Analysis of Copper in PDB files ANALYSIS OF COPPER IN PDB

Transcription

Analysis of Copper in PDB files
ANALYSIS OF COPPER IN PDB FILES
Thesis presented to Escola Superior de Biotecnologia of the Universidade Católica Portuguesa to fulfill
the
requirements of Master of Science degree in Bioinformatics
by
Joana Pinto
July 2009
Sumário
A determinação de estruturas de proteínas tem sido um importante marco no desenvolvimento das
ciências biológicas, um dos métodos usados para a sua concretização é a cristalização por raio-X,
embora esta técnica seja bastante fidedigna, ficheiros PDB tendem a apresentar bastantes erros devido
ao facto dos cristalógrafos não conseguirem observar a diferença entre certos átomos, e certamente que
este facto afecta negativamente a análise de estruturas de proteínas. Ao recorrer à validação de ficheiros
PDB, é possível corrigir estes artefactos gerados pela cristalização, de modo a que as estruturas de
proteínas se tornem cada vez mais precisas, seguindo esta directriz, o ponto fulcral deste projecto centrase no estudo de iões cobre em proteínas, a análise do ambiente que envolve estes iões metálicos
fornece um entendimento claro acerca de potenciais erros nas estruturas.
Os programas WHAT IF e YASARA foram usados para realizar uma análise exaustiva de ficheiros PDB
com iões cobre com uma resolução melhor que 2,0 Å. O uso de ambos os programas permitiu a
visualização dos iões e a sua interacção com os seus ligandos, bem como a sua geometria.
A maioria dos iões cobre examinados nos ficheiros PDB apresenta uma geometria tetraédrica, quer para
Cu + quer para Cu2+, a combinação de ligandos mais comum são duas Histidinas, uma Cisteína, e uma
Metionina. Quando analisadas e comparadas no mesmo gráfico, as estruturas de todos os iões cobre I e
cobre II com geometria tetraédrica regular, não foi visível qualquer diferença.
No final deste projecto, foi possível concluir, com base nos ficheiros PDB analisados, que não há
diferenças significativas entre as estruturas dos iões Cobre reduzidos e oxidados, estes centros activos
tendem a manter as mesmas distâncias entre os iões e os ligandos, qualquer que seja o seu estado de
oxidação. No entanto, se alguma diferença existe ela será menor que o erro esperado pela determinação
de estruturas através de cristalização por raio-X. No que às proteínas de cobre diz respeito, existiu nas
duas últimas décadas um grande vazio científico, durante o qual não existiu qualquer publicação que
descrevesse um novo conhecimento acerca destas proteínas, contudo apesar de actualmente existirem
novas técnicas e ter sido possível avançar nesta área, continua a existir uma carência no que toca a
dados de alta qualidade. Fizeram-se no passado suposições baseadas em más estruturas, assim sendo,
certamente que muitas destas suposições estão erradas.
Abstract
Determination of protein structures has been an important mark in the development of biological sciences,
one of the methods used to achieve it is X-Ray Crystallography, but although this technique is very
reliable, PDB files can present gross errors, due to the fact that crystallographers cannot observe the
difference between certain atoms, and surely this adversely affects the protein structure analyses. Using
PDB files validation, it’s often possible to correct these crystallography artifacts so that protein structures
become more and more accurate, using this as a guideline the main focus of this project has been to
study Copper ions in proteins, analyzing the environment surrounding these metal ions provides a clear
understanding of potential errors in the structures.
Programs WHAT IF and YASARA were used to perform an exhaustive analysis through all the Copper
containing PDB files with a resolution better than 2.00 Å. The use of both softwares allowed the
visualization of the ions interacting with its ligands, as well as its geometry.
The majority of the Copper ions examined in the PDB files presented a tetrahedral geometry arrangement,
either for Copper I as for Copper II, and the far most common combination of ligands binding to the metal
ions are two Histidines, one Cysteine, and one Methionine. When analyzed and compared in the same
plot, all the regular tetrahedral Copper I and Copper II centers showed no differences in their structures.
By the end of this project, it was possible to conclude, based on the PDB files analyzed, that there are no
significant differences between the reduced and oxidized copper centers; these active sites tend to
maintain the same distances between the ions and the ligands whatever its oxidation state is. However, if
any differences exist, they are smaller than the expected error in the X-Ray structure determination.
Concerning to Copper proteins, there has been a science gap of about two decades, during when there
wasn’t any publication describing novel copper knowledge about these proteins, although nowadays there
are new techniques and it has been possible to advance in this area, there is still a lack of high quality
data. In the past there were some assumptions made relying in bad structures, and by being so, these
conclusions are certainly wrong.
.
Contents
1 Introduction........................................................................................................ 1
1.1 Purpose of PDB files validation ..................................................................................................... 1
1.2 What is the PDB............................................................................................................................. 1
1.3 Ions ................................................................................................................................................. 2
1.3.1 Copper....................................................................................................................................... 2
1.4 Type I Copper proteins ................................................................................................................... 2
1.4.1 Plastocyanin as an example of type I Copper Centers.......................................................... 3
1.5 Type II Copper proteins .................................................................................................................. 4
1.5.1 PHM as an example of type II Copper .................................................................................... 4
1.6 Type III Copper proteins ................................................................................................................. 6
1.6.1 Hemocyanin as an example of type III Copper ..................................................................... 6
+
2+
1.7 Cu versus Cu .............................................................................................................................. 8
1.8 Molecular Geometry ....................................................................................................................... 9
2 Materials and Methods ..................................................................................... 10
2.1 PDB files .......................................................................................................................................... 10
2.2 Introduction to WHAT IF ................................................................................................................. 10
2.3 Introduction to YASARA ................................................................................................................. 12
3 Results and Discussion ................................................................................... 14
3.1 Cu + analysis .................................................................................................................................... 14
2+
3.2 Cu analysis ................................................................................................................................... 15
3.3 Regular tetrahedrals for Cu+ and Cu2+ .......................................................................................... 17
3.4 Copper Center Distances Plot ....................................................................................................... 23
3.5 Flipping Histidines........................................................................................................................... 25
3.6 Wrong previous studies .................................................................................................................. 27
4 General Conclusions ........................................................................................ 28
5 Future Work....................................................................................................... 29
6 Bibliography...................................................................................................... 30
ANALYSIS OF COPPER IN PDB FILES
Thesis presented to Escola Superior de Biotecnologia of the Universidade Católica Portuguesa to fulfill
the
requirements of Master of Science degree in Bioinformatics
by
Joana Pinto
under the supervision of
Prof. Dr. Gert Vriend
July 2009
Acknowledgements
First of all, I would like to thank my parents for all the support, all the confidence and for having provided
me this experience; my brothers and sister, for taking care of the old guys while I was gone; my other half,
for trusting in my capacities and for not letting me quit.
