3200 V, capillary voltage: -4500 V, capillary exit voltage 140 V, skimmer
1: 15 V, skimmer 2: 12V)
73
Chapter three
Table 3.5
Fractional Factorial Design (FFD) experiment for optimum condition
Run
flow
neb
dry
temp
end
capll
capexit
Skim1
Skim2
Int.
1
1
40
20
100
3200
4200
100
15
5
60000
2
1
40
30
125
3200
4800
120
25
12
210000
3
1
40
50
150
3200
4500
140
20
8
290000
4
1
50
20
125
4000
4500
100
20
12
0
5
1
50
30
150
4000
4200
120
15
8
100000
6
1
50
50
100
4000
4800
140
25
5
270000
7
1
60
20
150
3600
4800
100
25
8
105000
8
1
60
30
100
3600
4500
120
20
5
300000
9
1
60
50
125
3600
4200
140
15
12
520000
10
2
40
20
125
3600
4500
120
15
8
145000
11
2
40
30
150
3600
4200
140
25
5
350000
12
2
40
50
100
3600
4800
100
20
12
230000
13
2
50
20
150
3200
4800
120
20
5
180000
14
2
50
30
100
3200
4500
140
15
12
575000
15
2
50
50
125
3200
4200
100
25
8
260000
16
2
60
20
100
4000
4200
120
25
12
0
17
2
60
30
125
4000
4800
140
20
8
350000
18
2
60
50
150
4000
4500
100
15
5
225000
19
3
40
20
150
4000
4800
140
15
12
190000
20
3
40
30
100
4000
4500
100
25
8
160000
21
3
40
50
125
4000
4200
120
20
5
270000
22
3
50
20
100
3600
4200
140
20
8
340000
23
3
50
30
125
3600
4800
100
15
5
125000
24
3
50
50
150
3600
4500
120
25
12
460000
25
3
60
20
125
3200
4500
140
25
5
340000
26
3
60
30
150
3200
4200
100
20
12
120000
27
3
60
50
100
3200
4800
120
15
8
550000
74
Chapter three
3.4
SUMMARY
In this chapter, a procedure to achieve the optimal ESI-MS condition for
detecting bCA II - small molecule complex has been successfully developed using
fractional factorial design (FFD) approach. In particular, FDD has been used in
experiments designed to investigate the key instrumental factors controlling the
desolvation process, as well as the interactions between these factors. It has been
found that flow rate, nebulizer gas pressure and drying gas flow are factors that
greatly affect the sensitivity of the complex detection. Capillary exit voltage also has
a great effect on the desolvation in vacuum and on the preservation of the complex.
These factors have been found to interact with each other and contribute to the final
response.
Therefore, to achieve optimal ESI-MS conditions, the effects of all of these
factors and their interactions have to be considered. These factors are incorporated in
a second FDD which focuses on minimum moment aberration. It has been found that
the best condition is achieved when the capillary exit voltage is at the highest setting,
and the flow rate, drying gas flow rate and nebulizing gas are at medium settings.
The results show that FFD can be used successfully to develop an
optimization method for ESI-MS, where many parameters are considered at the same
time with a small number of experiments. The four-step optimization strategy
focusing on the 9 influential factors will be used throughout this thesis when
complexes other than bCA II are investigated.
3.4
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Murata H, Takao T, Shimonishi Y: Optimization of skimmer voltages of an electrospray ion
source coupled with a magnetic sector instrument. Rapid Commun. Mass Spectrom. FIELD
Full Journal Title:Rapid Communications in Mass Spectrometry 1994; 8: 205-210.
26.
Loo JA: Electrospray ionization mass spectrometry: a technology for studying noncovalent
macromolecular complexes. Int J Mass Spectrom 2000; 200: 175-186.
27.
Griffey RH, Sannes-Lowery KA, Drader JJ, Mohan V, Swayze EE, Hofstadler SA:
Characterization of low-affinity complexes between RNA and small molecules using
electrospray ionization mass spectrometry. J Am Chem Soc 2000; 122: 9933-9938.
28.
Loo RRO, Goodlett DR, Smith RD, Loo JA: Observation of a noncovalent ribonuclease Sprotein/S-peptide complex by electrospray ionization mass spectrometry. J Am Chem Soc
1993; 115: 4391-4392.
29.
Goodlett DR, Loo RRO, Loo JA, Wahl JH, Udseth HR, Smith RD: A study of the thermal
denaturation of ribonuclease S by electrospray ionization mass spectrometry. J Am Soc Mass
Spectrom 1994; 5: 614-622.
30.
Schmidt A, Karas M: The influence of electrostatic interactions on the detection of hemeglobin complexes in ESI-MS. J Am Soc Mass Spectrom 2001; 12: 1092-1098.
31.
Crescenzi C, Di Corcia A, Marchese S, Samperi R: Determination of acidic pesticides in
water by a benchtop electrospray liquid chromatography mass spectrometer. Anal Chem
1995; 67: 1968-1975.
32.
Hunt SM, Sheil MM, Belov M, Derrick PJ: Probing the effects of cone potential in the
electrospray ion source: Consequences for the determination of molecular weight
distributions of synthetic polymers. Anal. Chem 1998; 70: 1812-1822.
33.
Fries A, Hunter WG: Minimum aberration 2k-p designs. Technometrics 1980; 22: 601-608.
34.
Bob GEP, Hunter GS: The 2k-p fractional factorial designs. Technometrics 1961; 3: 311-351,
449-458.
77
Chapter three
35.
Standards NBo: Fractional factorial experiment designs for factors at two levels. In Applied
Mathematics Series 48. Washington DC, US Government Printing Office, 1957.
78
CHAPTER FOUR
FTICR-MS AS A DETECTOR FOR SMALL COMPLEX (<2000 DA) AND
LIGAND STRUCTURE RECOGNITION TOOL - A STUDY FOR
FRAGMENTATION PATTERNS OF ACTIVE LIGANDS IN THE BINDING
OF NATURAL PRODUCT EXTRACTS TO HEMIN
Abstract: This chapter presents a strategy for using FTICR-MS to detect known
compounds and recognize known structural classes in natural products in crude
extracts. A set of plant (25) and marine sponge (25) extracts were used for a study
with hemin. Owing to high resolution of FTICR-MS, the molecular formula can be
generated, and artemisinin in its crude extract was identified. Using trapping and
dissociation techniques, MS2 can be obtained to confirm artemisinin by its
fragmentation patterns and MS3 for assignment of chemical structural class of
flavones and flavonols. Mechanism pathways are proposed for the fragmentation of
the ions. An active flavone was isolated from the methanol extract of the plant
Artemisia argyi by mass directed purification (LC/MS) and its activity with hemin
was confirmed. Its structure was proposed by MS3 and confirmed by NMR. Another
two active compounds in two marine sponge extracts were also isolated based on
their molecular mass. Their structures were established by NMR. A MS2
fragmentation for the two marine compounds was performed and is a start for
establishing a recognition pattern of the cyclic peroxide structural class.
4.1
INTRODUCTION
This chapter investigates the application of MS techniques such as high
resolution MS and multistage MS to identify known inhibitors or a structural class of
compounds. These known compounds need to be identified early in the screening
step to avoid reinventing known drugs.
Hemin and artemisinin were used as a protein and ligand model. Hemin was
chosen because it contains no interfering factors such as unsuitable buffers or
nonvolatile salts. Thus, the investigation on the multistage MS technique and high
resolution will be the main focus. Hemin also has interesting therapeutic applications
and has molecular mass of less than 1,000 Da. It is also in the plan of the thesis to
79
Chapter four
include a wide range of protein/target molecular masses. A strategy for this study is
proposed as below:
Scheme 4.1
Strategy for early detection of known drugs or known structural class
of active compounds
4.1.1
Natural products as a source of antimalarial drugs
Most antimalarial drugs have come from natural sources.1,2 The first natural
product antimalarial agent was quinine (10). It is an alkaloid extracted from the bark
of the South American Cinchona tree. It was first used to treat malaria in Rome in
1631. Later, different derivatives of quinine were synthesized and used in the
treatment of malaria. The second natural product antimalarial agent is artemisinin
(17), extracted from the leaves of Artemisia annua. Artemisia has been used by
Chinese herbalists for more than a thousand years in the treatment of many illnesses,
such as skin diseases and malaria. In 1972 artemisinin was identified as the active
constituent, and is now the most efficient drug to treat multi-drug resistant strains of
falciparum malaria. Other natural products that are active in strains of falciparum
malaria
include
flavonoids
(18),3-5
80
neolignan
(19),6
phenylacetylene,
Chapter four
phenylheptatriyne (20),7 terpene isonitriles (21-24),8 cyclic peroxide (25).9 Taking
into account that the isolation of lead compounds is very time-consuming for active
natural product extracts, the efficient and early identification of previously isolated
compounds is essential.
OMe
O
O
O
O
O
H
H
N
N
X
H
O
X = H, Flavone
X = OH, Flavonol
O
H
OH
Quinine (10)
Artemisinin (17)
MeO
(18)
OMe
OMe
H
OMe
O
OH
OMe
polysyphorin (19)
(20)
H
H
H
i-Pr
N+
C-
H
CN
H
H
H
H
H
(21)
H
H
NC
(22)
81
H
NC
(23)
Chapter four
NCS
H
H
H
H
O
H
O
NC
(24)
4.1.2
OMe
O
Cyclic peroxide (25)
MS as a detector of complexes formed with hemin in a search for
antimalarial drugs
Malaria is an infection caused by Plasmodium falciparum parasites and
transmitted to human beings by the bite of infected female mosquitoes, Anopheles
spp. According to an estimation of the World Health Organization (Fact sheet No94,
May 2007), this disease infects between three and five hundred million people and
causes around one to three million deaths annually. South and Central America,
South and East Asia, the Caribbean, Oceania, Central Asia and the Middle East are
all affected by malaria, with Africa being the most affected region. Ninety percent of
all malaria deaths occur in tropical Africa, mostly children under five. Despite
efforts in reducing transmission using mosquito nets and increasing medical
treatment, malaria is still a major global health problem, with the death rate of one
child every thirty seconds in Africa. It is estimated that the death rate may double in
the next twenty years. Thus, the need for malaria vaccines, non-resistant drugs, and
effective control methods is urgent.10
To achieve new drugs which are highly adaptive to the character of the
malaria parasite, a quick, reliable and effective screening assay is required. Various
target locations and their associated pathways or mechanisms have been investigated
for antimalarial assays such as cytosol with folate metabolism,11 parasite membrane
with phospolipid synthesis,12 mitochondria with electron transport,13 apicoplast with
fatty acid synthesis,14 and food vacuole with heme polymerization.15
Since 1981, after a publication in Science on the study of the chloroquinehemin complex on malaria parasites,16 hemin has attracted a large number of
investigations concerning its mechanism with chloroquine and artemisinin. Hemin
appears to be the site of action of a number of existing antimalarial drugs and thus
82
Chapter four
offers as a new screening target for malaria.17 Inside the red blood cells, the malarial
parasite must degrade the hemoglobin for the acquisition of essential amino acids,
which the parasite requires to construct its own protein and for energy metabolism.
This is essential for parasitic growth and division inside the red blood cell. This
process is carried out in the digestive vacuole of the parasite. During this process,
heme is released from hemoglobin into the food vacuole of the parasite. Heme is
very toxic to the parasite because it causes damage to its cell membranes.18 To avoid
being destroyed by this molecule, the parasite polymerizes heme to form hemozoin,
a non-toxic molecule. Hemozoin collects in the digestive vacuole as insoluble
crystals. The heme moiety consists of Fe(II)-protoporphyrin IX (FP). In the process
of polymerizing heme, the parasite converts Fe(II) to Fe(III) which is hemin or ferric
protoporphyrin (26). Antimalarial agents bind to heme, inhibiting the polymerization
process. It may be possible to exploit this unique polymerization pathway as one of
the strategic targets in a screening program for antimalarial drugs. Hemin has a
cationic mass of 616.1772. A compound forming a complex with hemin can be
easily detected by MS. Antimalarial drugs interacting with heme have been studied
using ESI-MS as a detection method.19
The study by Pashynska and colleagues19,20 has demonstrated that stable
noncovalent complexes can be formed between Fe(III)-heme and antimalarial agents
(i.e. quinine, artemisinin, and the artemisinin derivatives). Differences in the binding
behavior of the examined drugs with Fe(III)-heme and the stability of the drug-heme
complexes are established by using collision-induced dissociation tandem mass
spectrometry (ESI-MS/CID/MS). The results show that all tested antimalarial agents
form a drug-heme complex with a 1:1 stoichiometry but that quinine also results in a
second complex with the heme dimer or β-hematin. ESI-MS experiments performed
on mixtures of the various antimalarial agents with heme indicate that quinine binds
preferentially to Fe(III)-heme, while ESI-MS/CID/MS shows that the quinine-heme
complex is more stable than the complexes formed between heme and artemisinin
and its derivatives. The study illustrates that electrospray ionization mass
spectrometry and collision-induced dissociation tandem mass spectrometry are
suitable tools to probe noncovalent interactions between heme and antimalarial
agents.
83
Chapter four
O
Me
Me
-
HO
O-
N-
N
+
Fe 3
N-
N
Me
O
Me
.2 H+
O-
Hemin (26)
4.1.3
Ligand structure recognition – A strategic approach to speed up the
identification of new drugs in natural products
In the course of detecting the complex formed between an active natural
product compound and heme, besides identifying the true active constituent of the
natural product extract, MS also offers valuable information such as accurate
molecular mass, empirical formula, and may allow detection of functional groups
and other substituents, determination of over-all skeleton and finally structure
elucidation.21-23
4.1.3.1 Accurate mass
Accurate mass information is essential for structural confirmation of a
compound. FTICR-MS offers the highest mass accuracy of any mass spectrometer.24
The ability to accurately measure an ion’s cyclotron frequency while it is trapped
inside the FTICR cell is governed by instrumental and experimental conditions such
as variations in magnetic field strength, trapping potentials, excitation variables and
ion populations.25-28 A large ion population can create ion space charge effects due to
Coulombic interactions between the ions themselves in the FTICR-MS cell, thus
shifting the cyclotron frequency, and leading to mass errors.25,29 Calibration
methods, external or internal, have been used to overcome the issue of deterioration
in mass accuracy due to space charge. Using external calibration protocols, mass
accuracy of better than 1 ppm mass error can be expected for a pure compound.30
However, this degree of mass accuracy is only achievable providing strict
experimental protocols are observed. Further improvement in mass accuracy can be
84
Chapter four
attained by using an internal mass calibration method.31 In this approach, space
charge effects, trapping, and detection factors are basically identical for all ions in
the cell. However, drawbacks have been encountered for analyzing a pre-mixed
solution of analyte and internal calibrant. There is a potential for preferential
ionization when different properties and/or concentrations of the analyte and the
internal calibrant are present in the pre-mixed solution32,33 It is always challenging to
achieve the required comparable signal intensity between pre-mixed internal
calibrants and analytes when dealing with biological samples especially with an
unknown composition and concentration. To overcome the limitation caused by
incorporation of an analyte and an internal calibrant in solution, a dual emitter for the
ESI source that allows simultaneous introduction of sample and internal calibrant
have been developed for infusion injection method.26 Two ESI emitters are
sequentially positioned in front of the heated metal capillary inlet of the ionization
source. The switching time between the analyte emitter and internal calibrant emitter
is smaller than 50 ms, which allows the analyte and internal calibrant to be
accumulated almost simultaneously in the hexapole and injected as a single ion
packet into the ICR cell. Ion abundances, for the analyte and internal standards are
matched by adjusting the hexapole accumulation times. The mass accuracy
measurement was greatly improved. Average mass errors were from 41 ppm down to
1.1 ppm for an oligonucleotide with theoretical mass of 4548.769 Da.
The use of dual ESI-source for internal calibration is necessary, particularly
when dealing with a complex mixture like natural product extracts, because
significant different solution concentrations of each compound and large ion
population are a real challenge in obtaining accurate mass measurements. The above
mentioned dynamic approach should require complex fabrication of the dual source
in comparison with the approach used in this thesis. A simpler, static source design
was therefore employed with two discrete sprayers where the calibrant and analyte
are introduced into the MS at the same time. This approach has proved to be very
robust, simple, and particularly very effective in LC-FTICR-MS.34 The calibrant ion
abundance can be independently adjusted by changing the flow rate. Furthermore the
sample preparation time is less since there is no need for mixing analytes with the
calibrants.
85
Chapter four
Figure 4.1
A dual nebulizer Apollo ESI-source
4.1.3.2 Multiple Stage MS
Multiple stage MS (MSn) has been used widely for elucidation of structure,
determination of fragmentation mechanism, and determination of elementary
composition. MSn is an additional requirement for ESI mode because this soft
ionization does not yield fragmentation. Structure elucidation using MS
fragmentation has been demonstrated for a few classes of compounds, such as
nodulation factors and flavonoids. When fragment ions correspond to features
known to a class of compounds, based on the known mass fragmentation pattern,
structure of the compound can be determined or confirmed.
MSn can only be performed on ion-trap and FTICR instruments. It uses
dissociation techniques to gain structural information about precursor ions and to
study pathways of fragmentation. In some structural classes these pathways form a
pattern. A normal MS2 experiment includes a step to isolate a precursor ion of
interest and a second step of excitation of the ion to yield product ions and neutral
fragments. The MS2 experiment ends here as the product ions are consumed by the
detector. In MSn, the product ions are trapped allowing another isolation and
fragmentation to be performed. It is possible to increase the number of steps by
selecting ions of the first fragmentation as a precursor for the next MS experiment.
The number of steps can be increased further to reach an MSn experiment where n is
the number of generations of ions being analyzed. The number of steps is dependent
86
Chapter four
on the intensity of precursor ions and on the physical dimensions of the instrument.
At least 3 stages can be performed on a 4.7 Tesla instrument,35 and at leat 5 on a 7.0
Tesla instrument.36
Although most MS instruments enable MS2 experiments in space, using a
first analyzer for the isolation of precursor ions and a second analyzer for detection
of product ions, FTICR-MS allows tandem MS in time by performing an appropriate
sequence of events in an ion storage device. Time-based instruments (ion-trap or
FTICR-MS) are known to have better sensitivity due to their capability of ions
preservation. Figure 4.2 demonstrates the difference of a product ion scan performed
by a space-based and a time-based instrument.
Figure 4.2
Comparison of a product ion scan performed by a space-based and a
time-based instrument
Ion activation is an important step in multiple MS and can be accomplished
by several means, such as collision with a gaseous or solid target, or absorption of
photons. In FTICR-MS, collision-induced dissociation (CID) with argon gas has
been traditionally used. For CID experiments in FTICR-MS, collisional energies are
in the range of 1-500 eV. Although dissociated by low collisional energies, the large
87
Chapter four
number of collisions in conjunction with the long time-scale between activation and
detection allows for relatively efficient fragmentation of precursor ions.37 However,
low-energy CID also has drawbacks. Ions are excited to orbital radii smaller than 5
mm, representing only about 20% of the available ion radius in a 2-inch cubic cell.
Such small cyclotron radii do not always allow sufficient spatial separation of the
excited ion cloud from the other ions in the cell. As a result of a high charge density
near the center of the cell, electric and magnetic shielding is formed. Consequently,
the excitation field is reduced, leading to shifts of the observed frequencies to lower
values during detection.38,39 This effect can be lessened by decreasing the number of
ions in the cell, but at the sacrifice of sensitivity of the experiment. CID is a pulsed,
on-resonance excitation of the parent ion concomitantly with a pressure burst of a
collision gas. This normally produces only single energetic collisions between the
parent ion and the collision gas, thus resulting in potentially low efficiencies for
parent to product ion conversion. Sustained off-resonance irradiation (SORI-CID) is
a modified method, which employs a lower energy, off-resonance RF pulse during a
high-pressure burst of gas. The effect is such that multiple collisions can occur
between the parent ion and the collision gas driving remaining parent ions to
fragmentation. The off-resonance method takes advantage of the fact that ion
excitation can also be achieved by the application of an off-resonance electric field
pulse with the irradiated frequency 500-2000 Hz away from the cyclotron frequency
of the precursor ion. As a consequence, ions undergo multiple accelerationdeceleration cycles with a period corresponding to the difference between the
irradiation frequency and their natural cyclotron frequency. Collisional energies are
less than 10 eV, and ions are allowed to undergo multiple collisions prior to
fragmentation, allowing the lowest energy fragmentation pathways to be observed.
Fragmentation efficiencies well over 90% were obtained for the SORI-CID of small
organic ions.37
4.2
4.2.1
Materials
Hemin chloride [Fe (III) protoporphyrin IX chloride (C34H32ClFeN4O4, MM
651.94615 Da, purity > 98 %, hemin C34H31FeN4O4, MM 616.1772 Da), NaI, CsI,
artemisinin (C15H22O5, MM 282.14672 Da), aspiginin, 7-hydroxyflavone, 5-
88
Chapter four
hydroxy-7-methoxyflavone, chrysin, 3,7-dihydroxyflavonol and fisetin were
purchased from Sigma Aldrich.
4.2.2
Sample preparation
Heme stock solution (10 mM) was prepared using hemin in MeOH (plus a
drop of NH4OH to solubilize heme). Artemisinin stock solution (10 mM) was
prepared in MeOH. Drug-heme mixtures with a molar concentration ratio 1:1
contained drug (100 μM) and heme (100 μM) in MeOH:H2O (3:1; v/v). In the case
of crude extract, 1μL of crude extract was dissolved in MeOH (100 μL) and was
incubated with heme (100 μM) in MeOH:H2O (3:1; v/v). The final pH of the drugheme mixture was 7.0, at which pH the iron atom in the heme molecule is known to
be in the Fe(III) state. The final mixture was subjected to ESI-FTICR-MS.
4.2.3
Mass Spectrometry
Mass spectral data was obtained in the positive ion mode on a Bruker Apex
III 4.7 Tesla, which was equipped with an ESI Apollo source (described in Chapter
2). Samples were directly infused by a Cole-Parmer syringe pump with a flow rate of
2 μL per minute. The end plate or counter electrode voltage was biased at 4000V and
the capillary voltage at 4400 V relative to the ESI needle. N2 gas was used as
nebulizing gas with a pressure of 40 psi and as counter-current drying N2 gas with a
flow of 20 L/min. The drying gas temperature was maintained at 125ºC. The
capillary exit voltage was tuned at 100 V. ESI mass spectra were recorded in the
mass range m/z 50-1500. SORI-CID was used for fragmentation in FTMSn
experiments. Data acquisition and processing were performed using Xmass software.