To Ana, nothing better than: “Together in electric dreams, because the friendship that you gave, has taught
me to be brave”.24 hours per day for 5 months, a lot of tragic however funny stories.
To the students and staff at the Centre for Molecular and Biomolecular Informatics, thank you for making
my stay so pleasant, I loved it!
Last but not least, Gert Vriend, first of all thank you for letting me work with you and for showing me what
bioinformatics really is, and for all the hospitality and kindness.
Thank you all for making my stay in The Netherlands something unforgettable.
1 | Introduction
1.1 Purpose of PDB files Validation
Some bioinformatics areas rely on protein structures and their work is done using Protein Data Bank
(PDB) files, for some of these areas, like structural biology, homology modeling and drug design it’s
fundamental that three dimensional macromolecular coordinates are as accurate as possible, in order to
get the answers to their scientific questions in the most reliable way possible
[12]
. During the deposition of
data in the Protein Data Bank, there is a validation process, the software used in this validation reports
numerous outliers in protein’s geometry and backbone torsion angles
[3]
, there are also other potential
problems found which are recorded by external validation sites, e.g. PDBREPORT [13].
In order to solve the poor quality problems of some PDB files, new refinement methods have arise, like
PDB_REDO
[12]
, these new refinement techniques are based in the latest improvements in X-Ray
Crystallography methods, this means that an already existing structure will be calculated again but with
new crystallographic methods, only existing after the structure was first deposited
[13]
. These refinement
methods were applied in a large scale to PDB entries, improving a large number of structures
[12]
, such
methods rely on improved software and better knowledge of protein structure – and this is the context in
which this project is inserted.
1.2 What is the PDB?
PDB stands for Protein Data Bank, which is a databank that stores three dimensional coordinates for
protein structures, it started in 1971 and has been growing exponentially in the past few years, there were
about 50.277 entries (including proteins, nucleic acids, nucleic acid-protein complexes, and a few other
molecules) by April of 2008, nowadays, this number is about 57944. Both NMR spectroscopy and X-Ray
Crystallography data can be stored in the PDB. The PDB is not a curated database, but a databank, so
errors won’t be corrected before the release of the coordinates and this is the reason why it is so frequent
to find errors in the structures. These errors can be found, as said before, in PDBREPORT. This database
stores the structural problems in PDB files, solved either by X-Ray crystallization or NMR techniques, the
analysis of the PDB files are done using WHAT_CHECK
[11]
.
1.3 Ions
Ions are atoms that have lost or gained electrons, this is why they present positive or negative net
charges, being also called cations and anions. Several ions can be found in proteins, such as Zinc, Iron,
and Copper, also Fluoride, Chlorine or Iodine. These ions can have different functions in the proteins
where they are inserted in, for instance, for the small zinc fingers domains the metal ion stabilizes their
[4]
DNA-binding regions, while Iron in Hemoglobin is essential to oxygen’s transportation .
This study will be focused in copper containing proteins, in which these metal ions can take part, for
example, in electron transfer, hydroxylation reactions and even oxygen transport.
1.3.1 Copper
Copper is an element with an atomic number of 29, a mass around 64 g.mol-1, and it’s a relatively
nonreactive ion that can be in its elemental form. It’s considered to be a transition metal thus as all the
other transition metals, copper has an incomplete d sub-shell
[16]
.
Contrarily to what could be expected,
2 9
copper’s electronic configuration is not [Ar] s d , but instead, an electron is removed from the 4s orbital to
completely fill the 3d orbital, so that its configuration will be [Ar] s 1d 10, due to this unpaired electron in the
4s orbital copper is considered to be a paramagnetic metal
[16]
.
Copper proteins can be classified and grouped according to their function – catalysis or electron transfer –
but also according to their metal center. Copper proteins are divided in three classes, according to the
copper center type: Type I, type II and type III [23]. It’s possible for a certain copper protein to have different
types of copper centers, for example, nitrite reductase possesses a type I and a type III center
[23]
, the
examples given in this introduction are the simplest possible, i.e., all the proteins described below possess
only one type of center.
1.4 Type I Copper Proteins
For type I center proteins, also known as blue copper proteins, usually a single copper ion binds to two
Histidines, one Cysteine and one Methionine
[23]
charge-transfer (LMCT) transition near 600nm
some examples of this class of proteins
copper proteins family
[16]
.
[23]
, their blue color results from an intense ligand-to-metal-
[1]
. Plastocyanin, Rusticyanin and Ascorbate oxidase are
. There are about fifty thousand proteins belonging to the blue
1.4.1 Plastocyanin as an Example of Type I Copper Centers
Plastocyanin is a monomeric copper-containing protein, with a molecular weight of around 10,5 Da and a
length of about 97-100 amino acids
[15]
which can be found in most higher plants. This protein contains a
single copper ion, located at a depth of 5 to 10 Å near one end of the molecule, and it's coordinated by
four residues: two Histidines, one Cysteine, and one Methionine.
Although Plastocyanin's molecular surface differs according to the different organisms, the copper binding
site is usually conserved and it’s said to present distorted tetrahedral geometry. The base of the
tetrahedron is constituted by two nitrogens from two Histidines – one of these Histidines is usually
exposed to the surface - and sulfur from Cysteine. At the top of the tetrahedron there is sulfur from
Methionine. The distortion of the tetrahedron is a consequence of the bond lengths between the metal ion
and the sulfur ligands; the distance Cu-SMet (~2,9Å) is bigger than the distance Cu-SCys (~2.1 Å)
[19]
. This
difference in the distances is believed to destabilize the oxidized form of the ion and to increase the redox
potential of the protein, which is required for electron transfer [10].
a)
b)
Figure 1: a) Plastocyanin, PDB file 1BXU b) Plastocyanin’s active site. Pictures made with YASARA [14].
Plastocyanin has a typical beta-barrel structure; it's located at the lumen of the thylakoid in chloroplasts
and plays an important role in photosynthesis by coupling photosystem II with photosystem I through the
shuttling of electrons from cytochrome b6f to P700 - electron transfer [9].
1.5 Type II Copper Proteins
In the type II center proteins, a single copper is usually binding to three Histidines and another ligand that
can be another Histidine, a water molecule
[23]
or even another residue. Some publications
[23]
reveal that
copper can also bind up to five residues. Proteins containing this kind of center usually don't present any
color. These centers usually occur on enzymes with oxidation or oxygenation functions. Peptidylglycine αHydroxylating Monooxygenase, Cu/Zn Superoxide dismutase and Amine oxidase are some examples of
proteins containing this class of copper centers.
1.5.1 Peptidylglycine α-Hydroxylating Monooxygenase as an example of Type II Copper Centers
Peptidylglycine α-Hydroxylating Monooxygenase (PHM) is the amino-terminal domain of a bifunctional
Peptidylglycine α-Amidating Monooxygenase (PAM) protein, which function is to catalyze the
hydroxylation of glycine α-carbon of peptidylglycine substrates
[17]
. PHM contains uncoupled binuclear
copper centers, namely CuA and CuB, cycling between the two oxidation states possible
[18]
.
This enzyme it's composed by two domains, domain I which is a beta-sandwich of two antiparallel betasheets containing three disulfide bridges and binding to the Cu A, and domain II, which is also a betasandwich domain also consisting of two antiparallel beta-sheets and one five-stranded mixed beta-sheet
containing not three but two disulfide bridges and binding to CuB [18].
The CuA center is coordinated by three nitrogens from Histidine residues and a water molecule, whereas
Cu B is coordinated by two nitrogens from Histidines, sulfur from a Methionine residue and also a water
molecule [2]. The two Copper centers are at a distance of about 11 Å from each other.
Figure 2: PHM, PDB file 1OPM, with both of its domains, domain I (left) and domain II (right). Pictures made with
YASARA [14].
a)
b)
Figure 3:.PHM, PDB file 1OPM. a) CuA active center, in this case, the water molecule isn’t visible. b) Cu B active center
with its four ligands, presents tetrahedral geometry. Pictures made with YASARA [14].
1.6 Type III Copper Proteins
Type III Copper centers are binuclear centers in which each of the two copper ions – Cu A and CuB - are
coordinated by three nitrogens from three Histidine residues and a molecule of Oxygen, these centers are
[8]
found in enzymes with oxygenase/oxidase function and also oxygen-transporting proteins . Hemocyanin,
Tyrosinase and Catechol oxidase are examples of proteins with type III copper centers.
1.6.1 Hemocyanins as an example of Type III Copper Centers
Hemocyanins, along with Tyrosinases and Cathecol Oxidases, are the simplest examples of type 3 copper
center containing proteins, despite the fact that these proteins have different physiological functions, they
all share the same copper center [26]. Hemocyanins vary in its structure according to the organism in which
they are present; however a general description can be made [7].
Hemocyanin (Hc) can be compared to Hemoglobin (Hb) since they both have an oxygen transport
function. On the contrary of Hb, Hemocyanin is found mostly in arthropods and mollusks
[6]
; it isn't
bounded to blood cells but suspended in the hemolymph and it's usually a large multi subunit protein. The
most important difference between these two oxygen carriers is that Hb has an iron-based active site,
while Hc has a copper-based active site. Hc is a rather poorer respiratory pigment than Hb. In the
deoxygenated state the protein is colorless, but once binding to oxygen, it appears with a pale blue color
[21]
.
Hemocyanin’s N-terminal domain is composed by several α helices, in fact the copper ions can be found
in this domain, and on the other hand, the C-terminal domain has an immunoglobulin-like sandwich
structure
[16]
. The copper center in this protein is formed by two copper ions coordinated by three Histidine
residues each, and binding to oxygen.
Figure 4: Hemocyanin, PDB file 1NOL, from an arthropod in the oxygenated state. The distance
between the two Copper ions is of about 3.6 Å. Picture made with YASARA [14].
a)
b)
Figure 5: Hemocyanin, PDB file 1OXY, from an arthropod a) Copper center of Hemocyanin and its surroundings b) Copper
center and its ligands. In the oxygenated state, the distance between the two Copper ions is of about 3.6 Å. Picture made
with YASARA [14].
1.7 Cu+ versus Cu2+
Copper has two stable oxidation states, cuprous (Cu +) and cupric (Cu2+); there is also another oxidation
state, Cu3+, which is extremely rare to find, due to the difficulty for biological ligands to stabilize it
[2]
.
Cuprous ions are less stable than cupric ions, therefore they are easily oxidized. The cuprous electronic
0
10
configuration is [Ar] 4s 3d , because electron’s first removal will happen from 4s orbital, and by having
this configuration with no unpaired electrons, cuprous is a diamagnetic ion.
0
9
On the other hand, cupric’s configuration is [Ar] 4s 3d due to the fact that the second electron is removed
2
from the 3d orbital, leaving an unpaired electron in the d x paramagnetic ion
2
y
orbital, and therefore cupric is a
[19]
.