Parameters for MS2 were correlated sweep pulse length, 1000 μs; correlated
sweep attenuation, 21.4 dB; ejection safety belt, 0 Hz; user pulse length, 40000 μs;
ion activation pulse length, 250000 μs; ion activation attenuation, 42.0 dB;
frequency offset from activation mass, 500 Hz; user delay length, 7s.
Parameters for MS3 were correlated sweep pulse length, 600 μs; correlated
sweep attenuation, 42.5 dB; ejection safety belt, 0 Hz; user pulse length, 40000 μs;
ion activation pulse length, 250000 μs; ion activation attenuation, 42.0 dB;
frequency offset from activation mass, 500 Hz; user delay length, 7s.
89
Chapter four
Argon gas was pulsed into the cell with a peak pressure of 1 x 10-7 mbar. The
activation energy (attenuation) was adjusted to give nearly complete reduction of the
precursor ion signal.
4.2.4
Extraction and purification
Fifty plant and marine sponge biota (200 mg, Table 4.1 and 4.2) were
extracted exhaustively with methanol. The extracts were dried and re-dissolved in
methanol (8 mL). 1 μL of the extracts were used for screening.
The active extracts from the screening results were subjected to mass directed
purification. The chosen biota (5 mg) was extracted with methanol (300 mL). The
extract was evaporated and pre-absorbed onto C18 (~1 g) and packed dry into a
small cartridge, which was connected to a semi-preparative C18 column (Betasil
C18, 150 mm x 21.2 mm, 5μm, Thermo Electro Corporation). Pure compounds of
mass of interest were isolated using mass-directed purification on an online LC/MS
Agilent HP1100 LC/MSD. The extract was eluted at 10 mL/min with a gradient
solvent system starting with 100% water (1%TFA) gradient to 60% acetonitrile
(1%TFA)- 40 water (1 TFA) in 50 min, then a gradient to 100% actonitrile (1%TFA)
in the next 10 min. 2D NMR data was acquired using a cold probe attached to a
Varian INOVA 600 MHz NMR spectrometer. Pure compounds from this
purification step were tested again in the screening assay to confirm activity.
90
Chapter four
Table 4.1
List of plant biota
Sample ID
Family
Genus
Species
Source
1
QID014838
Asteraceae
Artemisia
anomala
China
2
QID022878
Asteraceae
Artemisia
scoparia
China
3
QID022889
Asteraceae
Artemisia
simulens
China
4
QID023012
Asteraceae
Artemisia
japonica
China
5
QID023018
Asteraceae
Artemisia
scoparia
China
6
QID023025
Asteraceae
Artemisia
simulens
China
7
QID023148
Asteraceae
Artemisia
simulens
China
8
QID023109
Asteraceae
Artemisia
japonica
China
9
QID023115
Asteraceae
Artemisia
japonica
China
10
QID024118
Asteraceae
Artemisia
sp.
China
11
QID024169
Asteraceae
Artemisia
sp.
China
12
QID024376
Asteraceae
Artemisia
roxburghiana bess
China
13
QID024309
Asteraceae
Artemisia
sp.
China
14
QID015360
Asteraceae
Artemisia
anomala
China
15
QID015361
Asteraceae
Artemisia
anomala
China
16
QID027056
Asteraceae
Artemisia
annua l.
China
17
QID027277
Asteraceae
Artemisia
lactiflora wall.
China
18
QID027280
Asteraceae
Artemisia
annua l.
China
19
QID015773
Asteraceae
Artemisia
argyi
China
20
QID015777
Asteraceae
Artemisia
argyi
China
21
QID027258
Asteraceae
Artemisia
annua l.
China
22
QID027261
Asteraceae
Artemisia
annua l.
China
23
QID100065
Asteraceae
Artemisia
annua
China
24
QID100066
Asteraceae
Artemisia
annua
China
25
QID101493
Asteraceae
Artemisia
frgida willd
China
Table 4.2
List of marine sponge biota
Sample ID
Order
Family
Genus
Species
1
QID5821894
Poecilosclerida
Podospongiidae
Diacarnus
levii
2
QID5821803
Poecilosclerida
Podospongiidae
Diacarnus
levii
3
QID6008053
Poecilosclerida
Cladorhizidae
Diacarnus
spinipoculum
4
QID6009558
Poecilosclerida
Podospongiidae
Diacarnus
3248
5
QID6009717
Poecilosclerida
Podospongiidae
Diacarnus
3248
6
QID016044
Poecilosclerida
Podospongiidae
Diacarnus
spinipoculum
7
QID019935
Poecilosclerida
Podospongiidae
Diacarnus
levii
8
QID027908
Poecilosclerida
Podospongiidae
Diacarnus
9
QID2174823
Poecilosclerida
Cladorhizidae
Diacarnus
levii
10
QID011577
Poecilosclerida
Podospongiidae
Diacarnus
spinipoculum
91
2663
Chapter four
11
QID012499
Poecilosclerida
Cladorhizidae
Diacarnus
spinipoculum
12
QID018285
Poecilosclerida
Podospongiidae
Diacarnus
2663
13
QID011571
Poecilosclerida
Podospongiidae
Diacarnus
spinipoculum
14
QID008062
Poecilosclerida
Podospongiidae
Diacarnus
levii
15
QID2165368
Poecilosclerida
Cladorhizidae
Diacarnus
levii
16
QID006867
Poecilosclerida
Cladorhizidae
Diacarnus
levii
17
QID020013
Poecilosclerida
Cladorhizidae
Diacarnus
spinipoculum
18
QID2280289
Poecilosclerida
Podospongiidae
Diacarnus
levii
19
QID5820459
Poecilosclerida
Podospongiidae
Diacarnus
levii
20
QID6004785
Poecilosclerida
Podospongiidae
Diacarnus
3248
21
QID6004766
Poecilosclerida
Cladorhizidae
Diacarnus
3247
22
QID6004807
Poecilosclerida
Podospongiidae
Diacarnus
3248
23
QID6004572
Poecilosclerida
Cladorhizidae
Diacarnus
2663
24
QID6011588
Poecilosclerida
Podospongiidae
Diacarnus
25
QID6013591
Poecilosclerida
Cladorhizidae
Diacarnus
sp.
3953
4.3
4.3.1
Identification of hemin and hemin-artemisinin complex
In
positive-ion
mode,
optimized
desolvation
conditions
(capillary
temperature 150 °C, capillary exit voltage 120 V) allow the detection of hemin and
intact hemin-ligand complexes. The intact protein complex was observed as a strong
ion signal in the mass spectra. The ESI mass spectrum obtained for the heminartemisinin complex is shown in Figure 4.3. The hemin-artemisinin noncovalent
complex (m/z 898.3236) was the most abundant ion in the spectrum. Free hemin was
also seen at m/z 616.1775 Da. Artemisinin molecular mass was calculated from the
spectra as 282.1461 which is only 0.0006 Da or 2 ppm error. This result confirms the
accuracy of the method and the instrument.
92
Chapter four
Figure 4.3
4.3.2
Hemin and its complex with artemisinin
Identification of active extracts via complexes formed with hemin
Screening 50 plant and marine sponge extracts with hemin resulted in four
active extracts from Table 4.1 (QID015773 and QID027261) and Table 4.2
(QID10644 and QID2280289). The extracts were reanalyzed for mass accuracy of
the complexes. To achieve the mass accuracy measurement using internal
calibration, a setup of dual ESI emitters was positioned in front of the heated metal
capillary inlet of the ionzation source in the FTICR-MS. Ion abundances, for the
analyte and internal calibrants were matched by adjusting the introduction flow rate
of the calibrants. This system was performed on those active extracts. Figures 4.4-7
show the complex signals for these crude extracts. Free hemin signals in these
samples were observed at values, which differ from 0.0001 Da to 0.0060 Da from
the calculated mass. Complex signals were observed at m/z 898.3226, 960.2627,
1022.4513 and 1022.4460. The molecular mass (MM) of active components was
calculated based on the difference between the m/z of the complex and hemin. They
are 282.1453 Da (QID027261), 344.09030 Da (QID015773), 406.2760 Da
(QID016044) and 406.2750 Da (QID2280289).
93
Chapter four
Figure 4.4
MS spectrum of QID027261 incubated with hemin, showing a
complex at m/z 898.3226
Figure 4.5
MS spectrum of QID015773 incubated with hemin, showing complex
at m/z 960.2027
94
Chapter four
Figure 4.6
MS spectrum of QID016044 incubated with hemin, showing complex
at m/z 1022.4855
Figure 4.7
MS spectrum of QID02280289 incubated with hemin showing
complex at m/z 1022.4841
95
Chapter four
Table 4.3 shows the MMs of compounds forming complexes with hemin.
Based on the information of MM and taxonomy of the biota containing these active
compounds, different approaches were carried out.
Table 4.3
Molecular mass of active compounds from natural product extracts
Biota
m/z complex
m/z hemin
MM compound
Approaches
QID027261
898.3226
616.1773
282.1453
Section 4.3.3
QID015773
960.2627
616.1724
344.09030
Section 4.3.4 &
4.3.5
QID10644
1022.4513
616.1753
406.2760
Section 4.3.6
QID2280289
1022.4460
616.1710
406.2750
Section 4.3.6
In QID027261, Artemisia annua, the active compound has a MM of
282.1453 which is only 0.0014 Da different from artemisinin, the antimalarial agent
isolated from the same plant species. Thus a FTICR-MS spectrum for artemisinin is
needed for a comparison. MS2 fragmentation patterns for artemisinin and the active
compound of QID027251 are also required to confirm the whether the compound is
artemisinin. This approach was performed and reported in 4.3.3.
In QID015773, the accurate mass of the active component does not direct to
a specific compound, but proposes a molecular formula suggesting the structural
class of flavonoids, which are also known antimalarial agents. MS2 and MS3 spectra
were obtained for known flavonoids and the active component in its crude extract for
comparision (Sections 4.3.4 and 4.3.5)
In QID10644 and QID2280289, the accurate mass of the active components
was used for mass-directed purification of the compounds. Activity of the
compounds was confirmed after purification. Structures of the compounds were
elucidated by NMR techniques. MS2 spectra of these compounds were performed as
a start for a mass fingerprint collection of their structural class (Section 4.3.6).
96
Chapter four
Figure 4.8
4.3.3
MS spectrum of complex formed by hemin-extract QID027261
Confirmation of artemisinin existence in crude extract by fragmentation
patterns
4.3.3.1 MS2 optimisation – artemisinin patterns
The active plant was Artemisia annua, and the active compound had a MM
of 282.1453 which was only 0.0014 Da different from the theoretical MM of
artemisinin. The plant was expected to contain artemisinin as the active contituent.
Thus, pure artemisinin was used to generate a MS2 fragmentation pattern and to
compare with the MS2 fragmentation of the active compound. The existence of
artemisinin in the active extract and its activity thus would be confirmed. Precursor
ion for artemisinin was obtained during infusion of acetonitrile solutions containing
the analyte into the FTICR-MS. Using the ESI Apollo source equipped with dual
emitters pumped with NaI/CsI as a reference calibrant in positive mode, the analyte
yielded predominantly sodium adduct ions at m/z 305.137485. The precursor ion was
subjected to collision-induced dissociation to determine the resulting product ions.
The product ion spectrum showed the fragmentation pattern at m/z 263.127604,
245.115913, 231.133766 and 209.154099 (Figure 4.8). Results showed the m/z
values of fragment ions were within a mass error of less than 5 ppm compared to
theoretical values (Table 4.4). Due to the NaI/CsI calibrant used, some fragment ions
97
Chapter four
had sodium adducts. The smallest fragment ion m/z 209 was protonated and showed
the loss of sodium adduct ion.
Figure 4.9
MS2 fragment ions for artemisinin in FTICR-MS
Table 4.4
Formula, observed mass, calculated mass, mass error (ppm) and
fragment scheme identity of fragment ions observed in the MS2 spectrum of the
sodiated artemisinin
Formula
Observed
Calculated
Error
Identity
mass
mass
(ppm)
C15H22O5Na+
305.137034
305.13594
3.56
[M+Na]+
C13H20O4Na+
263.127604
263.12538
0.69
[M+Na-C2H2O]+
C13H18O3Na+
245.115913
245.11482
4.4
[M+Na-C2H4O2]+
C13H20O2Na+
231.133766
231.13555
5.0
[M+Na-C2H2O2]+
C13H21O2+
209.154099
209.15361
2.0
[M+H-C2H2O2]+
4.3.3.2 Active compound for QID027261 – MS2 fragmentation –Confirmed
artemisinin
The hemin-active compound complex was observed as a singly charged ion
at m/z 898.3226, if it was used as a precursor ion for MS2 experiment, the pre-
98
Chapter four
charged hemin would keep the positive charge and be observed in the mass
spectrum. The active component, dissociated from the complex as a neutral species,
which could not be detected by ESI-MS and thus could not be used further as a
precursor ion for fragmentation pattern. Therefore in this study, the free active
component in the non-binding state was used as a precursor ion instead.
The active component with a molecular mass of 282.1453 Da as calculated in
Table 4.3, was observed as a sodium adduct at m/z 305.135622 in the condition of
the assay (Figure 4.10). This sodium adduct was used as a precursor for the MS2
fragmentation.
MS2 fragmentation of the active component in its assay solution (crude
extract and hemin) showed a fragmentation pattern at m/z 305.135434, 263.124670,
245.114800, 231.135233, 209.154160 (Figure 4.10 and Table 4.5). These
fragmentation species were the same as artemisinin fragment ions. Thus, the active
component was confirmed as artemisinin. Owing to the MS2 fragmentation pattern,
the active component was elucidated without any chromatography process.
Figure 4.10
MS2 fragment ions for active compound in QID027261
99
Chapter four
Table 4.5
Formula, observed mass, calculated mass, mass error (ppm) and
fragment scheme identity of fragment ions observed in the MS2 spectrum of the
active compound in extract QID027261.
Formula
Observed
Calculated
Error
mass
mass
(ppm)
C15H22O5Na+
305.135434
305.13594
1.65
[M+Na]+
C13H20O4Na+
263.124670
263.12538
2.69
[M+Na-C2H2O]+
C13H18O3Na+
245.114800
245.11482
0.08
[M+Na-C2H4O2]+
C13H20O2Na+
231.135233
231.13555
1.3
[M+Na-C2H2O2]+
C13H21O2+
209.154160
209.15361
2.6
[M+H-C2H2O2]+
4.3.4
Identity
Hemin - QID015773 complex
Methanol extract of Artemisia argyi biota (QID015773) displayed a complex
with hemin at m/z 960.262721. The accurate mass of the active constituent was
deduced as 344.090319 and proposed a molecular formula of C18H16O7 as the closest
possibility. A Dictionary of Natural Products search on this formula returned 146
hits, 74 of these belong to the flavonoid structural class. As the aim of this study is to
quickly identify known compounds or known structural class of compounds to help
prioritizing projects, a set of known flavonoids was used to generate diagnostic MS
fragmentation patterns (MS2 and MS3) for the structural class. MS2 fragmentation of
flavonoids has been studied by other MS techniques, however to the best of our
knowledge flavonoids have not been subjected to ESI-FTICR-MS and to MS3
fragmentation. It is expected there is a similarity in MS2 fragmentation patterns
between techniques if the same desolvation source is used (i.e. ESI). However, the
high resolution of FTICR-MS can confirm the fragment identity which is lacking in
other studies. Furthermore, it can provide more structural information in MS3
fragmentation. Flavones and flavonols are the two major groups for flavonoids and
were chosen for the study model set. These patterns were then used to characterize
the active compound in QID015773. To demonstrate the utility of these
fragmentation patterns, the active compound was purified and its structure was
elucidated by NMR techniques.
100
Chapter four
4.3.4.1 MS2 for flavones and flavonols – Background
FAB/MS/MS,40 EI/MS/MS, APCI/MS/MS41-43 have been employed for
structure determination of flavonoids. Collisional activation of [M+H]+ or [M+H]led to the sequential loss of moieties characteristic for flavones or flavonols.
Although different ion sources and activation techniques were used on these
compounds, there is an agreement in fragment ions and pathways for flavones and
flavonols. There are five common fragmentation pathways observed in the
dissociation of flavonoids (Figure 4.11). These fragmentations are normally labeled
with bond positions and rings involved such as i,jA+ or i,jB-. These symbols designate
primary product ions containing intact A or B ring in which the subscript i,j indicate
the C-ring bonds that have been broken. Characteristics fragments for flavonoids are
1,3
A+ and
0,2 +
0,2
A+, 0,2A+-CO, 1,3B+-2H and 1,3A+-C2H2O.
B . Characteristics for flavones are
0,4 +
B and
1,3 +
B , for flavonols are
H+
1,3 +
A
0,2 +
A
B
0
O
1
2
A
0,2 +
B
3
4
O
1,3 +
B
Figure 4.11
Fragmentation patterns of flavonoids
4.3.4.2 Analysis of flavone and its recognition patterns using FTICR-MS
(a)
MS2 for flavones by FTICR-MS
In this study, four hydroxy flavones namely apigenin (27), chrysin (28), 7hydroxyflavone (29), 5-hydroxy-7-methoxyflavone (30), with different substitution
of hydroxyl or methoxy groups were first investigated by full scan ESI-MS. The
protonated biomolecule ions [M+H]+ were observed. They were then isolated and
ESI-MS2 spectra were obtained (Figures 4.12-15). The fragmentation pathways
exhibit some common features for flavones and also show variations due to the
difference in substitution groups. The fragmentations such as 1,3A+, 1,3B+, 0,4B+-H2O,
[M-C3O2]+ were observed and summarized in Table 4.6. These common fragments
101
Chapter four
mostly are in agreement with previously reported observations in other MS
techniques. The only difference was the absence of the cleavage 0/2 of the C ring,
which was reported when high energy CID was used (30keV caesium ions).
OH
HO
O
OH
O
HO
O
Apigenin (27)
HO
O
OH
Chrysin (28)
O
O
O
OH
O
7-Hydroxyflavone (29)
O
5-Hydroxy-7-methoxyflavone (30)
The most useful fragmentations for flavone identification are those that
involve the cleavage of two C-C bonds at positions 1/3 and 0/4 of the C ring,
resulting in structurally informative
1,3
A+ and
0,4 +
B -H2O. This result is in agreement
with other results obtained using other ion sources. High resolution of FTICR-MS
allowed the assignment of the leaving neutral species. It was noticed the loss of 28
Da was observed for compounds 27, 29, and 30. Because both CO and C2H4 have an
average molecular mass of 28.0 Da, an accurate mass of this loss can confirm which
one was the leaving species. A difference between the compound m/z and the
fragment signal m/z was accurately calculated as 27.997052 Da, which is much
closer to the accurate mass of CO (27.994915 calculated mass, Δ = 0.002 Da) than
C2H2 (28.03130, Δ = 0.034 Da). Thus, it was confirmed that the leaving species is
CO. Similarly, other leaving fragments are calculated on the same basis.
102
Chapter four
Table 4.6
FT-MS2 product ions obtained from the [M+H]+ ions of compounds
27-30
M
Apigenin
Chrysin (28) 7-
(27)
5-Hydroxy-7-
Hydroxyflavo
methoxyflavon
ne (29)
e (30)
Calculated [M+H]+
271.0611
255.0652
239.0703
269.0808
[M+H]+
271.06095
255.065198
239.070278
269.080426
[1,3A+H]+
153.018248
153.018199
137.023302
167.034428
[1,4A++2H+H]+
-
-
-
-
+
119.051998
103.055366
103.055693
-
[0,4B+H]+
163.037005
-
-
-
[0,4B-H2O+H]+
145.028396
129.033509
129.033505
129.034923
[0,2B+H]+
-
-
-
-
[M-CO+H]+
243.060750
-
211.073853
226.062541*
183.080170
-
1,3
[ B+H]
[M-CO-CO+H]+
[M-CH2O2+H]+
225.053486
209.060250
-
209.059910*
[M-C2H2O+H]+
229.050832
213.062462
-
-
[M-C3O2+H]+
203.070245
187.076314
171.078895
-
[M-CH3+H+
-
-
-
254.059593
The loss of small neutral species from the protonated molecules is used to
identify the presence of specific functional groups. For example, the presence of a
methoxyl group in compound 30 can be easily detected by the loss of CH3 from the
protonated molecule resulting in the base peak at m/z 254. The experiments showed
that the fragmentation mechanism also related to the substitution site, and the
number of methoxyl groups and hydroxyl groups. A methoxy group in ring A would
change the intensity of the
1,3
A+ ion. This cleavage in compound 30 was not a
preference cleavage resulting in a low intensity of the ion when compared with
fragment ions 1,3A+ of compounds 27-29, where a hydroxyl group was a substitution
group instead of a methoxyl group. According to the MS2 patterns for the four
flavones, the diagnostic signals for flavones under ESI-FTICR-MS are suggested to
be at [1,3A+H]+, [1,3B+H]+, [0,4B-H2O+H]+, [M-CO+H]+, and [ M-CH2O2+H]+.
103
Chapter four
Figure 4.12
MS2 fragmentation of apigenin (27), using m/z 271 as the precursor
Figure 4.13
MS2 fragmentation of chrysin (28), using m/z 255 as the precursor
104
Chapter four
Figure 4.14
MS2 fragmentation of 7-hydroxyflavone (29), using m/z 239 as the
precursor
Figure 4.15
MS2 fragmentation of 5-hydroxy-7-methoxyflavone (30), using m/z
269 as the precursor
105
Chapter four
(b)
MS3 for flavones by FTICR-MS
MS3 fragmentation patterns for the four flavones are shown in Figures 4.1619 and Table 4.7. They all display the same loss of CO groups in tandem. MS3
experiments on
1,3
A+ gave detailed information on the substitution of ring A. A
fragment ion at m/z 67 were observed for compounds 27, 28, and 30 which share the
same substitution pattern of being oxygenated at position 5 and 7. A proposed
mechanism for these fragment ions is presented in Scheme 4.2. Diagnostic cleavage
for flavones in MS3 were found to be at [1,3A-CO+H]+, [1,3A-CO-CO+H]+.