Copper usually forms a metal complex, binding to surrounding atoms or molecules, in order to
characterize the type of complex formed it’s necessary to look at the geometry of it. The geometry will
depend on the nature and number of ligands binding to the metal.
The number of ligands is often referred to as coordination number, and depends on several factors like for
e.g. size, charge and electron configuration of the metal and the ligands. The donors that will act as
ligands to the metal can be soft or hard, Sulfur and Phosphorous are soft ligands and therefore have
preference for soft ions, on the contrary to Oxygen which is a hard donor that prefers binding to hard ions
[2]
. Nitrogen is somewhere in the middle of soft and hard donors, being less hard than oxygen. For copper,
the ligands and the coordination numbers may be affected according to the oxidation state of the ion.
Being the reduced state of copper more softer than the oxidized state, the soft donors tend to bind to Cu
increasing its redox potential, while hard donors bind easily to Cu
frequent coordination numbers are 2, 3 or 4 and 4, 5 or 6 for Cu
2+ [2]
.
2+ [2]
+
+
. It’s said that for Cu the most
1.8 Molecular Geometry
Figure 6: Types of molecular geometries found, according to the number of ligands and electron lone pairs [24].
Number
Geometry
Geometry
Geometry
Geometry
Geometry
of
with no lone
with one
with two
with three
with four
Ligands
electron pairs
electron lone
electron lone
electron lone
electron lone
pair
pair
pair
pair
2
Linear
3
4
Trigonal Planar
T - Shape
Tetrahedral
Trigonal pyramid
Angular
Trigonal bi-pyramid
Seahorse
T shape
Linear
Octahedral
Square pyramid
Square planar
T shape
5
6
Figure 6 shows the different types of geometries that can be found in molecules.
Linear
2 | Materials and Methods
2.1 PDB files
The PDB files containing copper were obtained using the PDB scanning WHAT IF menu that was written
especially for this project. These files were manually divided in three groups, according to the oxidation
+
state of the copper ions, the clearly Cu , the clearly Cu
2+
ions and also the ones that aren’t clearly any of
these. This indetermination about the oxidation state can be due to the same protein having more than
one copper ion, and these multiple ions having different oxidation states, in these cases is difficult to
determine which one is which.
+
For a total number of 114 Cu containing files, only 35 were analyzed, and for Cu
2+
there were 562 files,
but only 321 were analyzed; there were about 16 files for the non-clear copper ions, these were also
analyzed. The discarded PDB files were either solved by NMR spectroscopy or they had a resolution
worse than 2.0 Å. Why this limit resolution? Because at a resolution between 1.5 Å and 2.0 Å, the
probability of having wrong rotamers in the structure is very low and small errors can normally be
detected.
2.2 Introduction to WHAT IF
WHAT IF
[25]
was written by Gert Vriend, and it started on December of 1987 in Groningen, The
Netherlands. This computer program was written to contribute to protein engineering, drug design,
molecular dynamics studies and Homology Modeling. It has been used on protein structures correction
and validation, since it provides a flexible environment for manipulating and analyzing proteins, nucleic
acids and their interactions.
WHAT IF was used in this project in order to analyze the copper ions in their environment in the protein,
since it provides a simple way to see the geometry of copper’s ligands.
For both Cu+ and Cu2+ PDB files, WHAT IF performed all calculations, and for each copper ion in each
PDB file it returned several results, such as: which atom (N, O, S) of which residue was binding to copper;
the number of residues acting like a ligand; distance between each ligand and the metal ion; torsion
angles; RMS distances from planarity for the different planar groups in the structure; the degree of body
off-Centerness, i.e. the distance of the ion to the center of the “geometry box”; and also the prediction of
the geometry for the ion, having into account the number of ligands to Copper and the values of the
several calculations described above.
All these calculations have been subject to parameters, for example:
- For planarity RMS values, the closest to zero, the more flat is the plane. So, for instance, when
WHAT IF is predicting if a certain ion could have a square planar geometry, its decision will be
based in this calculation;
- For the degree of body off-Centerness, for values between 0 and 0.60, the ion is considered to
be well centered inside the geometry-box;
According to the results obtained for both Cu+ and Cu2+, all the PDB files containing copper with four
ligands were analyzed again in WHAT IF. This time, the objective was to look at the ion and its
surroundings and, according also to the previous calculations, check the geometry and decide if the
structure was regular or not, in this case, check which tetrahedrals were regular and which were not.
WHAT IF was especially updated for this analysis, by changing one of the parameters. This parameter is
SKPNOO; it was altered to “allow” the ion to bind to nitrogen, oxygen and sulfur, because these are the
favorite donors for Copper. The option GRSION was also used to build lines around the Copper, and from
the Copper to each ligand, forming a geometry-box around the ion, also it performed symmetry
calculations in order to increase, if possible, the number of ligands of each copper ion. The geometry box
allows the user to check in a pleasant way if the ion is well positioned, using this mechanism and the
values obtained before - such as degree of body off-centeredness – it’s possible to do a thorough analysis
of the ion’s position and surroundings.
a)
b)
Figure 7: Example of geometry-box with a Copper ion binding to two Histidines, one Cysteine and a Methionine. Only
side chains are shown. The yellow lines connect the ligands atoms. Copper is shown as a green cross. a) top view
b) side view
In Figure 7, the ion is nicely inserted inside of the geometry box, but in the case below the copper ion is
barely inside it.
a)
b)
Figure 8: Example of geometry-box with a Copper ion binding to four nitrogens from Histidine residues. Only side
chains are shown and copper is shown as a green cross. It’s visible that this ion is barely inside the box.