Table 4.7
FTMS3 product ions obtained from the 1,3A+ ions of compounds 27-30
M
Apigenin
(precursor)
(27)
Chrysin (28) 7-
5-Hydroxy-7-
Hydroxyflavone
methoxyflavone
(29)
(30)
[1,3A+H]+
153.011519
153.017361
137.021453
167.035501
[1,3A-CO+H]+
125.018406
125.024410
109.029951
-
[1,3A-CO-
97.031118
97.029590
81.035392
67.017648
67.019291
-
CO+H]
+
[1,3A-CO-CO-
67.01901*
COH2+H]+
Figure 4.16
MS3 fragmentation of apigenin (27), using m/z 153 as the precursor
106
Chapter four
Figure 4.17
MS3 fragmentation of chrysin (28), using m/z 153 as the precursor
Figure 4.18
MS3 fragmentation of 7-hydroxyflavone (29), using m/z 137 as the
precursor
107
Chapter four
Figure 4.19
MS3 fragmentation of 5-hydroxy-7-methoxyflavone (30), using m/z
167 as the precursor
108
Chapter four
O
HO
C
O
HO
O
HO
C
C
O
O
O
OH
OH
OH
Exact Mass: 152.01041
O
HO
HO
HO
-CO
C
C
C
O
O
O
OH
OH
OH
-CO
H
HO
HO
HO
HO
HO
H
OH
OH
H
OH
HO
O
H
H
HO
H
HO
H
H
Scheme 4.2
Proposed mechanism for MS3 fragment ions of precursor ion
compounds 27-30.
4.3.4.3 Analysis of flavonol and its recognition patterns using FTICR-MS
OH
OH
HO
HO
O
O
OH
OH
O
O
3,7-Dihydroxyflavonol (31)
Fisetin (32)
109
1,3
A+ of
Chapter four
The MS2 spectra of [M+H]+ ions of flavonols 31 and 32 are summarized in
Table 4.8.
The spectra for 31 and 32 are in Figure 4.20 and 4.21. The two
fragmentation routes gave rise to
1,3
A+ and
0,2
A+ ions at m/z 137 and 149 for both
compounds 31 and 32, respectively. One fragmentation route resulted in
1,3
A+,
however 1,3B+ ions that was formed in all cases of tested flavones was not observed.
0,2 +
Instead,
B ions were found at m/z 105 and m/z 137 for 31 and 32, respectively.
Similarly to flavone, losses of CO, (CO)2 and CH2O2 from the molecular mass were
seen in flavonol class.
An MS3 experiment on
0,2
A+ ions gave rise to m/z 121 due to a loss of one
CO group and m/z 93 due to a loss of two CO groups. The loss of two CO groups
from
0,2
A+ ions was diagnostic for flavonols due to the existence of the hydroxyl
group at position 3. Proposed mechanism of this fragmentation is in Scheme 4.3.
It is concluded that fragment ions of 0,2B+ and 0,2A+ ions in MS2 and fragment
ions of 0,2A+-CO and 0,2A+-CO-CO in MS3 are diagnostic for flavonols.
Table 4.8
31 and 32
Flavonols
Fisetin (32)
255.06519
287.05502
[M+H]+ (precursor)
255.06491
287.05494
1,3
A+H+
137.02294
137.02322
0,2
A+H+
149.02385
149.02346
0,2
A-CO+H+
-
121.03020
1,3
B-CO+H+
-
149.02346
0,2
B+H+
105.03543
137.02322
M-CO-CO+H+
199.08325
231.06362
M-CH2O2+H+
209.06385
241.04537
M-C2H2O3+H+
181.06819
213.05165
-
269.04096
Calculated [M+H]
+
M-H2O+H
+
110
Chapter four
Figure 4.20
MS2 pattern of 3,7-dihydroxyflavonol (31), using m/z 255 as the
precursor
Figure 4.21
MS2 pattern of fisetin (32), using m/z 287 as the precursor
111
Chapter four
Table 4.9
FT-MS3 product ions obtained from the
1.3
A+ ions of compounds 31-
32
Fisetin (32)
[1,3A+H]+ (precursor) 137.027966
137.023966
[1,3A-CO+H]+
109.029169
Table 4.10
109.030008
FT-MS3 product ions obtained from the
0,2
A+ ions of compounds 31-
32
0,2
+
Fisetin (32)
[ A+H] (precursor) 149.016303
149.023887
[0,2A –CO+H]+
121.026732
121.028754
[0,2A -CO-CO+H]+
93.034412
93.036353
Figure 4.22
112
Chapter four
Figure 4.23
MS3 fragmentation of fisetin, using m/z 137 ([1,3A+H]+) as the
precursor
Figure 4.24
113
Chapter four
Figure 4.25
MS3 fragmentation of fisetin, using m/z 149 ([0,2A+H]+) as the
precursor
HO
O
HO
0,2 +
A
O
OH
O
O
HO
HO
-CO
O
O
O
HO
HO
-CO
O
Scheme 4.3
Proposed mechanism for MS3 fragment ions of precursor ion
compounds 31 (similarly for compound 32)
114
0,2
A+ of
Chapter four
4.3.5 Structure determination of an active component in crude extract
QID015773
Figure 4.26
MS of complex of hemin with QID015773 crude extract
Screening crude plant extracts with hemin showed that there was an extract
which displayed a complex with hemin at m/z 960.262721 (Figure 4.26). The
formula of this active component (33) was deduced from its exact mass as C18H16O7
with an accuracy of 0.0007 Da (344.0896 calculated vs. 344.0903 measured). A free
active compound in a non-binding state at m/z of 345.0951 with and accuracy of
0.0017 Da was also observed.
An MS2 experiment was performed on the m/z 345 ion in crude extract and
the spectrum is illustrated in Figure 4.27 and Table 4.11. The loss of two neutral CH3
group was deduced (15.0255, with an error of 0.002 Da) and the m/z 169 ion is
designated as
1,3
A+* (the symbol * represents the parent molecule ion with a loss of
CH3 group), diagnostic for the base component of a flavonoid (Scheme 4.4) To
determine whether the second loss of the CH3 group is related to the m/z 300 ion, an
MS3 experiment was performed on the m/z 330 ion. The hypothesis that the m/z 315
originated from the m/z 330 has been confirmed (Figure 4.28, Table 4.11).
Continuing to perform the experiment on the m/z 315 ion did not show any loss of
CH3 group confirming the compound has at least two methoxyl groups. The MS3 on
m/z 330 data showed the fragment moiety m/z 169 which is 1,3A+*. The existence of
the m/z 169 at the experiment on m/z 330 showed that one of the two OCH3 groups is
115
Chapter four
at ring A. Further fragmentation of the ion did not show any loss of 15 amu showing
the possibility of the existence of one methoxyl group in ring A. Thus, it was
concluded that the remaining two methoxyl groups should be in ring B. MS4
experiment on
113 and
1,3
1,3
A+* at m/z 169 showed
1,3
A+*-CO at m/z 141,
1,3
A+*-(CO)2 at m/z
A+*-(CO)3 at m/z 85 (Figure 4.29), suggesting that 33 has two hydroxyl
and one methoxyl groups in ring A. Therefore 33 is a flavone with 5 substitution
groups. Two methoxyl and two hydroxyl groups were confirmed by MS2 and MS4
experiments and the other methoxyl group was deduced by its accurate mass. These
substitution groups are arranged in the two rings A and B. Based on the substitution
pattern recognition concluded by MS4 data by FTICR-MS, one hydroxyl group at
ring A should be in position 5 due to the fragmentation at m/z 85. Proposal for this
fragmentation is presented in Scheme 4.5. The existence of m/z 169 also suggested
that the methoxy group had to be at position 6 for the proton transfer step involving a
5- member transference, to be possible.
The pure compound (33) was also purified and its NMR data confirmed the
suggested structure (Appendix 1).
O
HO
O
O
O
6
5
OH
O
(33)
116
Chapter four
Figure 4.27
MS2 fragmentation of compound 33, using m/z 345 ([M+H]+) as the
precursor
Figure 4.28
MS3 fragmentation pattern of 33, using m/z 330 ([M-CH3+H]+) as the
precursor
117
Chapter four
Figure 4.29
MS4 fragmentation pattern of 33, using m/z 169 ([1,3A+H]+) as the
precursor
Table 4.11
33
Compound 33
[M-CH3+H]+ (precursor)
[1,3A+H]+
169.013103*
[0,2B+H]+
165.055543?
[M-CO+H]+
287.056216*
[M-CO-CO+H]+
259.061477*
+
269.043867*
[M*-CH2O2+H]
[M-CH3+H]+
330.077086/ 315.048646
* means the moiety was fragment from M-CH3 instead of M
Table 4.12
FTMS4 product ions obtained from the 1,3A+ ions of compounds 33
Compound 33
[1,3A+H]+ (precursor)
169.01498
[1,3A-CO+H]+
141.018217
[1,3A-CO-CO+H]+
113.023515
[1,3A-CO-CO-CO+H]+
85.030030
118
Chapter four
O
HO
O
O
O
HO
O
O
-CH3
O
H
O
O
OH
O
O
H
-CH3
O
O
HO
HO
O
O
O
O
HO
H
HO
O
O
O
O
O
1,3 *
HO
O
HO
C
A
O
HO
O
O
HO
OH
OH
O
Scheme 4.4 Proposed mechanism for MS2 fragment ions of precursor ion [M+H]+ of
compound 33
119
Chapter four
HO
O
HO
C
HO
O
HO
C
O
HO
O
HO
C
O
O
OH
OH
OH
HO
HO
HO
HO
C
C
HO
O
HO
C
O
O
O
OH
OH
OH
H
HO
HO
HO
HO
OH
HO
HO
HO
OH
H
HO
O
O
H
HO
HO
Scheme 4.5
Proposed mechanism for MS4 fragment ions of precursor ion 1,3A+ of
compound 33
4.3.6
Hemin - QID10644 and Hemin - QID2280289 complexes
4.3.6.1 Active compounds isolated from marine sponge extracts
Screening QID10644 crude plant extracts with hemin showed that there was
a complex with hemin at m/z 1022.4855 and a free active compound in a nonbinding state at m/z of 407.2750. The formula of this active component (34) was
deduced from its exact mass as C24H38O5 with a mass accuracy of 0.004 Da
compared with the calculated MM (406.2719 Da).
Similarly with QID2280289, an unbound active compound has MS signal at
m/z 407.2746. The formula of C24H38O5 (35) was deduced for this biota with a mass
accuracy of 0.004 Da. It was noticed that it is same formula as for QID016044. A
search on Dictionary of Natural Products for the formula returned 73 possibilities
120
Chapter four
with a variety of structural classes. Due to the uncertain conclusion from this search,
a mass-directed purification was performed for the biota.
4.3.6.2 Purification of active compounds
Based on the molecular mass of active component, mass directed purification
was conducted leading to two pure compounds. The HPLC fraction that contained
m/z 407.2 was collected. This fraction contained a pure active compound. High
resolution mass spectrometer was performed and confirmed the compound formula.
Their activity on hemin was also confirmed. These compounds were subjected to
NMR techniques for structure elucidation. The compounds were determined as
diacarnoic acid, which is also reported as an antimalarial agent. A literature search
on this compound revealed no data on NMR or its stereochemistry. Differences in
proton and carbon NMR shifts were observed for the proton at position 3 and the
methyl group at position 2. NMR data are listed in Appendix 2. Optical rotation
values ([α]D) of the two compounds were +16.74o (c = 0.1, CH2Cl2) and +47.31o (c =
0.1, CH2Cl2) for 34 and 35, respectively The active compounds isolated here were
proposed to be epi-isomers at position 3. Their structures are presented as compound
34 (erythro at C2-C3, QID016044) and 35 (threo at C2-C3, QID2280289).
O
O
O
3
H
O
O
OH
2
OH
H
O
Rel
O
(34)
O
Rel
(35)
4.3.6.3 MS2 fragmentation pattern of active component 34 of QID16044
Figure 4.30 shows MS2 fragmentation pattern for the precursor m/z 407.2750,
signals at m/z 411, 385, 367, 355, were the major fragment ions observed. High
mass accuracy of the technique showed that the neutral loss species were H2O, CO2,
C2H6O2, and C3H6O2. Scheme 4.6 proposes the fragment ions observed for
compound 34.
121
Chapter four
Table 4.13
Formula of neutral loss, observed mass, calculated mass, mass error
(Da) and fragment identity observed in the MS2 spectrum of the active compound 34
Precursor
Fragment
Neutral
Observed
Calculated Error
ions
loss
mass
mass
429.1880
(Da)
429.2617
-0.0763
429.1880
411.1906 H2O
17.9974
18.01056
-0.0132
429.1880
385.2097 CO2
43.9783
43.9893
-0.0110
429.1880
367.1922 C2H6O2
61.9958
62.03678
-0.0410
429.1880
355.1734 C3H6O2
74.0146
74.03678
-0.0222
O
O
O
O
OH
-CO2
H
O
O
O
[M + Na]+, m/z 385.2719
+
[M + Na] , m/z 429.2617
-C2H6O2
-C3H6O2
O
O
O
O
O
O
[M + Na]+, m/z 355.2249
[M + Na]+, m/z 367.2249
Scheme 4.6
122
Chapter four
Figure 4.30
4.3.6.4 MS2 fragmentation pattern of active component 35 of QID2280289
Figure 4.31 shows the MS2 fragmentation pattern of 35 using the precursor
m/z 407.2746. MS signals at m/z 385, 367, 355, 341, and 243 were observed.
Comparing this fragmentation pattern with the one of compound 34, it was noticed
that they had similar fragmentations at m/z 385, 367 and 355. Mass accuracy on
these fragment ions showed that these ions from compound 34 and 35 were identical.
Thus, it is concluded that the two compounds share the same structural moieties that
led to the same cleavage in MS2.
Compound 35 showed two extra signals at m/z 341 and 243. These two
signals were much stronger in intensity than the other signals. High mass accuracy of
the technique proved that the signals at m/z 341 and m/z 243 were M-C4H8O2 and MC9H14O4, respectively (Table 4.14, Scheme 4.7).
Collectively, MS2 fragmentation patterns were constructed for the cyclic
peroxide compounds and could discriminate the two stereoisomers. However, for
diagnostic fragmentation pattern of this structural class, a larger number of
compounds of this class are required to confirm the fragmentation pattern.
123
Chapter four
Figure 4.31
Table 4.14
Formula of neutral loss, observed mass, calculated mass, mass error
(Da) and fragment identity observed in the MS2 spectrum of the active compound 35
Precursor
Fragment
Neutral
Observed
Calculated Error
ions
loss
mass
mass
429.1854
(Da)
429.2617
-0.07629
429.1854
385.1857 CO2
43.9997
43.9893
0.0104
429.1854
367.2036 C2H6O2
61.9818
62.03678
-0.05498
429.1854
355.1807 C3H6O2
74.0047
74.03678
-0.03208
429.1854
341.155 C4H8O2
88.0304
88.05243
-0.02203
429.1854
243.1076 C9H14O4
186.0778
186.0892
-0.01141
124
Chapter four
O
O
O
O
OH
-C4H8O2
H
O
O
O
[M + Na]+, m/z 314.2093
+
[M + Na] , m/z 429.2617
-C9H14O4
O
[M + Na]+, m/z 243.1725
Scheme 4.7
4.4
SUMMARY
Hemin (target < 1000 Da) and its complex with artemisinin were successfully
detected using ESI-FTICR-MS. The accurate mass for artemisinin was deduced with
high resolution (deviation from theoretical value of less than 5 ppm). Screening 50
plant and marine sponge biota with hemin returned 4 active extracts. One of the four
active natural product compounds had the molecular mass very close to artemisinin
(Δ = 0.002 Da). The MS2 pattern of artemisinin and the suspect artemisinin active
component were used to confirm the identity of the active component as artemisinin.
Flavonoid structural class was also detected in one of the active extracts
based on its MS2 pattern. Structure elucidation of this active flavonoid was proposed
by comparing its MS3 with the MS3 fragmentation patterns of other flavonones and
flavonols. The first MS3 fragment ions of these 4 flavones and 2 flavonols were also
presented in this study.
The third and fourth active compounds were isolated based on their accurate
mass information using mass-directed purification. Their structures were determined
by NMR. They are diacarnoic acids and are epi-isomers at position 3. A MS2
experiment was performed and could discriminate between these two compounds.
125
Chapter four
This study demonstrates that known drugs can be detected, and the
rediscovery of known drugs can be prevented, using a screening campaign. Multiple
stage MS is an effective approach to recognize a structural class based on diagnostic
fragmentation patterns. For a successful screening of natural product extracts,
accurate MS and multistage MS are powerful techniques and should be used in
addition to ligand-protein complex detection.
4.5
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129
Chapter four
130
CHAPTER FIVE
MASS SPECTROMETRY IN THE RECOGNITION OF INTACT PROTEIN
COMPLEX FROM 13 KDa TO 66 KDa – METHOD DEVELOPMENT FOR
PROTEIN COMPLEXES IN NATURAL PRODUCT EXTRACT MATRIX
Abstract: A three-step methodology - protein identification, protein complex in
clean matrix identification and protein complex in natural product matrix
identification, was applied to three proteins having the molecular mass ranging from
13 kDa to 66 kDa. Difficulties in the identification process of protein complexes are
non-volatile assay buffers, protein impurities, the complexity of natural product
extract matrix, the high molecular mass of proteins and the dissociation of protein
complexes. Direct infusion, microdialysis, off-line size exclusion and on-line size
exclusion were used to resolve these difficulties.
5.1
INTRODUCTION
The chapter aims at:
(1) Setting up a method for screening natural product extracts using ESI-
FTICR-MS for different target proteins.
(2) Developing online methods for screening with natural product extracts.
(3) Mining data for chemical information of inhibitors from MS spectra.
For aim (1), this chapter presents a stepwise detection methodology for a
successful screening setup. This methodology aims at a high signal to noise (S/N)
ratio for the protein and protein-ligand complex in a clean matrix by ESI-MS. It
extends out to the application of the identification of protein complex in a complex
assay matrix such as natural product extracts. During the process to accomplish aim
(2), techniques such as direct infusion analysis, offline and online size exclusion, and
online microdialysis were employed and developed. For aim (3) different approaches
such as deduction method and trapping method combined with in source CID or
SORI-CID technique were employed to determine the ligand molecular mass.
131
Chapter five
The problems normally encountered for ESI-MS are the assay buffer
incompatibility, the protein impurities, the complexity of natural product extract
matrix, the identification of high molecular mass ions, and the dissociation of
protein-ligand complexes. These factors affecting the direct detection of the
complexes by nondenaturing ESI technique makes it necessary to select and handle
these factors in a step-by-step manner. This detection methodology involves:
(1) Identification of a protein.
(2) Identification of a protein-ligand complex in clean matrix.
(3) Identification of a protein-ligand complex in a natural product crude
extract matrix.
These steps are discussed in connection with three proteins: bovine
pancreatic ribonuclease A, human alpha thrombin, and human serum albumin.
Optimization steps for ESI source as presented in Chapter 3 are used when necessary
throughout the procedure.
5.2
RIBONUCLEASE A (MM ~ 13,700 Da)
The bovine pancreatic ribonuclease A (RNase A) superfamily, the only
enzyme family restricted to vertebrates1 has been identified in the human genome 13
and localized in chromosome 14.2 RNase A catalyzes the cleavage of RNA. Select
homologs of RNase A use this activity to effect diverse biological phenomena,
especially pathological side effects during cancer and inflammatory disorder. These
homologs include human angiogenin (ANG) a potent inducer of neovascularization
involved in cancer and in vascular and rheumatoid diseases, eosinophil-derived
neurotoxin (EDN), and eosinophil cationic protein (ECP), two neurotoxins
implicated in hypereosinophilic syndromes and allergy. EDN has been also
implicated in the soluble HIV-1 inhibitory activity by lymphocytes. These biological
activities are critically dependent on their ribonucleolytic activity, leading to a fact
that RNase A is an appealing target for the development of therapeutic intervention
for those disorders. Therefore RNase A has been the molecular target for the
development of small molecule inhibitors. These inhibitors are being developed with
the goal of restraining the biological activities of different RNase A homologs in a
variety of pathological conditions. Small molecule inhibitors of the active site of
RNase A could be of therapeutic benefit in RNase-related disorders. Molecular
132
Chapter five
modelling and crystal structures of RNase-inhibitor complexes 3,4 have led to efforts
to design such molecules using RNase A as a convenient model system.5
5.2.1
Materials and Methods
5.2.1.1 Materials
RNase A (EC#3.1.27.5, MM ~13,700 Da) is a single chain polypeptide,
isolated from bovine pancreas, containing 4 disulfide bridges. It was purchased from
Sigma Aldrich, stored at –20oC, supplied as an essentially protease, a salt-free
lyophilized powder, and used without further purification. The protein was dissolved
in ammonium bicarbonate (10 mM, pH 8) to generate stock solution (1mg/ml).
Adenosine-5’- monophosphate (AMP) (C10H14N5O7P, MM 347.22 Da) was also
purchased from Sigma-Aldrich in the form of adenosine-5’-monophosphate
monohydrate (C10H14N5O7P. H2O). It was dissolved in MeOH to generate stock
solution (10 mM). Sephadex G 25 and Biogel P-6 were purchased from Pharmacia
and Bio-Rad, respectively. Agilent tuning mixture (P/N G2421A) was used to
calibrate the instrument.
NH2
N
N
N
N
OH
O
OH
HO
OH
P
O
O
Adenosine -5’-monophosphate (36)
5.2.1.2 Methods
Five plant biota were chosen randomly from the Eskitis Institute biota
library. These biota (200 mg) were extracted with methanol (8 mL). The extracts
were evaporated and re-constituted in 800 μL methanol as a stock solution. 1 μL of
this stock solution is equivalent to 250 μg of dry weight biota.
RNase A was prepared in ammonium bicarbonate (10 mM, pH 8) at 73 μM
and 7.3 μM for online SEC-ESI-FTICR-MS and direct infusion ESI-FTICR-MS,
respectively. Incubation assay was performed in a molar ratio of 1:4 for RNase
A:AMP. The total volume of each sample was 200 μl. The sample was incubated for
133
Chapter five
1 hour, and directly infused to the MS at a flow rate of 2 μL/min. The protein
complex – natural product extract samples were prepared as above with an addition
of 1 μL of the stock natural product extract. They were incubated for one hour at
room temperature before being analyzed by MS.
(1)
For direct infusion analysis
ESI mass spectra were obtained in the positive mode with a sample flow rate
of 2 μL/min, a nebulizing N2 gas pressure of 50 psi, a counter-current drying N2 gas
flow of 30 L/min, a drying gas temperature of 125°C, a capillary voltage of 4000V,
an end voltage of 4500 V, a capillary exit voltage of 140 V, a skimmer 1 voltage of
20 V and a skimmer 2 voltage of 12 V.
(2)
For size exclusion chromatography (SEC) analysis
ESI mass spectra was obtained in the positive mode with a flow rate of 100
μL/min unless not other stated, a nebulizing N2 gas of 60 psi, a counter-current
drying N2 gas of 50 L/min, a drying gas temperature of 180°C, a capillary voltage of
4000V, an end voltage of 4500 V, a capillary exit voltage of 140 V, a skimmer 1
voltage of 15 V and a skimmer 2 voltage of 8 V.
5.2.2
MS Characterization of RNase A
ESI-FTICR-MS analysis, even in broad-band (m/z 200-6000) mode
acquisition, gave the high-resolution mass spectrum of RNase A in ammonium
bicarbonate (10 mM, pH 8) (Figure 5.1a). With the nondenaturing solution condition
used, three charge states at 6+, 7+, and 8+ were observed. The charge state 7+ was
the major one. Figure 5.1b represents an expansion of the charge state 8+, in which
m/z values were displayed in isotopic peaks. To verify the accuracy of the mass
measurements, the experimental isotopic distribution of each ion was compared to
the theoretical simulation (Figure 5.1c). As shown in Figure 5.1b and 1c, the
deviation (mass error) between the measured and theoretical mass to charge ratios
for the most abundant isotopic peak of the RNase A ions is 0.46 ppm, indicating the
high mass accuracy of the FTICR-MS technique. Figure 5.1b also shows that the
resolving power (m/Δm), of nearly 20000, can differentiate an m/z of 2000.0 and an
134
Chapter five
m/z of 2000.1. Owing to this high-resolution spectrum, the charge state z of RNase A
can be confirmed by inverting the mass difference between adjacent isotope peaks.
Figure 5.1
a) MS spectrum of RNase A in ammonium bicarbonate at charge
state of 6+, 7+, 8+ b) Experimental isotopic spectrum of RNase A at charge state 8+
c) Theoretical isotopic spectrum of RNase A at charge state 8+
135
Chapter five
5.2.3
Identification of RNase A – inhibitor complex
The RNase A solution (0.1mg/mL or 7.3 μM) was mixed with a 3-fold molar
excess of AMP in ammonium bicarbonate (10 mM, pH 8), and analyzed by direct
infusion into ESI-FTICR-MS. The Rnase A- AMP complex was also observed at the
charge states of 6+, 7+, and 8+.
Figure 5.2 shows the [M]8+ion for unbound RNase A and bound Rnase A.
The high resolution mass spectrum exhibited ions at m/z 1712.1662 and 1755.5677,
corresponding to the charge state 8+ of free RNase A and RNAse-AMP complex,
respectively. The m/z shift of 43.3905 at charge state 8+ in the spectrum corresponds
to the presence of one AMP molecule in the RNase A binding site. The binding
stoichiometry of the complex is thus one AMP molecule to one RNase A molecule.
It is noted that the average molecular mass of AMP is calculated as:
m/z shift x z = 43.3905 x 8 = 347.124 (Theoretical average MMAMP =
347.221)
136
Chapter five
Figure 5.2
a) Experimental MS isotopic spectrum of RNase A and RNase A-
AMP complex in ammonium bicarbonate at charge state 8+ b) Theoretical isotopic
spectrum of RNase A - AMP complex at charge state 8+ c) Experimental isotopic
spectrum of RNase A - AMP complex at charge state 8+
The RNase A - AMP mixture sample was also analyzed by ESI-FTICR-MS
under a denaturing condition (H2O/MeOH/CH3COOH, 50/50/1, pH 3) (Figure 5.3b).
Comparing this spectrum with the spectrum of RNase A acquired under the same
denaturing condition (Figure 5.3 a), only the pattern of protein signals at the same
charge states of 6+, 7+, 8+, 9+ and 10+ was observed and there was no signal of the
RNase A-AMP complex. The absence of complex signals under the denaturing
condition gave strong evidence that the binding of AMP to RNase A was specific.
137
Chapter five
Figure 5.3
a) MS spectrum of RNase A in denaturing condition at charge states
of 6+, 7+, 8+, 9 +, and 10+ b) MS spectrum of RNase A-AMP in denaturing
condition at charge states of 6+, 7+, 8+, 9+, and 10+. No complex signal observed
5.2.4
Identification of RNase A –inhibitor complex in natural product crude
extracts
5.2.4.1 Increasing signal to noise by size exclusion liquid chromatography
Following the successful observation of the RNase A - AMP complex, the
ability of identification of RNase A - inhibitor in crude natural product extracts was
investigated. RNase A was incubated with AMP in methanol extracts of five
randomly chosen plants, and analyzed by direct infusion ESI-FTICR-MS. Results
showed that the S/N for the unbound protein and complexes were so low that signals
for the expected species could not be detected (Figure 5.4 a). It was not unexpected
since natural product extracts contained many heavy residues, which prevented
protein ions from being ionized or desolvated. In the incubation step, if there were
active compounds in natural product extracts, these compounds would bind to the
proteins. The unwanted and unbound materials, which were detrimental to the
electrospray ionization step, should be removed.
138
Chapter five
Figure 5.4
a) Spectrum of RNase A - AMP in crude extract analyzed by direct
infusion ESI-FTICR-MS. b) Spectrum of RNase A - AMP in crude extract analyzed
by size exclusion ESI-FTICR-MS
Owing to the difference in molecular masses of the large molecular protein
and the small molecular compounds in natural product extracts, size exclusion was
utilized here to separate the high molecular mass protein from the low molecular
mass natural products. The choice of resin and the dimension of the column together
with the flow rate were designed in a trial and error mode. The flow rate had to be
set at a higher value than at the infusion mode (2 μL/min). However, it should be
kept as small as possible to maintain a similar concentration of protein entering the
ESI source. The amount of size-exclusion resin used should be large enough for an
efficient separation. The diameter of the column should not be too wide because the
flow rate should be kept at a minimal value. The length of the column should not be
too long because dissociation of protein complexes might happen if they interacted
too long with the resin. It should also not be too short because there would be no
separation of the natural product matrix and protein. After trials with two different
resins: Biogel P-6 and Sephadex G 25, and flow rates of 100 μL/min, 400 μL/min
and 1 mL/min on columns of dimension 4.6 mm x 50 mm and 4 mm x 10 mm, a
condition for the pre-purification column was chosen. A column (4.6 mm x 50 mm)
was slurry-packed with Sephadex G-25 fine resin. The resin was prepared in
NH4HCO3 and swollen overnight. This column was used for semi-purification of
139
Chapter five
RNase A and its complex from the natural product matrix. Due to the limitation in
sizes of the available column shells, columns with i.d smaller than 4 mm were not
obtainable. The smallest optimum flow rate in this online SEC setup was 1 mL/min.
Therefore the protein injected had to be 10 times more concentrated (1 mg/mL) than
that of direct infusion experiments. A flow rate of 1 mL/min passed through the
column and a post-column splitter at a ratio of 1:9 delivered a flow rate of 0.1
ml/min to the ESI source. With an injection of 20 μL of RNase A-AMP-crude
extract sample, results showed that for all samples incubated with natural products,
the protein and protein complex signals were observed at a high S/N ratio (Figure
5.4 b).
This size exclusion purification process was also designed to operate as an
online method using HPLC automation contact closure to trigger the MS software.
This setup could allow a set of 500 samples to be acquired overnight (2 min/sample).
The flow rate was set at 1 mL/min, which can be accurately delivered using an
HPLC pump. An injection volume of 20 μL is also in the range designed for a
normal HPLC auto-injector. A splitter was used to deliver the same flow rate as in
the infusion method, which has been in the optimal zone (Figure 5.5). Keeping the
flow rate at this level would cut back the number of experiments for another
instrument optimization, although modification of instrument parameter values have
always been performed throughout the experiment when needed.
Splitter
Sample
Column
MS
waste
Figure 5.5
Diagram of the online setup method using HPLC
5.2.4.2 Molecular mass of inhibitors
Knowledge of the molecular mass of an active component (ligand) in crude
extracts is the key issue to reduce the bottleneck in the isolation process in natural
product discovery. If the molecular mass is known, the commonly used and timeconsuming process of bioassay-guided fractionation will be shortened. There are two
different methods to determine the ligand molecular mass.
140
Chapter five
(1)
Deduction from MS spectrum
This method is used to calculate the molecular mass of the ligand by using
the difference of a noncovalent complex m/z and a free protein m/z. In ESI positive
mode, the m/z of a compound seen on a spectrum is calculated by the following
equation:
(m/z) = (MM + zH)/z
where MM is the molecular mass of the compound, H is the mass of the
proton charge carrier, and z is the number of protons in a particular charge state.
In a spectrum of a protein complex, we can observe (m/z)complex and
(m/z)protein at the same charge state z.
(m/z)complex = (MMcomplex + zH)/z (1)
(m/z)protein = (MMprotein + zH)/z
(2)
The molecular mass of the ligand can be deduced from (1) and (2):
MMligand = MMcomplex - MMprotein = [(m/z)complex - (m/z)protein] x z
Figure 5.6
MS spectrum of a complex at a charge state z. Two different peaks on
the spectrum: the free protein m/z and the complex m/z
Figure 5.7 shows the spectrum of RNase-AMP complex in a crude natural
product extract. The molecular mass of AMP could be quickly deduced and
calculated as follows:
141
Chapter five
MMAMP = (2007.1728 – 1957. 5957) x 7 = 347.0397
Figure 5.7
MS spectrum of RNase A-AMP complex. Peaks of RNase A and
RNase A-AMP complex at the charge states of 7+ and 8+ were observed
It was calculated that for the 5 examples of protein complex in crude extracts
(Table 5.1) the experimental molecular mass of inhibitor (AMP) had an error of 0.13
Da to 0.42 Da from the theoretical molecular mass of AMP. This result shows that
the external calibration of the instrument used in this study is very effective in the
m/z region used in this work. The ligand mass information is satisfactory with
respect to the error range for mass-directed purification. A method to deduce more
exactly the ligand mass from isotopic spectra will be discussed in Chapter 6.
Table 5.1
Result of m/z AMP detected by SEC-FTICR-MS
Sample
RNaseA-AMP-ext1
RNaseA-AMP-ext2
RNaseA-AMP-ext3
RNaseA-AMP-ext4
RNaseA-AMP-ext5
m/z RNase A- m/z RNase
AMP
A at 7+
complex at 7+
charge
charge state
state
2007.0693
1957.4052
2007.2784
1957.6567
2007.2703
1957.6071
2007.1728
1957.5957
2007.3365
1957.678
142
Experimental
MM of AMP
Theoretical
MM of
AMP
Error
in Da
347.6487
347.3519
347.6424
347.0397
347.6095
347.2218
347.2218
347.2218
347.2218
347.2218
0.4269
0.1301
0.4206
-0.1821
0.3877
Chapter five
(2)
Trapping technique
This method aimed at visualizing the m/z of the ligand binding to the protein
and then directly identifying its molecular mass. The identification of the ligand
molecular mass is illustrated in Figure 5.8. The ligand-protein complex was first
isolated in the ICR cell. Sustained off-resonance irradiation collision induced
dissociation (SORI-CID), which was discussed in 4.2.3, was applied to dissociate the
complex into the protein and the ligand.
Figure 5.8
A schematic of the trapping technique. Ligand-protein complex
isolated and dissociated into ligand and protein using SORI-CID
Rnase A-AMP complex was observed at m/z 2005.3819 at a charge state of
7+. This (RNase A-AMP)7+ complex was isolated in the ICR cell. SORI-CID
dissociated the complex into the 6+ charge state protein ([RNase A]6+) and singly
charged positive ions of the inhibitor ([AMP]1+) at m/z 348.0545. Signal for the 7+
charge state of the RNase A-AMP complex ([RNase A-AMP]7+) was also observed
because the dissociation process did not fully go to completion (Figure 5.9). The
experimental m/z of AMP, which had an error of 0.015 Da compared with the
theoretical value, illustrated the good mass accuracy achieved by this method.
Furthermore this trapping and dissociation method, which directly determined the
ligand m/z itself, had the benefit of utilizing a better MS performance at low m/z
region and of eliminating the effects of the possible formation of buffer and cation
adducts with the complexes.
143
Chapter five
Figure 5.9
MS spectrum of a dissociated RNase A-AMP complex. Peaks of
RNasa A-AMP complex at 7+ charge state, RNase A at 6+ charge state, and singly
charged AMP (m/z 348.0545)
A good signal from the detached ligand is dependent on its abundance. In
general, an accumulation of 32 scans with a data set of 32,000 data points is needed
for a good signal intensity of the ligand peak (AMP). The isolation and dissociation
of the [RNase A-AMP]7+ complex required at least 6 minutes to complete this
acquisition. Since the protein band eluting the size exclusion column lasted only 20
seconds, the maximum number of scans obtained would be only one scan, resulting
in a low signal to noise ratio of the ligand AMP peak. A switching valve (Figure
5.10) was therefore installed after the pre-purification column and replaced the
splitter setup in Figure 5.5. At the retention time of the protein complex, the valve
changed from position 1 to position 2 and the entire amount of complex was stored
in the loop with a volume of 100 μL. When this collection was finished, the valve
switched to position 1 again. At this time, a syringe pump was used to deliver the
protein complex from the loop into the MS, at a flow rate of 2 μL/min. The
switching of the valve from one position to the other was incorporated in the Agilent
Chemstation software. This setup could deliver the RNase A-AMP complex to the
MS at a reasonable concentration for at least 50 minutes. This amount of injection
144
Chapter five
time provided a sufficient accumulation of scans required for a good intensity of the
ligand peak.
LOOP
SYRINGE PUMP
FTMS
COLUMN
(B)
(A)
HPLC PUMP
HPLC PUMP
TRAPPING POSITION
Figure 5.10
ANALYSING POSITION
Switching valve used for the trapping technique
145
Chapter five
5.3
HUMAN ALPHA THROMBIN (MM ~ 37 kDa)
Thromboemolitic disorders, such as stroke, deep vein thrombosis and
myocardial infaction are some of the largest medical causes of morbidity and
mortality in western society.6 The past decade has seen a great focus on the
development of antithrombotic agents. However, the progress in this pursuit
nowhere parallels the severity of the problem due to the many disadvantages of
current medicines. Medicines used to control the generation of thrombin such as
heparins, hirudin and hirulog must be administered as either intravenous infusion in
hospital or subcutaneous injections several times a day. Medicines for other
pathways, like warfarin, an oral anticoagulant agent, effective on the vitamin-Kdependent coagulation shows a slow onset of action, requires dietary restriction, and
exhibits drug-drug interactions. The need for better drugs, which are smaller and
noncovalent-based compounds, is urgent. In the course of pursuing orally
bioavailable inhibitors, knowledge of the disorders at the molecular level continues
to be expanded. Knowledge of blood coagulation pathways has been built up in
detail. More specific targets have been developed in high throughput screening
(HTS). This HTS assay is a spectrophotometric assay measuring the increase in
absorbance at 405 nm. The enzyme FIXa cleaves the chromogenic substrate
Pefachrome FIX into a peptide and pNA.
Peptide-pNA  Peptide-COOH + pNA (yellow)
Although HTS technology has been achieved, its application is only suitable
for screening pure compound libraries. Vast potential drug sources such as natural
products cannot be explored efficiently due to interference of existing fluorescent
compounds in the natural product source with the detection absorbance wavelength
of screening technology. An alternative screening method is therefore needed.
Nondenaturing ESI-MS is a method to detect active compounds via the recognition
of the molecular mass of active ligand-protein complex. This technique can
eliminate the interference of fluorescent compounds described above. So far, there
are no reports on using this technique for the identification of complexes formed
between inhibitors and human alpha thrombin (HAT). In this chapter, difficulties
and approaches for detecting a commercial high molecular mass protein in ESIFTICR-MS as well as complexes in pure form and in plant natural product matrix
146
Chapter five
are discussed. PPACK (D-Phe-Pro-Arg-chloromethlketone), a small molecular mass
inhibitor, was spiked into a matrix of plant extract.
5.3.1
Material and methods
5.3.1.1 Materials
HAT (lot # P09007, 13.3 mg/mL, MM ~37 kDa) was purchased from
Haematologic Technologies Inc. as a buffered solution in 50% glycerol/water (v/v),
frozen at -20oC at a concentration of 13.3 mg/ml. PPACK (D-Phe-Pro-Arg
chloromethylketone, MM 451 Da) was purchased from Sapphire Bioscience Pty.
Ltd. with a concentration of 0.5 mg/mL in ammonium acetate in the TFA salt form
(H-D-Phe-Pro-Arg-chloromethylketone. TFA) (C21H31ClN6O3.C2HF3O2). It was
used as stock solution. Dysinosine A (0.01mg, C26H44N6O10S, MM 632.74 Da) was
obtained from the Eskitis Institute Natural Product compound library. The
compound was purified by HPLC, its purity (>95%) was confirmed by MS and
NMR.7 It was dissolved in methanol to generate stock solution (20 μM). Bradford
test reagent was purchased from Sigma. Phosphate buffered saline (PBS) (pH 7.4)
was purchased from Introvigen. bCA II was from Sigma-Aldrich and used without
further purification. Agilent tuning mixture (P/N G2421A) was used to calibrate the
instrument.
H
OH
N
HN
NH2
H2N
N
HO
O
H
O
H
N
O
COCH2Cl
NH
N
HN
OSO3
O
D-Phe
3
N
H
NH2
H3CO
PPACK (37)
Dysinosin A (38)
5.3.1.2 Methods
Although ammonium bicarbonate was found to be a better buffer for the bCA
II-inhibitor complexes, ammonium acetate was still a suitable buffer for HATinhibitor complexes.
147
Chapter five
Three natural product plants were chosen randomly from Eskitis Institute
biota library. These biota (200 mg) were extracted with methanol (8 mL). The
extracts were evaporated and constituted in 800 μL methanol as a stock solution.
1μL of this stock solution is equivalent to 250 μg of dry weight biota.
Incubation assay was performed in a molar ratio of 1:5 for HAT:PPACK.
The total sample volume was 30 μL. The final protein and ligand concentration is
7.3 and 36 μM, respectively. The mixture was incubated for 1.5 hour at room
temperature. Protein complex–natural product extract samples were prepared as
above with an addition of 1 μL of the stock natural product extract (QID2312883,
QID2312884, and QID007482) and dysinosin A (0.01mg).
(1)
For direct infusion and online microdialysis experiments
ESI mass spectra was obtained in the positive mode with a sample flow rate
of 2 μL/min unless stated otherwise, a nebulizing N2 gas pressure of 40 psi, a
counter-current drying N2 gas flow of 20 L/min, a drying gas temperature of 125°C,
a capillary voltage of 4000V, an end voltage of 4500 V, a capillary exit voltage of
140 V, a skimmer 1 voltage of 15V and a skimmer 2 voltage of 8 V.
(2)
For size exclusion chromatography (SEC) experiments
ESI mass spectra were obtained in the positive mode with a flow rate of 100
μL/min, a nebulizing N2 gas of 60 psi, a counter-current drying N2 gas of 50 L/min, a
drying gas temperature of 180°C, a capillary voltage of 3800 V, an end voltage of
4500 V, a capillary exit voltage of 140 V, a skimmer 1 voltage of 20 V and a
skimmer 2 voltage of 8 V.
5.3.1.4 Online microdialysis
Online microdialysis was performed by means of a microdialysis device
(Figure 5.11). The device was assembled following the work of Liu et al8 and later
modified by Benkestock et al.9 The microdialysis hollow fibre membrane (190 mm
length, 200 μm i.d., 216 μm o.d.), with a molecular mass cut-off (MMCO) of 13kDa,
was made from regenerated cellulose and purchased from Spectrum Laboratories.
Two stainless steel T-unions (0.0625’’) from Swagelok were used as end fittings.
Polyetheretherketone (PEEK) tubes were purchased from Upchurch. Two 8-mm
148
Chapter five
long sleeves were made from PEEK tubing (0.03’’ i.d., 0.0625’’ o.d). PEEK tubes
(i.d. 0.013”, o.d. 0.025’’) were inserted inside the sleeves, and used as inlet and
outlet of the T-union. The membrane was inserted into the inner PEEK tubes and
tightened to the T-union by a ferrule and a nut. The counter flow in the dialysis was
delivered by means of an Agilent HPLC pump at 300 μL/min. The sample solution
was infused at a flow rate of 2 μL/min by a Cole-Parmer syringe pump.
T-Union
Figure 5.11
5.3.2
Membrane
d
PEEK tubing
A photo of the microdialysis device used in this thesis
Identification of HAT by ESI-FTICR-MS
The purchased HAT stored in glycerol was analyzed by direct infusion ESI-
FTICR-MS at a concentration of 1 mg/mL in ammonium acetate (10 mM, pH 7).
Due to the viscosity of the glycerol in the sample there was no protein signal
observed, although ESI parameters were increased for higher energy (Figure 5.12).
Drying gas and temperature were trialed at values of almost two times greater than
that with the volatile buffer, ammonium acetate. Results show that HAT had
ionization problems caused by glycerol (non-volatile buffer). A pre-cleaning or
treatment step of HAT is needed for ESI analysis.