Once knowing which the regular tetrahedral copper ions were, a plot - shown in the results section, Figure
10 - was calculated and all these structures were superposed in WHAT IF in order to calculate the
average positions for Cu + and Cu2+ and their ligands, with the objective of understanding the differences
between Cu + and Cu 2+ structures. However, only the regular Cu + and Cu 2+ ions with the ligands
arrangement of two Histidines, Cysteine, and Methionine were analyzed in this plot, due to the fact that
this is the most ordinary ligands arrangement.
2.3 Introduction to YASARA
YASARA
[14]
has been developed since 1993, it is a molecular-graphics, -modeling and -simulation
program for Windows, Linux and Mac OS X. It’s an intuitive program with a friendly interface with
photorealistic graphics. YASARA is also prepared to perform Molecular Dynamics and docking in small
molecules, and also create force fields.
Figure 9: Example of a Hydrolase, PDB file 2QXJ. The α-helices, the β-sheets and hydrogen bonds are represented.
Picture made with YASARA [14] .
In this project, the Twinset version was used. The twinset version consists in a combination of WHAT IF
and YASARA. WHAT IF inherits from YASARA the user’s interface, graphics, macro language, and so on;
this allows WHAT IF to be of easier access either in Linux as Windows.
3 | Results and Discussion
3.1 Cu+ Analysis
+
Notice that, as mentioned before, for a total number of 114 Cu containing files, only 35 files were
analyzed. In this section, Tables 1 – 4 show several statistics regarding the Cu + ions analyzed, numbers
relate to copper ions and not to PDB files. Also notice that a single PDB file often has multiple copper ions,
either to Cu+ as Cu 2+.
For Cu +, the most often seen number of ligands binding to the metal is four, Table 1, contrarily to other
studies, this project revealed that for Cu + coordination number 4 is indeed the most common, but
coordination numbers 2 and 3 are very rarely seen, in fact there are more ions with 5 ligands than with 2
and 3 together.
Also the preferred geometry for the ions with this coordination number was checked, Table 2, the most
often geometry is a tetrahedral configuration, 24 of a total of 37 copper ions have a tetrahedral geometry.
Being the tetrahedral geometry the most often seen, the following analysis will rely only in the tetrahedrical
copper ions.
Table 1: Number of Cu+ ions for each possible number of ligands.
Number of ligands
Number of Copper I ions
2
1
3
11
4
37
5
29
6
0
7
0
8
0
Table 2: Possible geometries for all the Cu+ ions binding to four ligands.
Geometry
Number of Copper ions
Tetrahedral
24
Other configurations
13
On Table 3, there are the ligands arrangements binding to each tetrahedral Cu+, being the arrangement of
two Histidines, one Methionine, and one Cysteine, the most common ligands arrangement followed by
four Histidine residues.
+
Table 3: Arrangements of ligands found in all the 24 tetrahedral Cu ions.
Ligands seen in tetrahedrals
2 Histidines, 1 Methionine, 1 Cysteine
14
2 Histidines, 1 Methionine, 1 Water
1
3 Methionine, 1 SCN
1
4 Histidines
7
4 Cysteines
1
2+
3.2 Cu Analysis
As said before, for Cu2+ there were 562 files, but only 321 were analyzed. In this section, Tables 5 – 8
show several statistics regarding the Cu2+ ions analyzed.
For Cu 2+, as for Cu+, the most often seen number of ligands binding to the metal is four, as seen in Table
4.Accordingly to previous studies, the most common coordination numbers are 4 and 5, although for
coordination number 6, there are fewer occurrences than for coordination number 3.
For all the 321 files analyzed, there are 331 copper ions with a tetrahedral geometry, as seen in Table 5,
and on the contrary of Copper I, there were a few square planar structures, although this number is not
significant. Being the tetrahedral geometry the most often seen, the following analysis will rely only in the
tetrahedrical copper ions
Table 4: Number of Cu 2+ ions for each possible number of ligands.
Number of ligands
Number of Copper II ions
2
4
3
45
4
384
5
231
6
30
7
25
8
3
Table 5: Possible geometries for all the Cu2+ ions binding to four ligands.
Type of Geometry
Tetrahedral
331
Square planar
8
Other configuration
45
On Table 6, there are the ligands arrangements binding to the tetrahedral oxidized Copper, being the
arrangement of two Histidines, one Methionine and one Cysteine, the most common ligands arrangement
followed by 3 Histidines and a water molecule.
Table 6: Arrangements of ligands found in all the tetrahedral Cu 2+ ions.
Ligands seen in tetrahedrals
2 Histidines, 1 Cysteine, 1 Methionine
210
2 Histidines, 1 Cysteine, 1 Glutamine
4
2 Histidines, 1 Cysteine, 1 Glutamic Acid
5
2 Histidines, 1 Cysteine, 1 Threonine
2
2 Histidines, 1 Cysteine, 1 Water
1
2 Histidines, 1 Methionine, 1 Water
4
2 Histidines, 1 Water, 1 Tyrosine
1
2 Histidines, 2 Waters
1
3 Histidines, 1 Aspartic Acid
2
3 Histidines, 1 Water
69
3 Histidines, 1 Cysteine
4
3 Histidines, 1 Tyrosine
2
3 Histidines, 1 TPQ
4
3 Histidines, 1 FMT
2
4 Histidines
19
3 Waters, 1 Histidine
1
All these statistics show that there isn’t enough data available, it’s possible to see that there is a certain
geometry that is more often seen, and also that there is a preferred arrangement of ligands, but all these
results rely in too few data. And also, the dataset used is not cleared, for example, there is a large number
of Plastocyanin’s structures and Nitrite Reductase that contains type I and type II copper centers, while
there is a lack of other copper protein’s structures.
3.3 Regular tetrahedrals for Cu+ and Cu2+
Either for the reduced and oxidized copper, some ions are regular tetrahedrals; these ions belong to the
+
2+
several PDB files shown on Table 7, for Cu and Table 9, for Cu . For each PDB file, there is the number
of regular copper ions on the protein, the name of the protein itself, and also some of the Regularity
Parameters used to distinguish the regular ones.
For all the 24 Cu + tetrahedrals, 14 of these were considered regular and they are spread over 9 PDB files,
Table 7. On Table 8, there are the ligands arrangements for the regular tetrahedral Cu+ ions. For Cu+, 13
of the 14 regular ions will be analyzed further on (Table 12), due to its ligands arrangement of two
Histidines, Cysteine and Methionine.
Table 7: Regular tetrahedrals for Copper I.
PDB file
Number of
Protein
Copper ions in
Class/Family
the file
Regularity Parameters
Cu Inside
Degree of Off
Geometry Box
Centerness
1a8z
1
Rusticyanin
Yes
0.46
1f56
3
Plantacyanin
Yes
0.47, 0.47, 0.29
1jxg
1
Plastocyanin
Yes
0.44
1sfh
2
Amicyanin
Yes
0.51, 0.50
2bzc
1
Plastocyanin
Yes
0.53
2cak
1
Rusticyanin
Yes
0.53
2gi0
2
Azurin
Yes
0.46, 0.44
3cvd
2
Plastocyanin
Yes
0.33, 0.29
3dso
1
---------
Yes
0.21
Table 8: Arrangements of ligands found in regular tetrahedral Cu + ions.
Ligands seen in regular tetrahedrals
2 Histidines, 1 Cysteine, 1 Methionine
13
3 Methionine, 1 SCN
1
From 331 Cu
2+
tetrahedrals, 215 of them were considered regular tetrahedrals; these regular copper ions
are spread over 123 PDB files, Table 9. On Table 10, there are the ligands arrangements for the regular
2+
2+
tetrahedral Cu . For Cu , 149 of the 215 regular tetrahedrals will be analyzed further on (Table 12), due
to its ligands arrangement of two Histidines, Cysteine and Methionine.
Table 9: Regular tetrahedrals for Copper II.
Number of
Protein
PDB
Copper ions
Class/Family
file
in the file
Cu Inside
Degree of Off
Geometry
Centerness
Box
1a4a
4
Azurin
Yes
0.13, 0.09, 0.14, 0.23
1aan
1
Amicyanin
Yes
0.50
1aoz
1
Ascorbate Oxidase
Yes
0.50
1aq8
3
Nitrite Reductase
Yes
0.18, 0.19, 0.20
1as6
3
Nitrite Reductase
Yes
0.22, 0.32, 0.23
1as7
3
Nitrite Reductase
Yes
0.29, 0.28, 0.34
1as8
3
Nitrite Reductase
Yes
0.28, 0.31, 0.24
1azv
1
Cu/Zn Superoxide Dismutase
Yes
0.37
1bq5
1
Nitrite Reductase
Yes
0.40
1bqk
1
Pseudoazurin
Yes
0.42
1bqr
1
Pseudoazurin
Yes
0.45
1bxu
1
Plastocyanin
Yes
0.54
1bxv
1
Plastocyanin
Yes
0.49
1byo
1
Plastocyanin
Yes
0.45
1byp
1
Plastocyanin
Yes
0.48
1e30
1
Rusticyanin
Yes
0.43
1eso
1
Yes
0.49
1et5
2
Nitrite Reductase
Yes
0.17, 0.07
1et8
1
Nitrite Reductase
Yes
0.26
1gs7
1
Nitrite Reductase
Yes
0.30
1gs8
2
Nitrite Reductase
Yes
0.30, 0.11
1gy1
2
Rusticyanin
Yes
0.45, 0.45
1hau
1
Nitrite Reductase
Yes
0.40
1ibb
1
Yes
0.45
1iuz
1
Plastocyanin
Yes
0.38
1j9q
3
Nitrite Reductase
Yes
0.17, 018, 0.15
1j9s
3
Nitrite Reductase
Yes
0.14, 0.17, 0.14
1jer
1
Stellacyanin
Yes
0.33
1juh
4
Dioxygenase
Yes
0.27, 0.28, 0.20, 0.23
1kbv
4
Nitrite Reductase
Yes
0.28, 0.32, 0.29, 0.28
1kcb
1
Nitrite Reductase
Yes
0.20
1kdi
1
Plastocyanin
Yes
0.48
1kdj
1
Plastocyanin
Yes
0.47
1l9o
3
Nitrite Reductase
Yes
0.17, 0.18, 0.13
1l9q
3
Nitrite Reductase
Yes
0.18, 0.19, 0.16
1l9p
3
Nitrite Reductase
Yes
0.16, 0.17, 0.17
1l9r
3
Nitrite Reductase
Yes
0.18, 0.21, 0.18
1l9s
3
Nitrite Reductase
Yes
0.18, 0.21, 0.18
1l9t
3
Nitrite Reductase
Yes
0.18, 0.20, 0.17
1mzy
2
Nitrite Reductase
Yes
0.20, 0.23
1mzz
4
Nitrite Reductase
Yes
0.18, 0.08, 0.40, 0.12
1n70
1
Nitrite Reductase
Yes
0.21
1ndt
1
Nitrite Reductase
Yes
0.35
1nic
1
Nitrite Reductase
Yes
0.21
1nie
1
Nitrite Reductase
Yes
0.22
1nif
1
Nitrite Reductase
Yes
0.20
1npj
3
Nitrite Reductase
Yes
0.09, 0.11, 0.22
1npn
3
Nitrite Reductase
Yes