149
Chapter five
Figure 5.12
MS spectrum of HAT without desalting and buffer exchange
5.3.2.1 HAT desalting and buffer exchange using online microdialysis
Microdialysis is the modified form of equlibrium dialysis described in
Chapter 2. Equilibrium dialysis has a disadvantage in that it requires a long time to
reach the equilibrium state. Microdialysis can overcome this problem, and
furthermore it can be easily set up for online automation. Like equilibrium dialysis,
microdialysis was first used to monitor unbound concentrations of active
neurotransmitter compounds in the interstitial space fluid by Ungerstedt et al.10
Later, it was used for cleaning up samples of macromolecules for mass spectrometry
analysis by Liu et al.8 In this work sodium ions were greatly reduced from
oligonucleotides prior to the ESI-MS analysis. Signal intensities were enhanced
compared to the direct infusion analysis of the original samples. Intact noncovalent
complexes were preserved while migrating through microdialysis membrane by a
study of Severs et al.11 In this work, an intact myoglobin (protein-heme group)
150
Chapter five
complex migrated through the capillary column via the microdialysis junction and
could be detected as an intact complex by ESI-MS.
In this application, samples of HAT in glycerol were delivered to the hollow
fibre at a flow rate of 300 μL/min. While being in the fibre, the sample was in
contact with ammonium acetate, the dialysis counter solvent. This counter solvent
was chosen from suitable solvents for MS ionization (e.g. ammonium acetate or
ammonium bicarbonate). As the molecular mass cut off (MMCO) of the membrane
was ~13 kDa, the system allowed materials of smaller molecular masses than this
MMCO pass through the membrane and go to waste. Glycerol therefore left the
protein solution. HAT, with a molecular mass of ~37 kDa, remained in the hollow
fibre and was delivered to the MS in a solution suitable for the ionization step
(ammonium acetate or ammonium bicarbonate). As a result, the ionization efficiency
of HAT was increased owing to the reduced level of glycerol.
Waste
Detector
Sample
Dialysis counterflow
hollow fiber
Figure 5.13
A diagram of the microdialysis cell used in the buffer exchange step
for HAT
An experiment was performed with HAT to test the microdialysis device and
to choose the optimal flow rates. The flow rate of the sample and of the counter
current buffer affecting the signal intensity of HAT is illustrated in Table 5.2. The
best HAT signal intensity was obtained with the sample flow rate of 300 μL/hour
and the counter buffer flow rate of 0.05 mL/min.
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Chapter five
Table 5.2
List of flow rates trialed with HAT
Sample flow rate (μl/hour)
Counter buffer flow rate (ml/min)
Intensity (per scan)
500
0.1
~270000
300
0.05
~300000
240
0.05
~200000
After passing through the online microdialysis system, a clear improvement
of the protein signal was observed at the charge states of 10+, 11+, and 12+ (Figure
5.14), compared to no protein signal observed during the direct infusion analysis
(Figure 5.12).
Figure 5.14
MS spectrum of HAT desalting and buffer exchange using online
microdialysis
5.3.2.2 HAT desalting and buffer exchange using size exclusion chromatography
(1)
Offline size exclusion chromatography using NAP5 column
Sample buffer (glycerol) was exchanged into ammonium acetate using
NAP5, a commercial Sephadex G25 DNA grade gel filtration column (Amersham
Biociences). HAT protein was dissolved in ammonium acetate before being injected
into the column. 0.2 mg of the protein in 200 μL of ammonium acetate at pH 7 was
packed into a NAP5. Thirteen fractions were collected; each fraction was about 5
drops. Each fraction was tested using Bradford reagents (10 μL of Bradford reagent
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Chapter five
was added to 5 μL of each fraction). Fractions 2 and 3, which changed to blue color,
were normally the ones containing protein. MS analysis of these fractions confirmed
the successful replacing of glycerol by ammonium acetate (Figure 5.15). Since this
manual desalting and buffer exchange process was time-consuming, an online SEC
was set up for further experiments.
Figure 5.15
MS spectrum of HAT desalting and buffer exchange using offline
SEC
(2)
Online size exclusion chromatography
A SEC setup with BioGel P-6 and Sephadex G25 was used for HAT. The
column dimension (4 mm x10 mm) was different from the column used in RNase A.
Protein came out at 2.1 to 2.6 min at the flow rate of 100 μL/min. Results showed
that after passing through size exclusion resins, HAT was free from its original
buffer (glycerol), staying in ammonium acetate buffer, and was successfully detected
in ammonium acetate. The spectrum obtained for HAT leaving Sephadex G25
column was shown in Figure 5.16.
153
Chapter five
Figure 5.16
MS spectrum of HAT desalting and buffer exchange using online
SEC
5.3.3
Identification of HAT–inhibitor complex
Dysinosin A, a noncovalent inhibitor of HAT, was used in one experiment
with SEC-FTICR-MS for a demonstration of the detection of HAT-dysinosin A
noncovalent complex in a natural product matrix. The isolation of this natural
product is laborious, plus the existence of this natural product in the source is scarce.
In other experiments PPACK, an irreversible (covalent) inhibitor of HAT, was used.
5.3.3.1 Observation of HAT-PPACK complex using online microdialysis ESIFTICR-MS
The mass spectrum of the HAT-PPACK complex was obtained using online
microdialysis coupled with ESI-FTICR-MS (Figure 5.17). The complex was
maintained and detected at the charge state of 11+ (m/z 3326) while passing the
microdialysis device. The unbound protein HAT peak was also observed at 11+
charge state (m/z 3289). Although the present work demonstrates the validity of the
application of online microdialysis for HAT and HAT-PPACK analysis by ESIFTICR-MS, there are several issues to consider, such as the robustness of the
microdialysis device in terms of membrane fouling. Blockages of the membranes are
likely if all the fine particulates are precipitated. The capture of the protein complex
and subsequent elution is needed to be efficient and reproducible. It is possible that
154
Chapter five
unknown small molecules and large particles in natural product extracts have
diffused into the membrane pores and built up on the membrane, causing the fouling
effect and affecting the efficiency of the dialysis of larger molecules. Five samples
of HAT-natural product extract were prepared by mixing HAT (25 μL of 8.6 μM)
and 1 μL of natural product extract stock solution. The samples were incubated for
one hour at room temperature and then analysed by using online microdialysis
FTICR-MS. The protein signal was observed but the dialysis membrane was blocked
after the fifth sample analysis.
It was time consuming preparing a microdialysis device. A long delay time
was required (~6min) from the starting point to the acquisition point, therefore
online SEC was a more practical choice for analyzing HAT-small inhibitor
complexes.
Figure 5.17
MS spectrum of HAT-PPACK using online microdialysis
5.3.3.2 Observation of HAT – PPACK complex using online SEC-ESI-FTICR-MS
The protein complex solution of HAT-PPACK was injected into the online
SEC coupled with FTICR-MS. The HAT-PPACK complex signal was observed at
10+, 11+, and 12+ charge states and shown in Figure 5.18.
155
Chapter five
Figure 5.18
a) MS spectrum of HAT-PPACK using online SEC b) MS spectrum
of HAT using online SEC
5.3.3.3 Observation of HAT-PPACK in natural product crude extracts using
online SEC-FTICR-MS
HAT-PPACK was mixed together and spiked with three plant extracts (Table
5.3). The samples were incubated for one hour at room temperature before analyzing
by SEC-ESI-FTICR-MS. The spectra show that the complex survived while passing
through the column, and was detected in the setting of natural product extracts
(Figure 5.19a). The complexes formed in all three samples together with the
unbound protein were detected at the charge state of 11+. Their m/z values are
presented on Table 5.3. From these m/z values the average molecular mass of
PPACK was deduced (Section 5.3.5.1).
156
Chapter five
Table 5.3
m/z values of HAT-PPACK complex, HAT at 11+charge state
and average molecular mass of PPACK
Sample
m/z HAT-PPACK
m/z HAT (charge
MMavg
complex (charge
11+)
(PPACK)
3327.2261
3289.4482
415.55
3327.2621
3289.4637
415.78
3327.1745
3289.4482
415.0
11+)
HAT-PPACKQID2312883
HAT-PPACKQID2312884
HAT-PPACKQID007482
Figure 5.19
a) MS spectrum of HAT-PPACK complex in crude extract
QID23122883, b) MS spectrum of HAT in crude extract QID23122883
5.3.3.4 Observation of HAT–dysinosin A complex in crude extract using online
SEC-ESI-FTICR-MS
HAT-dysinosin A was mixed together and spiked with 1 μL of a plant
extract. The mixture was incubated for one hour at room temperature before
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Chapter five
analysis. A HPLC flow rate of 0.1 mL/min was used so the entire flow could enter
the ESI source. Instead of using a splitter to direct a small ratio of the protein from
the column to the MS, as in the case of RNase A, the use of low flow rate aimed to
minimize the loss of protein to the waste line. A dissociation of HAT-dysinosin A
complex was detected when a low flow rate was employed in the column setup for
RNase A (4.6 mm x 50 mm). It was thought that when flow rate was small, the
amount of time the complex was exposed to the resin became longer and
dissociation of the complex might occur. Therefore, to shorten the interaction time
between the complex and the resin, a shorter column was used. A new self-packed
column (4 mm x 10 mm) was prepared. Figure 5.20 shows the MS spectrum for the
HAT-dysinosin A complex. The complex was maintained while passing through the
column.
Figure 5.20
MS spectrum of HAT-dysinosin A complex in crude extract acquired
by SEC-FTICR-MS
5.3.5
5.3.5.1 Molecular mass of PPACK
The average molecular mass of the active part of PPACK was deduced from
the spectra of HAT-PPACK complex and HAT (Figure 5.19).
MM ligand = (3327.2261 – 3289.4482) x 11 = 415.55
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Chapter five
An experimental mass of the active ligand was 415.55 Da. This value did not
correspond to the theoretical average mass of PPACK (450.96218 Da). The
difference of 35.5 Da was too big for an acceptable error. Literature searches were
performed on reaction mechanisms between PPACK and HAT, however no
explaination was found. A search at the protein databank for the X-ray crystallization
of HAT with PPACK revealed the ligand structure. The amino acid sequence for
PPACK is Phe-Pro-Arg-methylene-chloride, however in the crystal structure the
active ligand is Phe-Pro-Arg-methylene. Chlorine is a leaving group in the reaction
forming a covalent bond between PPACK and HAT. The theoretical average mass of
the active moiety Phe-Pro-Arg-methylene is 415.51 Da. Thus the MS result here was
very consistent with the X-ray structure analysis, confirming the active moiety of
PPACK when binding to HAT. This interesting result confirms FTICR-MS is a
powerful technique for drug development and will invite further study for
investigation of the binding sites for PPACK.
5.3.5.2 Molecular mass of dysinosin A
The average molecular mass of dysinosin A was deduced from the MS
spectrum (Figure 5.20).
MMaverage = (3337.0781 – 3279.5402) x 11 = 632.91
There was an error of 0.17 Da when compared with the exact average
molecular mass of dysinosin A (632.74 Da). This error is in the accepted error range
for MS acquired in low-resolution mode and for mass directed purification. This
information will help researchers to isolate the active compound using mass-directed
purification.
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Chapter five
5.4
Human serum albumin (HSA, MM ~ 67 kDa)
Human serum albumin (HSA) is the most abundant plasma protein,
contributing 60% w/w of the total protein content of the plasma. A molecule of HSA
consists of a single non-glycosylated polypeptide chain of 585 amino acids and
having a molecular mass of 66,500. The amino acid sequence of HSA has been
established by protein sequence analysis
12
and more recently by genetic analysis.13
HSA contributes 85% of the osmotic effect of normal plasma. Thus HSA is the
principal regulator of plasma volume. Besides contributing to colloid osmotic blood
pressure HSA aids in the transport, distribution and metabolism of many endogenous
and exogenous ligands. It is involved in the transfer of many ligands across organcirculatory interfaces such as in the liver, intestine, kidney and brain.14
HSA is used in this study as a protein target for screening because it is
desirable to develop a detection method that can quickly identify compounds
transferable by HSA. HSA can also be used as an off-target protein, to which too
much drug binding or irreversible binding can lower the active concentration of the
drug as well as affecting the pharmacokinetic, pharmacodynamic and toxicological
properties of the drug. HSA is chosen here as a model to test whether our FTMS (4.7
Tesla) can detect protein complex above 66 kDa. The bioaffinity MS screening is
rapid and can provide valuable information early in the drug development process.
5.4.1
Materials and Methods
5.4.1.1 Materials.
HSA (MM ~ 66,500 Da) was purchased from Sigma-Aldrich and used
without further purification. It was dissolved in ammonium acetate (10 mM, pH 7) to
generate stock solution (10 mg/mL). Warfarin (C19H16O4, MM 308.3287 Da) was
purchased from Sigma-Aldrich and dissolved in MeOH to generate stock solution (1
mg/mL). The Agilent tuning mixture (P/N G2421A) was used to calibrate the
instrument. One natural product plant was chosen randomly from Eskitis Institute
biota library. The dried, ground plant material (200 mg) was extracted with methanol
(5 mL). 10 μL of this raw methanolic solution is equivalent to 400 μg of dry weight
biota.
160
Chapter five
O
O
OH
O
Warfarin (39)
5.4.1.2 Methods
HSA (190 µL, 2mg/ml) was mixed with warfarin (10 µL, 1mg/mL) to the
molar ratio of 1:6 (HAS:warfarin). The total sample volume was 200 μL. The
mixture was incubated for one hour at room temperature prior to analysis. The HSAwarfarin-natural product extract sample was prepared as above with an addition of
10 µL of the stock marine extract. The marine extract was prepared from 200 mg dry
weight of material in 5 mL MeOH. Ammonium acetate was used as a buffer for this
HSA complex.
(1)
For direct infusion experiments
ESI mass spectra were obtained in the positive mode with a sample flow rate
of 2 μL/min, a nebulizing N2 gas pressure of 50 psi, a counter-current drying N2 gas
flow of 30 L/min, a drying gas temperature of 125°C, a capillary voltage of 4000V,
an end voltage of 4500 V, a capillary exit voltage of 140 V, a skimmer 1 voltage of
15V and a skimmer 2 voltage of 8 V.
(2)
For size exclusion chromatography (SEC) experiments
ESI mass spectra were obtained in the positive mode with a flow rate of 100
μL/min, a nebulizing N2 gas of 60 psi, a counter-current drying N2 gas of 60 L/min, a
drying gas temperature of 180°C, a capillary voltage of 3700 V, an end voltage of
4500 V, a capillary exit voltage of 140 V, a skimmer 1 voltage of 23 V and a
skimmer 2 voltage of 15 V.
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Chapter five
5.4.2
Identification of HSA by ESI-FTICR-MS
5.4.2.1 Direct infusion with HSA
HSA (2 mg/mL) was dissolved in ammonium acetate buffer (10 mM, pH 7),
and infused directly to the ESI-FTICR-MS. The mass spectra of this sample under
three different capillary exit voltages: 100 V, 140 V and 200 V are shown in Table
5.4. The spectra at capillary exit 100 V and 140 V showed low S/N signal indicating
that the desolvation was not efficient at these voltages. Another remark is that the
higher the capillary exit voltage was, the better the signal of HSA was (Table 5.4).
Capillary exit voltage was indeed an important factor in the desolvation process of
high molecular mass sample ions (discussed in Chapter 3).
Table 5.4
Signal intensity for HSA by direct infusion analysis
Capexit (V)
Intensity of HSA
100
4000
140
16000
200
76360
The stability of the protein was also studied in two experiments. The
physiological condition was obtained using ammonium acetate at pH 7.0. The
denaturing condition was prepared using H2O/MeOH/2% acetic acid; pH 3. Mass
spectra for the protein in these two conditions showed a clear difference in the
behavior of protein charge states. In the physiological condition, the highest intensity
of the protein signal was at charge 17+ (Figure 5.21). However, in the denaturing
condition (H2O/MeOH/2% acetic acid; pH 3), the charge envelope of the protein
changed to higher charge states (Figure 5.22). The shift from charge 17+ to charge
31+ was a clear indication that ammonium acetate was the right buffer condition for
the study and the addition of an organic solvent and organic/inorganic acids as
routinely used for ESI-MS would destroy the native form of the protein.
162
Chapter five
Figure 5.21
Mass spectrum of HSA acquired by direct infusion with capillary exit
voltage 200 V, HSA 17+ charge state was the major peak.
Figure 5.22
Mass spectrum of HSA acquired by direct infusion under denatured
condition (pH 3) with capillary exit voltage 200 V, HSA 31+ charge state was the
major peak.
5.4.2.2 Online size exclusion chromatography for HSA
HSA was prepared as in the direct infusion experiment (at physiological
condition). It was injected by the auto-sampler of an Agilent HPLC to a self-packed
Sephadex G-25 column (4 mm x 10 mm). The injection volume was 20 μL, the
elution solvent was ammonium acetate, and the flow rate was 0.1 mL/min. The
protein eluted at a retention time of 2.2 min. Experiments were performed with three
different capillary exit voltages: 100 V, 140 V and 200 V. With each capillary exit
163
Chapter five
voltage, the S/N ratio of the protein (HSA) was much better than that observed in
direct infusion analysis (Table 5.5). Online SEC was employed further for the
experiments with HSA–warfarin sample.
Table 5.5
Signal intensity for HSA and HSA-warfarin complex using SEC-
FTICR-MS analysis
Capexit (V) Intensity of HSA/scan Intensity of HSA-warfarin/scan
100
6500
not observed
140
29000
7000
200
20000
not observed ( complex disruption)
5.4.3
Identification of HSA-warfarin complex
5.4.3.1 Direct infusion analysis
The HSA-warfarin sample was analyzed by direct infusion ESI-FTICR-MS.
No signal was observed at capillary exit voltage of 100 V and 140 V. At capillary
exit voltage of 200 V there was a signal of HSA but no signal of HSA-warfarin
complex observed (Table 5.5). It was possible that in the purchased HSA there were
impurities preventing the ionization efficiency of the ESI process, and therefore the
observation of protein complex signal could not occur at a low capillary exit voltage.
At a high capillary exit voltage the protein HSA-warfarin noncovalent complex
could not survive the harsh conditions and was dissociated. To prove this, the
purchased HSA and HSA-warfarin samples were analyzed by using SEC-FTICRMS.
5.4.3.2 Online size exclusion chromatography
Experiments performed for three different capillary exit voltages showed that
at a capillary exit voltage of 100V, the complex S/N ratio was very low. At 200 V
the complex signal was not observed (Table 5.5). At 140 V, although the complex
signal was not great, the complex still remained intact and was observed at the
charge states of 16+, 17 + and 18+. The 17+ charge state was the major peak at m/z
3931.6134 (Figure 5.23 a). The HSA sample was also analyzed at the capillary exit
voltage 140V, giving the signals at charge states of 16+, 17+ and 18+. The peak of
17+ charge state was the highest peak at m/z 3913.5579 (Figure 5.23 b).
164
Chapter five
Figure 5.23
a) MS spectrum of HSA-warfarin complex acquired by SEC-FTICR-
MS at capillary exit 140 V, b) MS spectrum of HSA acquired by SEC-FTICR-MS at
capillary exit 140 V
5.4.4
Identification of HSA-warfarin in crude extract
The HSA-warfarin-natural product extract sample was analyzed by SEC-
FTICR-MS under capillary exit voltage of 140 V. The complex signal was observed
at charge states of 16+, 17+ and 18+. The major charge state for the complex was the
17+ charge state with m/z 3932.4370 (Figure 5.24a). Similarly the HSA-natural
product extract sample was analyzed by SEC-FTICR-MS. The protein HSA signal
was also observed at the charge states of 16+, 17+ and 18+. The major peak was at
the 17+ charge state with m/z 3914.2236 (Figure 5.24b).
165
Chapter five
Figure 5.24
a) MS spectrum of HSA-warfarin complex in natural product crude
extract acquired by SEC-FTICR-MS, b) MS spectrum of HSA in natural product
crude extract acquired by SEC-FTICR-MS
5.4.5
The average molecular mass of warfarin was calculated based on the
difference of the signals for the protein complex and unbound protein at the same
charge.
MM warfarin = {(m/z) [HSA-warfarin]17+ - (m/z)[HSA]17+}x 17
= (3932.4370 – 3914.2236) x 17 = 309.62
The average molecular mass was 309.62. Compared with the theoretical average
molecular mass of warfarin (308.3287), the error is greater than 1 Da, which is not
acceptable for the minimal acceptable mass tolerance for mass-directed purification
(i.e. 0.5 Da).
To determine accurately the molecular mass of the inhibitor (warfarin), the trapped
method was used. This method was described earlier in this chapter (Section
5.2.4.2). A switching valve (Figure 5.10) was used to trap the HSA-warfarin
noncovalent complex. The sample HSA-warfarin-natural product extract was
injected into the size exclusion column. At 2.1 min the switching valve went to the
166
Chapter five
position 2 to trap the complex in a loop. At 2.6 minutes the valve switched to the
position 1 and a syringe pump pushed the complex into the MS. The MS2 experiment
was first performed with the isolation of the complex in the ICR cell. The complex
was subsequently dissociated into the protein and ligand ions using SORI-CID. The
isolation step was not successfully carried out. Therefore a variation of SORI-CID,
in-source CID was used here. In-source CID is a dissociation technique where the
ion fragmentation process happens in the ESI source. The ligand-protein complex
ions are transferred intact from the solution phase into the ESI source where they are
fragmented into the protein and the ligand by increasing the capillary exit-skimmer
voltage (Figure 5.25). With this technique there is no need to isolate the proteinligand complex, thus it is applicable to cases where the isolation step in the ICR cell
is not easy to achieve. Furthermore the reading of the molecular mass of small
molecule ligands happens in the low m/z region of a spectrum where the MS
performance achieved better results.
Figure 5.25
Protein-ligand complex dissociated into protein and ligand by using
in source CID
For the HSA-warfarin complex it was found that at the capillary exit voltage
of 200 V the complex was dissociated (Table 5.5). Therefore the in-source CID was
applied to the HSA-warfarin complex under this capillary exit voltage. Figure 5.26
showed the signal for singly charge state warfarin at m/z of 309.14. Comparing with
the theoretical m/z of warfarin of 309.11, the acquired m/z has a mass accuracy of
0.03 Da, which is an acceptable tolerance for the mass-directed purification step.
167
Chapter five
Figure 5.26
MS spectrum of disrupted HSA-warfarin complex using in source
CID
5.5
SUMMARY
In this chapter, the successful identification of three target proteins, their
protein complexes in a clean matrix and in a natural product extract matrix has
confirmed that ESI-FTICR-MS can contribute to a drug discovery process in an
active and essential way. In particular, methods have been developed to overcome
problems caused by inherent buffers in proteins, protein impurity and the
complicated natural product extract matrix. These methods can be performed
manually, or in an automated way. It has been found that microdialysis and size
exclusion chromatography are suitable methods for protein desalting and buffer
exchange in clean matrix. However, in a natural product matrix, microdialysis
resulted in blockages due to fouling. On the other hand, size exclusion
chromatography has proved to be superior both in its function as a separator, and
also in its high throughput performance. ESI-FTICR-MS or SEC-FTICR-MS can
detect protein and protein noncovalent complexes in a natural product matrix from
13 kDa up to 66 kDa. The results support the conclusion that the ability of FTICRMS to give accurate molecular mass of the inhibitors represents a powerful means
for screening natural product extracts in the drug discovery process of finding
diversified small molecule inhibitors.
168
Chapter five
5.6
REFERENCES
1.
Finishing the euchromatic sequence of the human genome. Nature (London, United
Kingdom) 2004; 431: 931-945.
2.
Cho S, Beintema JJ, Zhang J: The ribonuclease A superfamily of mammals and birds:
identifying new members and tracing evolutionary histories. Genomics 2005; 85: 208-220.
3.
Leonidas DD, Shapiro R, Irons LI, Russo N, Acharya KR: Crystal structures of ribonuclease
A complexes with 5'-diphosphoadenosine 3'-phosphate and 5'-diphosphoadenosine 2'phosphate at 1.7 .ANG. resolution. Biochemistry 1997; 36: 5578-5588.
4.
Leonidas DD, Chavali GB, Oikonomakos NG, Chrysina ED, Kosmopoulou MN, Vlassi M,
Frankling C, Acharya KR: High-resolution crystal structures of ribonuclease A complexed
with adenylic and uridylic nucleotide inhibitors. Implications for structure-based design of
ribonucleolytic inhibitors. Protein Sci 2003; 12: 2559-2574.
5.
Russo N, Shapiro R: Potent inhibition of mammalian ribonucleases by 3',5'-pyrophosphatelinked nucleotides. J Biol Chem 1999; 274: 14902-14908.
6.
Wolff ME: Principles of Medicinal Chemistry, 4th Edition. Edited by William O. Foye,
Thomas L. Lemke, and David A. Williams. 1996.
7.
Carroll Anthony R, Pierens Gregory K, Fechner G, De Almeida Leone P, Ngo A, Simpson
M, Hyde E, Hooper John NA, Bostrom S-L, Musil D, Quinn Ronald J: Dysinosin A: a novel
inhibitor of factor VIIa and thrombin from a new genus and species of Australian sponge of
the family Dysideidae. J Am Chem Soc 2002; 124: 13340-13341.
8.
Liu C, Wu Q, Harms AC, Smith RD: On-line microdialysis sample cleanup for electrospray
ionization mass spectrometry of nucleic acid samples. Anal Chem 1996; 68: 3295-3299.
9.
Benkestock K, Edlund P-O, Roeraade J: On-line microdialysis for enhanced resolution and
sensitivity during electrospray mass spectrometry of non-covalent complexes and
competitive binding studies. Rapid Commun Mass Spectrom 2002; 16: 2054-2059.
10.
Ungerstedt U, Pycock C: Functional correlates of dopamine neurotransmission. Bull Schweiz
Akad Med Wiss 1974; 30: 44-55.
11.
Severs JC, Smith RD: Characterization of the microdialysis junction interface for capillary
electrophoresis/microelectrospray ionization mass spectrometry. Anal Chem 1997; 69: 21542158.
12.
Meloun B, Moravek L, Kostka V: Complete amino acid sequence of human serum albumin.
FEBS Letters 1975; 58: 134-137.
13.
Lawn RM, Adelman J, Bock SC, Franke AE, Houck CM, Najarian RC, Seeburg PH, Wion
KL: The sequence of human serum albumin cDNA and its expression in E. coli. Nucleic
Acids Research 1981; 9: 6103-6114.
14.
Pardridge WM: Plasma protein-mediated transport of steroid and thyroid hormones. Am J
Physiol 1987; 252: E157-164.
169
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170
Chapter six
CHAPTER SIX
DIRECT SCREENING OF NATURAL PRODUCT EXTRACTS USING
MASS SPECTROMETRY
Abstract: This chapter firstly presents the method setup for the identification of
bovine carbonic anhydrase II and its complexes. It then describes the results of the
application of the method in screening 85 methanolic crude extracts for new
inhibitor(s). The study used 10 alkaloid-enriched plant extracts and 8 desalted
marine sponge extracts, spiked with specific inhibitors of bovine carbonic anhydrase
II (bCA II; EC4.2.1.1), as a model set to test the ability of the method to identify
protein noncovalent complexes . The spiked extracts were incubated with bCA II and
then analyzed by ESI-FTICR-MS. The noncovalent complexes were detected and the
specific inhibitors were re-identified. There was no interference from the
desalted/alkaloid-enriched extracts to the formation of the noncovalent complexes.
The method allowed quick identification of the molecular mass of the bound ligand.
The quantification of the ligand binding to bCA II was illustrated by measuring the
dissociation constant for the bCA II-sulfanilamide complex. This method was then
applied to identify natural product compounds binding bCA II. Direct infusion and
online size-exclusion chromatography electrospray ionization Fourier transform ion
cyclotron mass spectrometry (SEC-ESI-FTICRMS) were employed to detect intact
target-ligand complex. Eighty-five methanolic plant extracts were screened against
bCA II, by direct infusion ESI-FTICR-MS and by online SEC-ESI-FTICR-MS. One
noncovalent complex was identified from the same plant extract by both methods.
The molecular mass of the bound ligand from this extract was determined. Mass
directed purification gave 6-(1S-hydroxy-3-methylbutyl)-7-methoxy-2H-chromen-2one (42), as the active compound. Subsequently, the binding to bCA II was
confirmed by ESI-FTICR-MS. The binding specificity was determined by competition
experiments between 42 and furosemide, a specific ligand of bCA II.
171
Chapter six
6.1
INTRODUCTION
This chapter demonstrates the ability of ESI-FTICR-MS in detecting
noncovalent complexes and identifying the active ligands in natural product extracts
in a high throughput mode. The target selected for this study was bovine carbonic
anhydrase II (bCA II) with the molecular mass of 29 kDa.
Carbonic anhydrases (CAs) (EC4.2.1.1) are metalloenzymes that catalyze the
following reversible reaction:
CO2 + H2O ↔ HCO-3 + H+
CAs can be divided into three classes: α, β, and γ. CA II is catalytically the
fastest member of the zinc-dependent α-class CA family.1 The reversible
interconversion of carbon dioxide and bicarbonate is important in many
physiological and biochemical processes. CA has been exploited clinically for many
decades and recently there has been renewed interest due to the discovery of
carbonic anhydrase isoforms in cancer cells.2,3 Inhibitors and activators of CA have
applications as treatments of glaucoma, osteoporosis, and cancer.4 CA II is
catalytically the fastest member of the zinc-dependent α-class CA family.1 bCA II is
commercially available and is a good model for the human homologue with 79.5%
sequence homology.5 This protein was chosen as a model target protein in various
studies for screening of combinatorial library compounds.6-8 There is no report, to
date, for choosing it as a target protein for screening natural product extracts.
To demonstrate the ability of ESI-FTICR-MS in detecting noncovalent
complexes, and identifying the active ligands, natural product extracts were prepared
using desalted marine sponge crude extracts and plant alkaloid-enriched crude
extracts and incubated with bCA II. Extracts were spiked with known specific bCA
II inhibitors, ethoxzolamide with a binding constant in the nanomolar range, and
sulfanilamide in the micromolar range. This study shows that the developed
technique can identify a complex of the protein-ligand in an extract mixture and
detect both known strong and weak ligands of bCA II. The dissociation constant
was calculated for bCA II-sulfanilamide to confirm the ability of the technique in the
preservation of intact protein complexes.
ESI-FTICR-MS was then applied to screen plant extracts based on the
formation of a noncovalent complex between a protein target and active constituents.
Eighty-five methanolic plant extracts incubated with bCA II were analyzed by ESI-
172
Chapter six
FTICR-MS using two methods, direct infusion analysis and online size exclusion
analysis. One active extract was identified by both methods. The active naturally
occurring coumarin-type compound isolated from this extract was confirmed to
specifically bind to bCA II. A rapid online size exclusion chromatography coupled
with ESI-FTICR-MS (SEC-ESI-FTICR-MS) was successfully developed, thus
enhancing the sensitivity of complex detection and reducing acquisition time.
6.2
6.2.1
Materials
Bovine carbonic anhydrase II (EC 4.2.1.1, 29089 Da) was purchased from
Sigma-Aldrich, and used without further purification. It was dissolved in ammonium
bicarbonate (10 mM, pH 8) to generate stock solution (34 µM). Sephadex G25 was
purchased from Pharmacia. The inhibitors of bCA II used in this study were from
Sigma-Aldrich, and listed in Table 6.1. They were dissolved in methanol to generate
stock solutions (400 µM).
Table 6.1
Structures and binding constants of the bCA II inhibitors used in this
study
Inhibitor name
9,10
(1) Ethoxzolamide
Inhibitor structure
Kd
C2H5O
0.25 x 10-9 M/
S
SO2NH2
N
0.15 x 10-9 M
C9H10N2O3S2
(16)
(2) Sulfanilamide11
4.4 x 10-6 M
NH2
SO2NH2
C6H8N2O2S
(40)
(3) Furosemide12
6.4 x 10-7 M
OH
O
HN
SO2NH2
O
Cl
C12H11ClN2O5S
(41)
173
Chapter six
6.2.2
Natural product extracts
6.2.2.1 bCA II- inhibitor in natural matrix experiments
For the bCA II-inhibitor in natural matrix experiments, 10 dried, ground
plant samples (200 mg) were extracted with methanol. These methanol extracts were
eluted through a strong cation exchange column. The column was flushed with
ammonia (20 %)- methanol (80%) solution to generate alkaloid - enriched extracts.
These extracts were dried, and reconstituted with methanol (800 μL).
Eight freeze-dried, ground marine sponge sample (200 mg) were extracted
with methanol. The methanol was evaporated from the extracts. The extracts were
then desalted using C18 cartridge and water. The desalted materials were eluted with
methanol and dichloromethane, and subsequently reconstituted with methanol (800
μl).
Three sets of samples for proof of concept experiments were prepared as
follows:
Set 1: eighteen extracts (1µL) were incubated with bCA II (3.4 μM) in
ammonium bicarbonate (10 mM, pH 8).
Set 2: eighteen extracts (1 µL) spiked with ethoxzolamide were incubated
with bCA II (3.4 μM) in ammonium bicarbonate (10 mM, pH 8). The final
concentration of ethoxozolamide was 1 μM.
Set 3: eighteen extracts (1 µL) spiked with sulfanilamide were incubated with
bCA II (3.4 μM) in ammonium bicarbonate (10 mM, pH 8). The final concentration
of sulfanilamide was 5 μM.
The total volume of each sample was 200 μL. These 54 samples were
incubated for one hour at room temperature, and analyzed by ESI-FTICR-MS.
6.2.2.2 Raw methanolic extract screening
For the natural product extract screening, 85 biota (200 mg) of plant material,
randomly chosen from the Eskitis Institute biota library, were extracted with 5 mL
methanol. Eighty-five samples were prepared by incubating natural product
methanol extract (10 µL) with bCA II at 34 μM in ammonium bicarbonate (10 mM,
pH 8) for online SEC-ESI-FTICR-MS, and with bCA II at 3.4 μM in ammonium
bicarbonate (10 mM, pH 8) for direct infusion ESI-FTICR-MS. The total volume of
174
Chapter six
each sample was 200 μL. They were incubated for 1 hour at room temperature
before being analyzed by MS. A list of 85 biota is in Appendix 3.
6.2.3
ESI-FTICR-MS analysis
All experiments were performed at the optimum condition found for bCA II-
ethoxzolamide complex on a Bruker Apex III 4.7 Tesla external ESI source FTICR
mass spectrometer. Samples were injected directly by a Cole-Parmer syringe pump
with a flow rate of 2 μL per minute or were flow injected by a HPLC pump with a
flowrate of 100 μL per minute. The end plate voltage was biased at 3200V and the
capillary voltage at 4500V relative to the ESI needle during data acquisition. A
nebulizing N2 gas with a pressure of 50 psi and a counter-current drying N2 gas with
a flow of 30 L/min were employed. The drying gas temperature was maintained at
180ºC for online SEC-ESI-FTICR-MS and at 100°C for direct infusion ESI-FTICRMS. The capillary exit voltage was tuned at 140 V and skimmer 1 voltage at 15 V.
Ions were accumulated in an external ion reservoir comprised of an rf-only hexapole,
a skimmer cone (skimmer 2) with a tuning voltage of 12 V, and an auxiliary gate
electrode, prior to injection into the cylindrical InfinityTM analyzer cell, where they
were mass analyzed.
Mass spectra were recorded in the positive ion mode with mass range 1606000 m/z for broadband low-resolution acquisition. Each spectrum was an average of
128 transients (scans) composed of 32000 data points for high-resolution mode and
32 transients of 32000 data points for low-resolution mode. All aspects of pulse
sequence control and data acquisition were performed on a 1200 MHz Pentium III
data station running Bruker’s Xmass software under Windows operating system.
6.2.4
Other Instruments
NMR spectra were recorded at 30oC on a Varian 500 MHz spectrometer. The
1
H and 13C chemical shifts were referenced to the solvent peak for DMSO-d6 at 2.50
and 39.5 ppm, respectively. Optical rotation was measured with a Jasco P-1020
polarimeter. (+)-HRESIMS measure acquired on a Bruker Daltonics Apex III 4.7e
Fourier Transform Mass Spectrometer, fitted with Apollo API Source. Optical
rotatory dispersion was measured with a Jasco J-715 Spectropolarimeter Circular
Dichroism/ Optical Rotatory Dispersion. FTIR and UV spectra were recorded on a
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Chapter six
Bruker Tensor 27 spectrometer and Camspec M501 spectrometer. Mass directed
purification was performed on the Agilent HP1100 LC/MSD.
6.2.5
Extraction and Isolation of the Active Natural Product Compound
The ground material (5 g), a Rutaceae Leionema ellipticum (Queensland
Herbarium) was extracted with methanol. The extract was evaporated and preabsorbed onto C18 (2 g) and packed dry into a small cartridge, which was connected
to a preparative C18 column (Betasil C18, 150 x 21.2 mm, 5 μm, Thermo Electro
Corporation). This fraction was chromatographed using mass-directed purification
on a HP1100 LC/MS, eluted at 10 mL/min with a gradient solvent system starting
with 100% water (1% TFA) gradient to 60% acetonitrile (1% TFA)- 40% water (1%
TFA) in 50 min, then gradient to 100% acetonitrile (1% TFA) in the next 10 min.
Compound 42 (20 mg) eluted at 20-22 min.
6.2.6
6-(1S-hydroxy-3-methylbutyl)-7-methoxy-2H-chromen-2-one
(Compound 42)
Yellow oil, [α]D +30.2o (c=0.13, methanol); ORD (mdeg), 310 (+40), 320
(+50), 325 (+75), 330 (+153), 335 (+75) 350 (0) nm; IR (film) νmax 3436, 2954,
1731, 1619, 1561, 1494, 1465, 1370, 1273, 1206, 1139, 1018, 903, 822, 505 cm-1;
UV (MeOH) λmax (ε) 221.6 (3287), 226.0 (3349), 228 (3168), 230 (2959), 242
(2306), 253 (1886), 262 (733), 295 (2620), 317 (3242), 321 (3219), 334 (3158), 345
nm (2578) for 1H and
13
C NMR (DMSO-d6) spectra see Table 6.5; (+)-HRESIMS
m/z 263.1279 (calcd for C15H19O4, 263.1278), acquired on a Bruker Daltonics Apex
III 4.7e Fourier Transform Mass Spectrometer, fitted with Apollo API Source.
6.3
PART ONE: METHOD SETUP
6.3.1
Detection of protein by ESI-FTICR-MS in physiological pH
bCA II (3.4 μM) was dissolved in ammonium acetate (10 mM) at a pH of 7.
Mass spectrum of bCA II acquired under this physiological pH showed the peaks at
charge states of 10+, 11+ and 12+ with the major peak at the charge state of 11+
(Figure 6.1). In another experiment, bCA II (3.4 μM) was dissolved in
water/methanol/2% acetic acid at pH 3. The mass spectrum of this bCA II showed
176
Chapter six
there was a marked change in the charge state distribution. There was a shift of
lower charge states (10+, 11+, and 12+) to higher charge states (21+, 22+, and 23+)
(Figure 6.2). This increase in charge states showed that the bCA II conformation
changed from a native state to a denatured state at different pHs. Therefore, it is
recommended that the MS condition be kept at a pH between 6-8. Acidic conditions
normally used to enhance the intensity of signals in MS analysis are not appropriate
in the identification of proteins in their native form.
Figure 6.1
Mass spectrum of bCA II acquired under native condition
Figure 6.2
Mass spectrum of bCA II acquired under denatured condition
177
Chapter six
6.3.2
Detection of protein-inhibitor complex
In similar experiments as in 6.3.1, an bCA II-sulfanilamide assay was
performed in ammonium acetate (10 mM) at pH 7. Mass spectrum of this bCA IIinhibitor sample was acquired
and showed peaks of bCA II-sulfanilamide
noncovalent complexes at the charge states of 10+, 11+ and 12+ with the major
peak at the 11+ (Figure 6.3). In the denaturing condition, the bCA II-sulfanilamide
sample in ammonium acetate/acetic acid (30/70) at pH 3 was analyzed by ESIFTICR-MS. The spectrum of the bCA II-sulfanilamide sample in acetic acid did not
show any signal of the protein complex (Figure 6.4), giving evidence for
sulfanilamide specificity. In the mass spectrum of the denatured bCA II, there was a
loss of 65 Da from the protein signal. It is deduced that there is a Zn molecule
leaving the bCA II when the protein becomes denatured.13
Figure 6.3
Mass spectrum of bCA II-sulfanilamide noncovalent complex (native
condition)
178
Chapter six
Figure 6.4
Mass spectrum of bCA II-sulfanilamide (denatured condition). No
complex was observed (compared with Figure 6.2). Zn left the denatured bCA II
(compared with Figure 6.1)
6.3.3
Detection of complex formed between protein target and its ligand in
natural product extract matrix
This study chose the widely investigated natural product platforms, marine
sponge and plant biota. The marine sponge extracts were desalted before being
incubated with bCA II since nonvolatile inorganic salt is known to suppress MS
signals due to its interference in the desolvation of ESI. Plant extracts were refined to
alkaloid-enriched crude extracts. Natural products are well known for their chemical
diversity, however small molecules which have drug-like properties will deliver high
rates of success in the drug discovery pipeline.14 Alkaloid-enriched crude extracts
were used to meet this requirement at the front end of the process.
All 54 incubated samples were directly infused to the ESI-FTICR-MS. In the
natural product matrix, the spiked ligands in all 36 samples showed complex
formation with bCA II. No complex was observed in the 18 natural product extractbCA II samples, confirming the complexes identified in the bCA II-inhibitor-natural
product extract samples originated from the interaction between the inhibitors
(ethoxzolamide or sulfanilamide) and bCA II. All 54 incubated samples showed
signals of unbound protein or complexes. Some raw spectra of bCA II-natural
product extract and bCA II-inhibitor-natural product extract samples are presented in
Figure 6.5.
179
Chapter six
Figure 6.5
Spectra of bCA II-marine sponge extracts and bCA II-inhibitor-
marine sponge extracts
The 36 natural product-ligand-bCA II spectra were then compared with the
control bCA II spectrum (Figure 6.6). The masses of the charge states, from 10+ to
12+, confirm the molecular mass of the protein to be 29,088 ± 0.5 Da were in
excellent agreement for low-resolution mode with the calculated mass (29,089)
obtained from the amino acid composition. It was observed that the complex
remained intact and there was still free protein in the assay solution. For natural
product–ethoxzolamide-bCA II sample, the three charge states from 10+ to 12+
corresponding in mass to 29,345 ± 0.5 Da were in close agreement with the
calculated mass of 29,347 Da for the 1:1 complex formed between bCA II and the
ligand. For natural product-sulfanilamide-bCA II samples, the one charge state 11+
corresponding in mass to 29,261 ± 0.5 Da was in close agreement with the calculated
mass of 29,261 Da for the 1:1 complex formed between bCA II and sulfanilamide.
The experiment was performed in a low-resolution mode for a quick turn around
time (2 minutes per run).
180
Chapter six
Figure 6.6 Spectra of control bCA II, bCA II-ethoxzolamide complex and bCA IIsulfanilamide complex
6.3.3.1 Determination of ligand molecular mass from complex in natural product
extract matrix
Knowledge of molecular mass of an active component (ligand) in crude
extracts is the key issue to reduce the bottleneck in the isolation process in natural
product discovery. If the molecular mass is known, the commonly used and timeconsuming process of bio-guided fractionation will be shortened. Owing to the high
resolution of the FTICR-MS, the molecular mass of the ligand can be deduced from
the mass-to-charge ratio (m/z) of the protein-ligand complex. In this experiment,
ESI-FTICR-MS analysis of bCA II yielded the ESI positive ion mass spectrum
(Figure 6.7). Peaks corresponding to the 10+ to 12+ charge states of bCA II were
observed, with the 11+ charge state the highest peak. This charge state envelope
demonstrates that bCA II retained its compact, tightly folded structure and is in a
nondenaturing condition.13 ESI-FTICR-MS analysis of the mixture of bCA IIinhibitor-natural product extracts also gave spectra with similarly charge state
181
Chapter six
envelope (Figure 6.8). Each charge state consisted of a grouping of two peaks: one
peak at a lower m/z value corresponded to free bCA II, and the other peak at higher
m/z corresponded to bCA II-ligand complex. Because of the impurity of the bCA II
used for this experiment, the protein has an extra m/z peak at 2686.6 (11+ charge
state) seen in control sample. This explains the identity of the m/z peak at 2710.1
(2686.6 + 23.5, m/z ethoxzolamide at 11+ charge state), seen in bCA IIethoxzolamide-natural product extract samples.