0.22, 0.18, 0.16
1oac
2
Amine Oxidase
Yes
0.31, 0.33
1oe1
2
Nitrite Reductase
Yes
0.23, 0.06
1oe2
1
Nitrite Reductase
Yes
0.31
1oow
1
Plastocyanin
Yes
0.41
1opm
1
Yes
0.29
1ov8
1
Peptidylglycine α-hydroxylating
monooxygenase
Auracyanin
Yes
0.54
1paz
1
Pseudoazurin
Yes
0.39
1phm
1
Yes
0.20
1plc
1
monooxygenase
Plastocyanin
Yes
0.22
1pmy
1
Pseudoazurin
Yes
0.40
1pnc
1
Plastocyanin
Yes
0.42
1pnd
1
Plastocyanin
Yes
0.35
1pza
1
Pseudoazurin
Yes
0.46
1qhq
1
Auracyanin
Yes
0.53
1rcy
1
Rusticyanin
Yes
0.49
1rzp
5
Nitrite Reductase
Yes
0.16, 0.16, 0.18, 0.12 ,
0.09
1sfd
2
Amicyanin
Yes
0.43, 0.41
1sjm
3
Nitrite Reductase
Yes
0.16, 0.18, 0.16
1srd
1
Yes
0.08
1tef
2
Plastocyanin
Yes
0.44 , 0.32
1teg
1
Plastocyanin
Yes
0.37
1ui7
1
Oxidase
Yes
0.62
1wa0
2
Nitrite Reductase
Yes
0.44, 0.08
1wa1
1
Nitrite Reductase
Yes
0.36
1wa2
1
Nitrite Reductase
Yes
0.39
1wae
1
Nitrite Reductase
Yes
0.34
1yjk
1
Yes
0.07
1zdq
3
Peptidylglycine α-Amidating
monooxygenase
Nitrite Reductase
Yes
0.16, 0.17, 0.20
1zds
5
Nitrite Reductase
Yes
0.15, 0.10, 0.11, 0.12,
0.16
1zia
1
Pseudoazurin
Yes
0.37
1zib
1
Pseudoazurin
Yes
0.46
1zv2
1
Nitrite Reductase
Yes
0.15
2a3t
1
Nitrite Reductase
Yes
0.26
2afn
4
Nitrite Reductase
Yes
0.24, 0.34, 0.23, 0.37
2bp0
2
Nitrite Reductase
Yes
0.10, 0.18
2bp8
2
Nitrite Reductase
Yes
0.09, 0.17
2bw4
1
Nitrite Reductase
Yes
0.20
2bw5
1
Nitrite Reductase
Yes
0.18
2bwd
1
Nitrite Reductase
Yes
0.17
2bwi
1
Nitrite Reductase
Yes
0.18
2bz7
1
Plastocyanin
Yes
0.53
2cbp
1
Phytocyanin
Yes
0.36
2cfd
1
Oxidase
Yes
0.60
2cj3
2
Plastocyanin
Yes
0.44, 0.45
2cwv
1
Oxidase
Yes
0.67
2d1w
1
Oxidase
Yes
0.61
2dws
1
Nitrite Reductase
Yes
0.18
2dwt
1
Nitrite Reductase
Yes
0.21
2gc4
4
Amicyanin
Yes
0.22, 0.29, 0.21, 0.27
2idt
1
Amicyanin
Yes
0.31
2j56
2
Amicyanin
Yes
0.37, 0.45
2jkw
2
Pseudoazurin
Yes
0.35, 0.43
2jl0
4
Nitrite Reductase
Yes
0.32, 0.11, 0.32 , 0.08
2jl3
2
Nitrite Reductase
Yes
0.31, 0.34
2nrd
2
Nitrite Reductase
Yes
0.20, 0.17
2oov
1
Amine Oxidase
Yes
0.16
2q5b
3
Plastocyanin
Yes
0.30, 0.25, 0.27
2qxj
1
Hydrolase
Yes
0.23
2sod
2
Yes
0.22, 0.17
2ux6
1
Pseudoazurin
Yes
0.20
2ux7
1
Pseudoazurin
Yes
0.33
2uxf
1
Pseudoazurin
Yes
0.23
2uxg
1
Pseudoazurin
Yes
0.40
2vm3
2
Nitrite Reductase
Yes
0.38, 0.10
2vm4
2
Nitrite Reductase
Yes
0.36, 0.12
2vw4
4
Nitrite Reductase
Yes
0.34, 0.34, 0.12, 0.09
2vw6
3
Nitrite Reductase
Yes
0.31, 0.11, 0.10
2vw7
4
Nitrite Reductase
Yes
0.33, 0.35, 0.10, 0.13
2yx9
1
Oxidase
Yes
0.58
3cqp
1
Yes
0.27
3phm
1
Yes
0.19
3sod
4
monooxygenase
Yes
0.27, 0.27, 0.27, 0.27
5pcy
1
Plastocyanin
Yes
0.44
7pcy
1
Plastocyanin
Yes
0.47
8paz
1
Pseudoazurin
Yes
0.37
Table 10: Arrangements of ligands found in regular tetrahedral Cu2+ ions.
Ligands seen in regular tetrahedrals
2 Histidines , 1 Cysteine , 1 Methionine
149
2 Histidines , 1 Cysteine , 1 Glutamine
3
2 Histidines , 1 Cysteine , 1 Threonine
2
2 Histidines , 1 Water , 1 Methionine
4
2 Histidines , 1 Water , 1 Tyrosine
1
3 Histidines , 1 Aspartic Acid
1
3 Histidines , 1 Cysteine
4
3 Histidines , 1 TPQ
2
3 Histidines , Water
43
4 Histidines
6
For the non-clear copper ions, the same analysis was performed, and Table 11 shows which files were
considered to have regular tetrahedral ions. In spite of this, these ions won’t be analyzed in the distances
plot.
Table 11: Non-clear regular tetrahedral copper ions.