Figure 6.7
Spectrum of bCA II in crude extract acquired in low-resolution mode
Figure 6.8
Spectrum of bCA II-ethoxzolamide complex in crude extract acquired
in low-resolution mode
182
Chapter six
High resolution FTICR-MS spectra showing isotopic distribution were
obtained for the bCA II complexes. Figure 6.9 shows the isotopically resolved
spectra of complexes formed by bCA II-extract spiked with ethoxzolamide and
sulfanilamide at the 11+ charge state. The average molecular mass of the bound
ligands were calculated with high mass accuracy as.15
MMethoxzolamide = [m/z(bCA II-ethoxzolamide complex) – m/z(free bCA II)] x (z)
= [2669.0269 – 2645.5385] x 11 = 258.3724 Da
MMsulfanilamide = [m/z(bCA II-sulfanilamide complex) – m/z(free bCA II)] x (z)
= [2661.1790 – 2645.5305] x 11 = 172.1335 Da
The identified ligands were 258.3724Da for ethoxzolamide, which has an error of
0.055 Da compared with the calculated molecular mass of 258.3173 Da, and
172.1335 Da for sulfanilamide with an error of 0.071 Da compared with the
calculated molecular mass of 172.2049 Da.
Figure 6.9
a) Isotopically resolved spectrum of bCA II-ethoxzolamide complex
obtained in high-resolution mode. b) Isotopically resolved spectrum of bCA IIsulfanilamide complex obtained in high-resolution mode.
6.3.3.2 Determination of dissociation constant
kon
P+L
PL
koff
Where P is protein, L is ligand, PL is protein-ligand complex
Kd = [P][L]/[PL]
183
Chapter six
Typical equilibrium binding experiments cannot be quantitatively analyzed
on the basis of classical mathematical equations when the receptor concentration is
so high that a significant fraction of the added radioligand concentration is in the
bound form. In a study by S. Swillens
16
the appropriate equations are derived and
used in a commercial graphics package to estimate the binding parameters, by
applying nonlinear regression to pseudo-experimental data.
From the law of mass action, total binding follows this equation.
Total binding = Specific binding + non-specific binding
Total Binding = (Bmax x [Ligand]free/Kd + [Ligand]free ) + [Ligand]free x NS
Where
Non-specific binding (NS) is assumed to be proportional to free ligand
concentration
Bmax is maximal binding, or the total number of binding sites
The concentration of free ligand is not known, but it equals the concentration
added minus the concentration that bound (specific and nonspecific). Defining X to
be the amount of ligand added and Y to be total binding, the total binding equation
becomes
Y= [Bmax(X – Y)/Kd + (X – Y)] + (X –Y)NS
For one side binding the total binding becomes
Y = Bmax X/(Kd+X)
The dissociation constant is most often measured by a titration experiment
where the equilibrium population of relevant species is monitored in a series of
solutions incorporating a constant concentration of protein and increasing
concentrations of ligand. The dissociation constant can be obtained as a parameter of
curve fit into the titration data using a nonlinear model relating experimentally
observed intensities and total concentrations of the protein and the ligand.
ESI-MS titration experiments were performed to determine binding constants
for protein-inhibitor complexes. To get an accurate value in an ESI titration
experiment, the protein concentration is generally below the expected Kd value and
the ligand concentration is titrated through the expected Kd.17 With our instrument, a
bCA II concentration less than 0.1 mg/mL (3.4 μM) was experimentally difficult due
to the nondenaturing ESI-MS conditions to detect noncovalent complexes. Therefore
the titration experiments were carried out with bCA II at a fixed concentration of 3.4
184
Chapter six
μM in 10 mM ammonium bicarbonate buffer (pH 8) and the sulfanilamide at a
varied concentration from 2 μM to 50 μM in nine values (2 μM, 3 μM, 4 μM, 5 μM,
6 μM, 8 μM, 10 μM, 40 μM, 50 μM). Appropriate aliquots of bCA II and
sulfanilamide solutions (200 μL) were prepared to obtain the titration samples. These
samples were incubated at room temperature for one hour before MS analyses.
Triplicate values of titration were used for the calculation of Kd.
To obtain the binding of the ligand L to the protein P, the law of mass
conservation is applied. In solution phase, a binding equilibrium of a protein-ligand
complex expressed as:
P+L
PL
It is assumed that the observed protein ion intensity reflects the true protein
concentrations.18 Either peak height or peak area can be used for quantitation
method.19 The peak height intensity of the bCA II at 11+ charge state was used here
for the calculation of the bound bCA II because the bCA II peak height intensity at
other charge states was in low abundance. The bound bCA II was calculated as
follows:
[PL]
= [P] total – [P]free
or
Intensity of PL = intensity of P total – intensity of P free
The intensity of PL was calculated by subtracting the intensity of Pfree from
Ptotal instead of the readout of intensity of the complex because the higher S/N was
seen for the protein signal. Results for MS response for PL based on charge 11+,
responding to various ligand concentrations are shown in Table 6.2
Table 6.2
Conc. (μM)
2.0
3.0
4.0
5.0
6.0
8.0
10.0
40.0
50.0
Concentration of ligand free and protein complex
MS Response for MS Response for MS Response for
PL (run1)
PL (run2)
PL (run 3)
436000.0
967700.0
834500.0
874900.0
997900.0
1293300.0
1240000.0
1445300.0
1532900.0
1435000.0
1567600.0
1653500.0
1426500.0
1567100.0
2003100.0
1470500.0
1656400.0
2057800.0
2603000.0
2146900.0
2792500.0
2602800.0
2588430.0
3211300.0
2848250.0
2680530.0
3401870.0
185
Chapter six
The Prism software was used to plot the intensity of the bound protein (bCA
II-sulfanilamide complex) against the total ligand concentration, sulfanilamide
(Figure 6.10). The software calculated the value of Kd for sulfanilamide as 5.765 μM
with the goodness of fit of 0.86. An error of 1.3 μM comparing with the literature
value of 4.4 μM was found in this experiment.
Complex instensity
4000000
3000000
2000000
1000000
0
0
10
20
30
40
50
60
[Ligand] total (µM)
Figure 6.10
Titration of sulfanilamide in bCA II for the determination of Kd
Table 6.3
Results for the determination of Kd and its curve fitness (calculated
from Prism, v. 3.0)
Equation: Y=Bmax*X/(Kd+X)
Best-fit values
BMAX
KD
Std. Error
BMAX
KD
95% Confidence Intervals
BMAX
KD
Goodness of Fit
Degrees of Freedom
R²
Absolute Sum of Squares
Sy.x
Data
Number of X values
Number of Y replicates
Total number of values
Number of missing values
3.3220e+006
5.765
172434
0.8337
2.9670e+006 to 3.6780e+006
4.047 to 7.482
25
0.8641
2.1500e+012
293278
9
3
27
0
186
Chapter six
6.3.3.3 Sensitivity of the ESI-FTICR-MS screening methodology
For ESI-MS technique, the detection limit is under the control of parameters
that influence the preservation of protein complexes prior to detection. The optimum
condition was used to determine the detection limit. Extracts from 200 mg dry
weight were dissolved in 800 μL of methanol (0.250 mg/μL). The extract volume
used for each sample was 1 μL. The total sample volume was 200 μL. The
compounds, ethoxzolamide and sulfanilamide, were titrated in a range from 2 to 0.5
μM with an increment of 0.5 for ethoxzolamide, and from 6 to 4.5 μM with an
increment of 0.5 for sulfanilamide, in the presence of protein and natural product
extracts. The protein-ligand complexes for ethoxzolamide were detected at 1 μM,
and for sulfanilamide were detected at 5 μM, at the flow rate of 2 μL per minute.
Thus specific binding for ethoxzolamide was detected at a concentration of 0.02% of
the total dry weight ((0.2x258x10-6/0.250) x 100%). Similarly specific binding for
sulfanilamide was detected at a concentration of 0.06% of the total dry weight
((0.2x172x5x10-6/0.250) x 100%). It is noted that, for a mixture of bCA II and
ethoxzolamide without natural product extracts, the bCA II-ethoxzolamide complex
was detected at concentration of 3.4 μM-0.5 μM, respectively. It proved that the
natural product extracts actually suppressed the ionization process and decreased the
MS sensitivity.
A minimum concentration of 0.1 mg/ml (3.4 μM) of protein target bCA II
should be used, as a poor signal to noise ratio was obtained with a bCA II
concentration less than 0.1 mg/ml. It took two minutes and required 13.6 pmol of
bCA II (2 μl/min x 2 min x 3.4 x 10-6 M) for screening of one extract.
187
Chapter six
PART TWO: BIO-AFFINITY SCREENING OF NATURAL PRODUCTS FOR
bCA II INHIBITORS
6.3.4
Detection of noncovalent complexes of protein and ligands in crude
extract
6.3.4.1 Method for screening natural product extracts
The screening method is summarized as in scheme 6.1.
Scheme 6.1
Screening work-flow
Samples were injected to MS using an Agilent autosampler. Mass spectra
were recorded when receiving a signal from the autosampler. For online SECFTICR-MS, data was acquired for 1 min. For the direct infusion method, data were
accumulated up to 8 to 16 min for a good signal-to-noise ratio. Two sets of data were
recorded for 85 incubated extracts, one for SEC-ESI-FTICR-MS and the other for
direct infusion ESI-FTICR-MS. Data processing was done by comparing the
spectrum of pure bCA II with spectra of bCA II-crude extracts. While all the 85
spectra of SEC-ESI-FTICR-MS showed the unbound bCA II, only 47 spectra of
direct infusion ESI-FTICR-MS showed signals for the unbound protein. However,
both methods showed a positive result for the same extract. Due to the low signal-tonoise ratio, more data accumulation was required for direct infusion ESI-FTICR-MS,
resulting in longer acquisition time (8-16 min/sample). For SEC-ESI-FTICR-MS,
the elution time for the protein complex was 1.1-2.1 min, thus the run time was
reduced to only 2.1 min per sample.
6.3.4.2 Size exclusion chromatography
A size exclusion column was used to separate large proteins or protein
complexes from small, unbound compounds, thus eliminating nuisance interferences
188
Chapter six
from crude extracts. Small molecular mass interferences are generally the main
cause of false negatives and false positives in crude extracts. Figure 5 shows four
different spectra, two obtained by direct infusion ESI-FTICR-MS and the other two
by online SEC-ESI-FTICR-MS. The spectrum obtained when incubated extracts
passed through the column is cleaner (Figure 6.11).
Figure 6.11 Spectra of bCA II-extract with and without size exclusion column
A main concern with online SEC is the dissociation of noncovalent complex
while it passes through the column. To minimize that problem, the residence time of
the noncovalent complex in the size exclusion column must be well controlled by
factors such as column length, flow rate, and gel bead size. A size exclusion column
must meet two criteria. First, it has to be short enough to preserve the noncovalent
complex. Second, it has to be long enough to be able to separate large molecules
from interferences. Experiments were done with different commercial size exclusion
columns including TosoHass column (part 18762, 4.6 mm x 30mm) and
Phenomenex BioSep-SEC-S2000 column (4.6 mm x 30mm). Although large
molecules were very well separated from smaller ones, noncovalent complexes
189
Chapter six
could not be maintained while passing through those columns. A column was made
using a guard column (4 mm x 10 mm) and packed with Sephadex G25. It was
successfully tested with sulfanilamide, a specific inhibitor of bCA II with an
inhibition constant Kd = 4.4 x 10-6 M.11 The bCA II-sulfanilamide noncovalent
complex was retained through the self-packed column. This Sephadex G25 selfpacked column proved to be suitable for preserving a complex with a weak-binding
inhibitor such as sulfanilamide, and was used in the screening of 85 plant extracts
incubated with bCA II. It is noted that the SEC-FTICR-MS spectra still showed
some signals (m/z < 500), which belonged to the natural product extracts. The
column was designed under the restraint of a few factors discussed above; therefore
it could not totally separate the complex from the natural product matrix.
Table 6.4
Properties of the size exclusion resins tested for this study
Sizeexclusion material
Diameter (μm)
MMcutoff (Da) Pore size (A°)
Sephadex G-25
20-80
1-5
na
Biogel P-6
<45
6-40
na
TosoHass (TSK-Gel SW)
10
na
na
Biosep-SEC-S2000
na
na
na
The most important factor for increasing the best separation between protein
and buffer salts is matching the flow rate to the internal diameter of the column. The
manufacturer recommended for a linear flow rate between 2 and 10 cm/h.20 Using 4
mm i.d. column, the linear flow velocity is 94 cm/h when the flow rate is 200
μL/min, an acceptable flow rate for the ESI source. Although this condition is not
within the optimal condition for the gel filtration media, it is impractical to increase
the i.d. column or decrease the flow rate since increased band spreading, analysis
time, and complex disruption result without any further signal enhancement.
The deleterious effect of overloading a sample is important in buffer
exchanging and desalting. To avoid that effect, the optimal injection volume should
be about 25% of the total column volume.21,22 The volume of this column is about
120 μL. An injection volume of 20 μL was chosen for the experiment.
190
Chapter six
6.3.4.3 Determination of ligand mass
The extract showing a noncovalent complex was re-analyzed in highresolution mode to determine the molecular mass of the bound ligand. An assay
volume of 10 μL of the re-analyzed extract was injected to the size exclusion column
at a flow rate of 200 μL/min. The unbound protein and protein complex eluted at a
retention time of 1.6 min with a bandwidth of 1.0 min. A switching valve, described
in Chapter 5, was turned to position 1 from time of 1.1 min to 2.1 min to trap the
noncovalent complex in a loop of 200 μL. It was then switched to position 2 for the
trapped purified complex to be injected into the FTICR-MS using a syringe pump. A
syringe flow rate of 2 μL/min delivered enough protein complexes to the ESI source
for data accumulation in high-resolution mode. Molecular mass of the bound ligand
was deduced from the isotopic mass of the complex.
The isotopically resolved spectrum of noncovalent complex formed by bCA
II and the active extract is shown in Figure 6.12. Peaks corresponding to the +11
charge state of bCA II-ligand complex were observed. The ligand mass is the
difference between the average molecular mass of the complex and the average
molecular mass of bCA II. The isotopic spectrum of noncovalent complex is needed
to obtain the average molecular mass of bound ligand with high accuracy.15 It was
calculated as 262.04 Da as follows.
MMboundligand = [m/z(bCA II complex) – m/z(free bCA II)] x z
= [2669.3654 – 2645.5436] x 11 = 262.04 Da
Mass directed purification was used to isolate this compound from the crude extract.
191
Chapter six
Figure 6.12
Isotopically resolved spectrum of complex bCA II- ligand from active
extract obtained in high-resolution mode
6.3.5
Structure elucidation of active compound from Leionema ellipticum
The active extract identified by both methods is a Queensland plant,
Rutaceae Leionema ellipticum. Mass-directed purification of the ion peak at m/z 263
(M+H)+ in ESI-MS positive mode afforded compound 42. Compound 42, a yellow
viscous oil, [α]D +30.2o (c=0.13, methanol) was assigned the molecular formula
C15H18O4 by HR-MS. The UV spectrum of compound 42 in methanol indicated the
presence of a 7-hydroxylated 6-(or 8-) substituted coumarin due to absorption of the
shoulders at 241, 253 and 295 nm.23 The coumarin nucleus was further supported by
the IR band at 1732 and 1619 cm-1, and typical AB-type signals at δ 6.25 and 8.01
(each 1H, d, J = 9.5Hz) for H-3 and H-4 in the HNMR spectrum. The 7hydroxylation was confirmed by HMBC correlation of the methoxyl signal at δ 3.85
to carbon 7 at δ 159 ppm. The 6-substitution was confirmed by the two singlet
aromatic proton at δ 6.98 (H-8) and δ 7.68 (H-5), which displayed HMBC
correlations to C-6, C-7, C-9, C-10 and C-4, C-6, C-7, C-9, C-10, and C-11,
respectively. The remaining signals arising from a 1-hydroxy-3-methylbutyl group
were two sets of three-proton doublet at δ 0.86 (J =7.0 Hz) and δ 0.91(J =7.0 Hz)
corresponding to two methyl groups, a one-proton multiplet at δ 1.76 (m), a two–
proton methylene multiplet at δ 1.36 (m) and a one proton methine doublet of
doublet at δ 4.9 (J=9.5, 4.0 Hz). The assignment and connectivity of these five
carbons having a hydroxyl groups were determined by COSY correlations, HMBC
correlations and HSQC data (Table 3). This interpretation was supported by the IR
bands at 3436 cm-1 and fragments at m/z 245 [M-H2O]+, and m/z 230 [M-H2O-CH3]-
192
Chapter six
.24 This 1-hydroxy-3-methylbutyl moiety, which was connected to the coumarin
nucleus at C-6, was further confirmed by the HMBC correlations of H-11 (δ 4.90,
dd, J = 9.5, 4.0 Hz) to C5, C6 and C7. According to the literature the configuration
of C-11 is determined from its ORD curve.25 If the configuration of C-11 was S the
ORD should present a positive curve. Since the compound showed a positive plane
curve, its C-11 should have the S-configuration. Thus, compound 42 was identified
as 6-(1S-hydroxy-3-methylbutyl)-7-methoxy-2H-chromen-2-one. This compound
had previously been reported as a synthetic product from a hydrogenation reaction of
a natural product.26 However, there was no NMR data reported for this compound.
OH
5
11
O
6
4
10
7
9
8
3
O
2
O
42
NMR data for compound 42 in DMSO-d6.
Table 6.5
Position
1
2
-
161.8
-
-
3
6.25 (d, 9.5)
112.5
4
2, 9
4
8.01 (d, 9.5)
144.8
3
2, 3, 5, 9, 10
5
7.68 (s)
125.5
-
4, 6, 7, 9, 10, 11
6
-
133.0
-
-
7
-
159.2
-
-
8
6.98 (s)
98.5
-
6, 7, 9, 10, 11
9
-
154.6
-
-
10
-
111.5
-
-
11
4.90 (dd, 9.5, 4.0)
64.5
12
5, 6, 7, 12, 13
12
1.36 (m)
48.6
11, 13
6, 11, 13, 14, 15
13
1.76 (m)
25.0
12, 13, 14
11, 12, 14, 15
14
0.86 (d, 7.0)
23.0
13
12, 13, 15
15
0.91 (d, 7.0)
22.5
13
12, 14, 15
16
3.85 (s)
56.1
-
7
H NMR (mult., Hz)
13
C NMR * COSY
(*) values deduced from HSQC data
193
HMBC
Chapter six
6.3.6 Confirmation and characterization of the binding
The isolated ligand with molecular mass of 262.04 (42), purified by mass
directed purification, was mixed with bCA II and analyzed by ESI-FTICR-MS
(direct infusion analysis). The noncovalent complex was confirmed with the one
charge state 11+ corresponded in mass to 29,350 ± 0.5 Da, in close agreement with
the calculated mass of 29,351 for the 1:1 complex formed between bCA II and
compound 42 (Figure 6.13).
Figure 6.13
Spectrum of bCA II-42 complex
The binding specificity of this ligand was determined by performing the
competition experiments between bCA II specific inhibitor, furosemide and
compound 42 (Figure 6.14). In this competition experiment, if compound 42 is a
specific inhibitor it will compete with furosemide for the same binding site of bCA
II.27 Assays were performed with the concentration of furosemide of 2, 3, and 4 µM.
Figure 6.14 a shows bCA II-compound 42 complex at 11+ charge state at
concentration of 3.4 µM-20 µM, respectively. The spectra shown in Figures 6.14 b-d
were obtained after mixing furosemide together with the bCA II-compound 42
complex. At the concentration of 2 µM of furosemide, the peak height intensity of
bCA II-compound 42 complex reduced from 837,630 to 462,890, and the bCA IIfurosemide complex appeared with the peak height intensity of 836,050. At the
concentration of 3 µM, the bCA II-compound 42 complex reduced further to
377,370, and the bCA II-furosemide complex increased to 1,156,300. At the
concentration of 4 µM, only bCA II-furosemide complex was seen with the peak
height intensity of 1,449,800. This experiment proved that compound 42, the natural
product ligand identified by the screening method, was a specific inhibitor of bCA
II.
194
Chapter six
Figure 6.14
Competition experiment spectra.
1
bCA II-42 complex.
2
bCA II-
furosemide complex
6.3.7
Increasing high- throughput
There is always a demand to develop a screening method with the ability to
screen as many samples as quickly as possible. Mass spectrometry based screening
techniques, which are easily coupled to automated liquid chromatography, have the
advantage of reaching the high-throughput goal. A ten-port switching valve was used
to increase the high throughput of the screening (Figure 6.15). In position 1, column
A was for the analysis and column B was regenerated. In position 2, column A was
regenerated and column B was for the analysis. It took two minutes for screening
one crude extract. Automated unattended operation has been easily achieved through
interface of HPLC with FTICR-MS.
195
Chapter six
Figure 6.15
A working diagram of using ten-port switching valve for increasing
high throughput (Gilson manual)
6.4
SUMMARY
This work successfully demonstrates that direct bioafinity screening using
ESI-FTICR-MS can detect a protein-ligand complex in a complex natural product
extract. Dissociation constant measured by the technique for bCA II-sulfanilamide
complex confirmed that the complex was preserved in the experimental conditions.
The same range of dissociation constant measured in this study compared with other
methods (5.75 μM vs 4.4 μM) confirmed that ESI-MS is a validated method in the
detection of noncovalent complexes. There was no interference from the
desalted/alkaloid-enriched extracts to the formation of the noncovalent complexes,
offering a possibility of wide applicability of this technique as a screening method.
The direct infusion method could detect unbound protein/complexes from all fiftyfour samples originated from desalted/alkaloid-enriched extracts. The method can
determine the ligand mass with an error of less than 0.08 Da and identify bioactive
compounds, if present, in a natural product extract down to the level of 0.02% dry
weight.
The results also establish that direct infusion and online SEC-ESI-FTICRMS is a superior method to screen crude natural product extracts for identifying true
binding ligands to bCA II. The direct infusion ESI-FTICR-MS method was able to
identify the protein in about 60% of protein- methanol extract mixtures, and
successfully identified one protein-ligand complex. The SEC-ESI-FTICR-MS
method was able to identify 100% protein-methanol extract mixtures and identified
one extract producing protein-ligand complex. The key advantage of the method is
that it can screen crude extracts without any preparation or fractionation work. With
196
Chapter six
a running time of 2 minutes per sample, up to several hundred crude extracts can be
screened a day.
Direct
screening can
eliminate the bottleneck
of bioassay-guided
fractionation as it allows direct isolation of active components from natural product
crude extracts using ligand mass information for mass-directed purification. This
direct bioaffinity screening mass spectrometry has great potential to become a
widely used screening method in natural product drug discovery owing to its
sensitivity, reliability and speed.
6.5
REFERENCES
1.
Lindskog S: Structure and mechanism of carbonic anhydrase. Pharmacol Ther 1997; 74: 120.
2.
Scozzafava A, Owa T, Mastrolorenzo A, Supuran CT: Anticancer and antiviral
sulfonamides. Curr Med Chem 2003; 10: 925-953.
3.
Pastorekova S, Casini A, Scozzafava A, Vullo D, Pastorek J, Supuran CT: Carbonic
anhydrase inhibitors: the first selective, membrane-impermeant inhibitors targeting the
tumor-associated isozyme IX. Bioorg Med Chem Lett 2004; 14: 869-873.
4.
Pastorekova S, Parkkila S, Pastorek J, Supuran CT: Carbonic anhydrases: current state of the
art, therapeutic applications and future prospects. J Enzyme Inhib Med Chem 2004; 19: 199229.
5.
Saito R, Sato T, Ikai A, Tanaka N: Structure of bovine carbonic anhydrase II at 1.95 .ANG.
resolution. Acta Crystallogr Sect D 2004; 60: 792-795.
6.
Gao J, Cheng X, Chen R, Sigal GB, Bruce JE, Schwartz BL, Hofstadler SA, Anderson GA,
Smith RD, Whitesides GM: Screening derivatized peptide libraries for tight binding
inhibitors to carbonic anhydrase II by electrospray ionization-mass spectrometry. J Med
Chem 1996; 39: 1949-1955.
7.
Muckenschnabel I, Falchetto R, Mayr LM, Filipuzzi I: SpeedScreen: label-free liquid
chromatography-mass spectrometry-based high-throughput screening for the discovery of
orphan protein ligands. Anal Biochem 2004; 324: 241-249.
8.
Poulsen S-A: Direct screening of a dynamic combinatorial library using mass spectrometry.
J Am Soc Mass Spectrom 2006; 17: 1074-1080.
9.
Chen RF, Kernohan JC: Combination of bovine carbonic anhydrase with a fluorescent
sulfonamide. J Biol Chem 1967; 242: 5813-5823.
10.
Mocharla VP, Colasson B, Lee LV, Roeper S, Sharpless KB, Wong C-H, Kolb HC: In situ
click chemistry: enzyme-generated inhibitors of carbonic anhydrase II. Angew Chem Int Ed
2005; 44: 116-120.
11.
Lanir A, Navon G: Nuclear magnetic resonance studies of bovine carbonic anhydrase.
Binding of sulfonamides to the zinc enzyme. Biochemistry 1971; 10: 1024-1032.
197
Chapter six
12.
Oenell A, Andersson K: Kinetic determinations of molecular interactions using Biacoreminimum data requirements for efficient experimental design. J Mol Recognit 2005; 18: 307317.
13.
14.
Lipinski CA, Lombardo F, Dominy BW, Feeney PJ: Experimental and computational
approaches to estimate solubility and permeability in drug discovery and development
settings. Adv Drug Deliv Rev 2001; 46: 3-26.
15.
Green MK, Vestling MM, Johnston MV, Larsent BS: Distinguishing small molecular mass
differences of proteins by mass spectrometry. Anal Biochem 1998; 260: 204-211.
16.
Swillens S: Interpretation of binding curves obtained with high receptor concentrations:
practical aid for computer analysis. Mol Pharmacol 1995; 47: 1197-1203.
17.
Sannes-Lowery KA, Griffey RH, Hofstadler SA: Measuring dissociation constants of RNA
and aminoglycoside antibiotics by electrospray ionization mass spectrometry. Anal Biochem
2000; 280: 264-271.
18.
Peschke M, Verkerk UH, Kebarle P: Features of the ESI mechanism that affect the
observation of multiply charged noncovalent protein complexes and the determination of the
association constant by the titration method. J Am Soc Mass Spectrom 2004; 15: 1424-1434.
19.
Goodner KL, Milgram KE, Williams KR, Watson CH, Eyler JR: Quantitation of ion
abundances in Fourier transform ion cyclotron resonance mass spectrometry. J Am Soc Mass
Spectrom 1998; 9: 1204-1212.
20.
Biorad: 2068, Desalting with Biogel@ P-6 DG Gel,Rev.B. Technote
21.
Gooding KM, Regnier FE, Editors: Chromatographic Science Series, Vol. 51: HPLC of
biological macromolecules: Methods and applications. 1990.
22.
Gooding KM, Regnier FE, Editors: HPLC of biological macromolecules. [In: Chromatogr.
Sci. Ser., 2002; 87]. 2002.
23.
Murray RDH, Mendez J, Brown SA: The natural coumarins: occurrence, chemistry and
biochemistry. New York: John Wiley & Sons Ltd, 1982.
24.
MacLeod JK: Mass spectra of some 7-methoxycoumarin derivatives with differing 6substituted C5 isoprenoid sidechains. Org Mass Spectrom 1972; 6: 1011-1022.
25.
Baba K, Matsuyama Y, Ishida T, Inoue M, Kozawa M: Studies on coumarins from the root
of Angelica pubescens Maxim. V. Stereochemistry of angelols A-H. Chem Pharm Bull 1982;
30: 2036-2044.
26.
Lahey FN, MacLeod JK: The coumarins of Geijera parviflora Lindl. Aust J Chem 1967; 20:
1943-1955.
27.
Benkestock K, Edlund P-O, Roeraade J: Electrospray ionization mass spectrometry as a tool
for determination of drug binding sites to human serum albumin by noncovalent interaction.
Rapid Commun Mass Spectrom 2005; 19: 1637-1643.
198
CONCLUSION
Drug discovery aims to develop and apply methods for the identification of
new active chemical entity from natural products. Towards this end, rapid and
effective strategies to identify the noncovalent interactions between active ligands
from natural product extracts with therapeutic protein targets without false positive
or negative results would be particularly valuable. This thesis presents the outcomes
of research exploring a novel approach of biological screening of natural product
extracts using bioaffinity ESI-FTICR-MS as a detection means.
Methods to optimize instrumental conditions for an efficient desolvation,
while still maintaining the intact non-denatured protein complexes in the gas phase,
have been established during the course of the research. It has been shown that under
optimal conditions that maximize speed, sensitivity and provide high resolution,
ESI-FTICR-MS may be used as a rapid and effective means to detect noncovalent
complexes in physiological conditions and to identify active compounds from
natural product crude extracts which interact with therapeutic proteins. The direct
detection of noncovalent complexes using ESI-FTICR-MS has been successfully
tested using an extensive range of targets with m/z varying from less than 1,000 Da
to more than 66,000 Da. There has been no interference from the natural product
extracts to the formation of the noncovalent complexes. The method has allowed
quick identification of the molecular mass of the bound ligand. The ability of the
technique in preserving intact protein-ligand complexes has been confirmed by
acquiring and comparing the spectra of these complexes under nondenaturing and
denaturing condition, or by calculating the dissociation constant for these complexes.
It is critical that the detection and analysis of the protein-ligand complexes be
accurately determined under physiological conditions to reflect the real biological
activity. This requirement, coupled with the complexity of natural product extract
matrix, present considerable challenges. These challenges have been successfully
met by the development of an online SEC-FTICR-MS. Direct infusion of ESI- and
online SEC-FTICR-MS allow accurate determination of molecular masses of the
active compounds of natural product extracts which interact with the target proteins.
An automation setup via HPLC coupled to FTICR-MS has also been established to
facilitate unattended operations with the running time of 2 min for screening one
extract using online SEC-FTICR-MS analysis.
199
The presence of nonvolatile salts, detergents, surfactants in protein media,
and other species in a natural product matrix introduces suppression effects on the
ESI process, thus hindering the detection of proteins, protein-specific ligand
complexes, protein-natural product ligand complexes, and may lead to false negative
results. In this thesis we report a near elimination of suppression effects by choosing
suitable buffers, optimizing instrumental conditions using FFD, using online
microdialysis, offline-, and online-SEC to perform desalting and buffer exchange.
The existence of weak noncovalent binding needs mild conditions during the ESI
desolvation process and also needs fast and efficient separation during the SEC
desalting or buffer exchange process as applied in this thesis. FFD was exercised in
setting the instrumental parameters such as flow rate, dry gas temperature, capillary
exit voltage for mild and efficient desolvation in ESI source. Trial and error
experiments were carried out in defining the optimal parameters for pore size, flow
rate, column length in SEC to minimize the impact of unintentional dissociation of
weak noncovalent complexes. While the unavoidable dissociation of existing insolution noncovalent complexes in the gas phase is always an issue, this thesis
demonstrated the identification of all experimental target-natural product extract
complexes.
Most notable is the successful screening of 85 raw methanolic plant extracts
with bCA II using both direct infusion and online SEC-FTICR-MS. A noncovalent
complex has been detected and the active compound which binds to bCA II
identified. The specificity of the binding has also been confirmed by competition
experiments with a specific inhibitor of the protein target. The outcomes of this work
have been reported in the Journal of Biomolecular Screening (first published online
on March 18, 2008). One of the key advantages of using ESI-FTICR-MS and
associated methods is that the screening of the crude extracts is carried out without
any preparation work such as pre-chromatographed, or pre-purification steps, thus
avoiding any contamination which may lead to false positive or negative results.
Information on the exact mass of the active compound also provides insights into the
chemical composition or structural class of the compounds, thus shortening the long
process of lead identification and allowing rapid mass-directed purification to isolate
the active compounds. A schematic of the optimal strategy for screening natural
product extracts is illustrated below:
200
DIAGRAM OF AN OPTIMAL STRATEGY FOR SCREENING NATURAL
PRODUCTS EXTRACTS USING ESI-FTICRMS
201
APPENDIX 1
1
H and 13C NMR data of compound 33
O
HO
O
9
2
3'
1'
O
3
O
4
5
OH
O
Position
1
Ha
13 b
2
-
163.3
3
6.88 (s)
103.4
4
-
182.1
5
6.60 (s)
94.6
6
-
152.7
7
-
131.7
8
-
152.7
9
-
158.5
10
-
103.8
1’
-
123.1
2’
7.52 (s)
109.5
3’
-
149.1
4’
-
152.2
5’
-
111.8
6’
7.64 (s)
120.1
7-OMe
3.74 (s)
60.0
C
3’-OMe 3.86 (s)
55.95
4’-OMe 3.84 (s)
55.80
8-OH
-
12.8(b, s)
a
Spectrum was recorded in DMSO-d6 at 25oC (500 MHz), b Spectrum was recorded
in DMSO-d6 at 25oC (125 MHz)
202
APPENDIX 2
1
H, 13C NMR, g-COSY and HMBC data of compound 34
O
O
3
H
O
Rel
O
Position
1
1
Ha
OH
2
13 b
g-COSYa
g-HMBCa
-
178.8
-
-
2
2.65
42.5
1, 3, 24
3
4.27 eq
81.4
1, 2, 24
4
1.77 (m)
22.4
3, 5
5
1.71 (m)
32.5
6
-
80.0
-
7
1.55 (m)
38.5
6, 8, 23
C
1.65 (m)
8
2.30 (dd,
22.8
6, 7, 9, 10, 17
9
-
167.8
-
10
-
130.1
-
11
-
200.4
-
12a
2.36 (m)
35.1
11, 13, 17, 18
12b
2.50 (dd, 17.4,
10, 11, 13, 17,
3.6)
18
13
-
41.1
14
1.27 (m)
41.3
-
1.48 (m)
15
1.63 (m)
18.5
16
1.34
35.7
9, 17, 21
1.95
17, 18
17
-
41.2
18
1.68 (d)
50.2
9, 11, 12, 13,
203
14, 17, 19, 20,
21
a
19
0.90 (d, 5.4)
33.0
13, 14, 18, 20
20
0.93(d, 5.4)
21.3
13, 14, 18, 19
21
1.08 (s)
18.02
9, 16, 17, 18
22
1.76 (s)
11.2
9, 10, 11
23
1.38 (s) ax
20.1
5, 6, 7
24
1.21 (d, 7.2)
12.7
1, 2, 3
o
b
Spectrum was recorded in DMSO-d6 at 25 C (500 MHz), Assignments were based
on HMQC and HMBC data.
204
1
H, 13C NMR, g-COSY, HMBC and ROESY data of compound 35
O
O
OH
H
Rel
O
1
a
H
O
Compound 35
C
gg-HMBCa
13 b
ROESYa
CO
SYa
1
-
177.6
-
-
-
2
2.70 (m)
42.7
3,
-
-
24
3
4.18 (dd)
81.0
3, 4
1, 2, 24
5, 24
4
1.83 (m)
23.3
4, 5
6
-
5
1.71 (m)
31.8
5, 4
3, 4, 6, 22
6
-
80.0
-
-
-
7
1.55
37.8
8
6, 8, 9
-
1.71 (m)
6, 8, 9, 20
8
2.30 (t, 9)
22.9
7
6, 7, 9, 10, 17
21, 23
9
-
167.9
7
-
-
10
-
130.1
-
-
-
11
-
200.3
-
-
-
12
2.37 (dd, 17.4, 35.2
18
11, 13, 14, 17, 18, 20, 21
17.4)
19
2.51 (dd, 17.4,
10, 11, 13, 14, 17,
3.6)
18, 19
13
-
41.1
14
1.20, 1.48
41.
15
1.62
18.6
1.70
16
1.36
-
-
19
15, 20
14,
-
16
35.8
15
205
9, 17, 21
8
1.96
17
-
41.3
18
1.70 (dd, 3.6, 50.3
17, 18
8, 21
-
-
-
12
9, 11, 12, 13, 14, 16, 19
14.4)
17, 19, 20, 21
19
0.90 (d, 5.4)
33.0
-
13, 14, 18, 20
20
0.93(d, 5.4)
21.3
-
13, 14, 18, 19
21
1.09 (s)
18.1
-
9, 16, 17, 18
12b,14, 16,
8, 12a, 15,
20
22
1.77 (s)
11.2
-
9, 10, 11
8,
23
1.36 (s)
20.6
-
5, 6, 7
5, 7
24
1.31 (d, 7.2)
13.4
2
1, 2, 3
3
a
Spectrum was recorded in DMSO-d6 at 25oC (500 MHz), b Assignments were based
on HMQC and HMBC data.
206
APPENDIX 3
A3.1
List of plant and marine sponge extracts used for the spiking experiment in
Chapter 6
A3.2
No
Sample ID
Family
Genus
Species
1
QID6000207
n/a
clavelina
cylyndrica
2
QID6000212
n/a
clavelina
cylyndrica
3
QID6000228
n/a
clavelina
pseudobau
4
QID6003649
clavelinidae
clavelina
cylindrica
5
QID024144
ranunculaceae
clematis
armandi fr.
6
QID024189
ranunculaceae
clematis
armandi fr.
7
QID027428
ranunculaceae
clematis
loureiana
8
QID101150
ranunculaceae
anemone
hupehensis
9
QID101151
ranunculaceae
anemone
hupehensis
10
QID101155
ranunculaceae
clematis
parviloba
11
QID2312811
ranunculaceae
clematis
finetiana
12
QID2312812
ranunculaceae
clematis
crassifolia
13
QID2312813
ranunculaceae
clematis
crassifolia
14
QID2313033
ranunculaceae
clematis
crassifolia
15
QID026298
ranunculaceae
clematis
armandii fr.
16
QID026384
ranunculaceae
clematis
armandii fr.
17
QID026462
ranunculaceae
clematis
armandii fr.
18
QID026468
ranunculaceae
clematis
armandii fr.
List of plant extracts used for screening experiment in Chapter 6
No
Sample ID
Order
Family
Genus
Species
1
QID6000207
n/a
n/a
clavelina
cylyndrica
2
QID6000212
n/a
n/a
clavelina
cylyndrica
3
QID6000228
n/a
n/a
clavelina
pseudobau
4
QID6003649
enterogona
clavelinidae
clavelina
cylindrica
5
QID024144
n/a
ranunculaceae
clematis
armandi fr.
6
QID024189
n/a
ranunculaceae
clematis
armandi fr.
7
QID027428
n/a
ranunculaceae
clematis
loureiana
8
QID101150
n/a
ranunculaceae
anemone
hupehensis
9
QID101151
n/a
ranunculaceae
anemone
hupehensis
207
10
QID101155
n/a
ranunculaceae
clematis
parviloba
11
QID2312811
<none>
ranunculaceae
clematis
finetiana
12
QID2312812
<none>
ranunculaceae
clematis
crassifolia
13
QID2312813
<none>
ranunculaceae
clematis
crassifolia
14
QID2313033
<none>
ranunculaceae
clematis
crassifolia
15
QID026298
n/a
ranunculaceae
clematis
armandii fr.
16
QID026384
n/a
ranunculaceae
clematis
armandii fr.
17
QID026462
n/a
ranunculaceae
clematis
armandii fr.
18
QID026468
n/a
ranunculaceae
clematis
armandii fr.
19
QID027425
n/a
ranunculaceae
clematis
filamentosa
20
QID027436
n/a
ranunculaceae
clematis
trullifera
21
QID101156
n/a
ranunculaceae
clematis
meyeniana
22
QID027427
n/a
ranunculaceae
clematis
loureiana
23
QID027434
n/a
ranunculaceae
clematis
trullifera
24
QID100771
n/a
ranunculaceae
clematis
apiifolia
25
QID101153
n/a
ranunculaceae
ranunculus
cantoniens
26
QID101154
n/a
ranunculaceae
ranunculus
cantoniens
27
QID002326
n/a
ranunculaceae
clematis
n/a
28
QID002329
n/a
ranunculaceae
clematis
n/a
29
QID002330
n/a
ranunculaceae
clematis
n/a
30
QID009536
n/a
ranunculaceae
clematis
n/a
31
QID009949
n/a
ranunculaceae
ranunculus
n/a
32
QID018645
n/a
ranunculaceae
ranunculus
n/a
33
QID018647
n/a
ranunculaceae
ranunculus
n/a
34
QID018708
n/a
ranunculaceae
ranunculus
n/a
35
QID025563
n/a
ranunculaceae
ranunculus
n/a
36
QID025583
n/a
ranunculaceae
clematis
n/a
37
QID031946
n/a
ranunculaceae
ranunculus
n/a
38
QID6000795
n/a
ranunculaceae
n/a
n/a
39
QID001799
n/a
rutaceae
leionema
n/a
40
QID001574
n/a
rutaceae
leionema
n/a
41
QID032421
n/a
rutaceae
leionema
n/a
42
QID001796
n/a
rutaceae
leionema
n/a
43
QID032183
n/a
rutaceae
leionema
n/a
44
QID1994728
n/a
rutaceae
leionema
n/a
45
QID009091
n/a
rutaceae
leionema
n/a
46
QID009109
n/a
rutaceae
leionema
n/a
47
QID032423
n/a
rutaceae
leionema
n/a
208
48
QID032431
n/a
rutaceae
leionema
n/a
49
QID008840
n/a
rutaceae
leionema
n/a
50
QID001763
n/a
rutaceae
leionema
n/a
51
QID001800
n/a
rutaceae
leionema
n/a
52
QID000555
n/a
strychnaceae
strychnos
n/a
53
QID000606
n/a
strychnaceae
strychnos
n/a
54
QID003564
n/a
strychnaceae
strychnos
n/a
55
QID003568
n/a
strychnaceae
strychnos
n/a
56
QID006371
n/a
strychnaceae
strychnos
n/a
57
QID006381
n/a
strychnaceae
strychnos
n/a
58
QID006390
n/a
strychnaceae
strychnos
n/a
59
QID006392
n/a
strychnaceae
strychnos
n/a
60
QID010866
n/a
strychnaceae
strychnos
n/a
61
QID010872
n/a
strychnaceae
strychnos
n/a
62
QID023945
n/a
strychnaceae
strychnos
n/a
63
QID024011
n/a
strychnaceae
strychnos
n/a
64
QID024101
n/a
strychnaceae
strychnos
n/a
65
QID024110
n/a
strychnaceae
strychnos
n/a
66
QID024406
n/a
strychnaceae
strychnos
n/a
67
QID025601
n/a
strychnaceae
strychnos
n/a
68
QID025605
n/a
strychnaceae
strychnos
n/a
69
QID032378
n/a
strychnaceae
strychnos
n/a
70
QID032384
n/a
strychnaceae
strychnos
n/a
71
QID032386
n/a
strychnaceae
strychnos
n/a
72
QID032387
n/a
strychnaceae
strychnos
n/a
73
QID5866362
<none>
strychnaceae
strychnos
<none>
74
QID5866368
<none>
strychnaceae
strychnos
<none>
75
QID5866373
<none>
strychnaceae
strychnos
<none>
76
QID1989853
n/a
strychnaceae
strychnos
n/a
77
QID2165974
n/a
strychnaceae
strychnos
n/a
78
QID016842
enterogona
clavelinidae
clavelina
australis
79
QID015499
<none>
loganiaceae
strychnos
<none>
80
QID021428
n/a
ranunculaceae
clematis
clemasie
81
QID024719
<none>
ranunculaceae
clematis
<none>
82
QID028308
n/a
ranunculaceae
clematis
sp.
83
QID028568
n/a
ranunculaceae
clematis
sp.
84
QID022503
n/a
asteraceae
peucedanum
decursivun
85
QID022510
n/a
asteraceae
peucedanum
decursivun
209
210

Thesis (Vu_2009_02Thesis)

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