Number of
PDB file
Copper ions
Protein
in the file
Cu Inside
Ion Off
Geometry Box
Centerness (Å)
1snr
3
Nitrite Reductase
Yes
0.17, 0.23, 0.18
2e86
3
Nitrite Reductase
Yes
0.20, 0.20, 0.21
2fjs
3
Nitrite Reductase
Yes
0.07, 0.12, 0.12
2pp7
3
Nitrite Reductase
Yes
0.18, 0.20, 0.25
2pp8
5
Nitrite Reductase
Yes
0.22, 0.20, 0. 33, 0.22, 0.36
2pp9
3
Nitrite Reductase
Yes
0.20, 0.21, 0.22
2ppa
2
Nitrite Reductase
Yes
0.24, 0.25
2ppc
2
Nitrite Reductase
Yes
0.16, 0.19
2ppd
1
Nitrite Reductase
Yes
0.35
2ppe
1
Nitrite Reductase
Yes
0.33
2ppf
1
Nitrite Reductase
Yes
0.19
3.4 Copper Center Distances Plot
Figure 10: Distances plot. Pictures made with WHAT IF [23]
Table 12: Number of regular PDB files and the regular PDB files analyzed in the distances plot due to its ligands
arrangement, also the number of copper ions in all the files analyzed in the plot.
Cu+
Cu2+
Number of Regular PDB files
9
123
Regular PDB files with desired ligands arrangement
8
94
13
149
Number of ions in the files with desired ligands arrangement
Table 12 shows for Cu+ and Cu 2+ the number of ions analyzed in the distances plot, as said before, on this
plot only the regular tetrahedrals with the two Histidines, Cysteine and Methionine ligands were analyzed.
For Cu +, there were 9 PDB files containing regular tetrahedrals, but only 8 of those files had copper ions
binding to the required ligands, the total number of ions on those files is 13. On the other hand, for Cu
2+
there were 123 files containing regular tetrahedrals, but only 94 of those files had copper ions binding to
+
the required ligands, also the total number of ions on those files is 149. So, for Cu , 8 ions were plotted,
2+
while for Cu there were 149 ions being plotted.
In Figure 10 are represented the positions for Cu + and Cu2+ and also its four most common ligands (H for
Histidine, C for Cysteine and M for Methionine). This plot represents the average positions for all the
intervenient residues in the regular tetrahedrals.
Several posterior studies mention large differences between the structures of oxidized and reduced
copper, for instance, in the published work of Taylor et al. (2006), it’s assumed that (for blue proteins)
except for the Cu-Smet distances, all the other bond distances generally get shorter when going from the
reduced to the oxidized state. Also, Guss et al (1986), says that there are significant changes on
distances in the four ligands and also in the copper ion. But, analyzing the data from Taylor et al. (2006),
the differences between both Reduced and Oxidized forms are not impressive.
Table 13: Distances (in Angstroms) from Copper ion to its four ligands, either in the reduced as oxidized form. The
difference between the Oxidized and Reduced forms is also shown. Table adapted from Taylor et al. (2006).
Bond Distances
Red
Cu-N
Oxi
Dif
Red
Cu-N
Oxi
Dif
Cu-S Cys
Red Oxi
Dif
Cu-Smet
Red Oxi
Dif
-
2,04
-
1,91
1,95
0,04
2,09
2,1
0,01
2,9
2,9
0
2,38
2,01
-0,37
2,09
1,97
-0,12
2,18
2,14
-0,04
2,8
2,93
0,13
2,1
2,06
-0,04
1,95
1,99
0,04
2,21
2,23
0,02
2,91
2,94
0,03
Poplar Plastocyanin
2,39
2,06
-0,33
2,12
1,91
-0,21
2,16
2,07
-0,09
2,87
2,82
-0,05
Rusticyanin
1,95
1,89
-0,06
2,22
2,04
-0,18
2,25
2,26
0,01
2,75
2,89
0,14
Amicyanin
Plastocyanin Cyanobacterium S.
Plastocyanin Dryoptteris C.
According to the results obtained in this project, the difference between the average positions, of the four
ligands and the metal ion were of about 0.75 to 1.0 Å but, by this time there were some deviations leading
to the deletion of some files, in order to clear the plot. Figure 10 shows the final plot, and the final value for
the difference of the average positions is of about 0.6 Å, being this value very close to the error expected
in the X-ray structure determination.
3.5 Flipping Histidines
Some literature describes Plastocyanin as having different structures, according to copper’s oxidation
state and pH levels to which the protein is subjected to. One of these cases was published by Guss et al.
(1986), the study relates to PDB files 5PCY and 6PCY; the authors assume there is a difference in the
protein’s active site, but as seen in Figure 13 when both structures are superposed, there is absolutely no
difference between the structures, besides a small change in Proline (in blue), and a rotation of an
β
γ
imidazole ring by 180º about C - C .
Figure 11: Superposed structures of PDB files 5PCY and 6PCY from Poplar Plastocyanin. Picture made with
YASARA
[14]
.
In Figure15, there are the 5PCY and 6PCY structures, this time; only the active site is visible. It’s clear the
flipping of the Histidine residue and the scission of the bond to the copper ion and subsequently, this
Histidine residue will make a hydrogen bond to the oxygen of Proline’s backbone.
a)
b)
Figure 12: a) 5pcy.PDB b) 6pcy.PDB. Picture made with YASARA[14]
The problem with 6PCY’s structure is that there is no reason for the flipping of the Histidine residue, and
this problem may be due to the fact that crystallographers cannot observe the difference between
nitrogen, carbon and oxygen, and usually Histidines are flipped in the wrong position in the structures.
Although, this problem can be solved during validation processes, since there are a series of calculations
that can be made in order to establish which position of the imidazole ring is energetically favorable to the
protein. About the proline puckering, at the resolution of both 5pcy (resolution 1.80 Å) and 6pcy (resolution
1.90 Å) this puckering tends to be unobservable, this means that the supposed puckering of this residue is
a crystallization artifact and not in fact a real puckering [25].
3.6 Wrong previous studies
Table 14: Full references of the most wrong articles
What’s wrong
References
Considers the favorite
Belle, C., Rammal, W., Pierre, J.L., (2005). Sulfur Ligation in
+
coordination numbers for Cu to
be 2, 3 and 4; and for Cu
2+
to be
Copper Enzymes and Models. Journal of Inorganic Biochemistry
99: 1929-1936
4, 5 and 6.
Considers the flipping of the
Guss, J.M., Harrowell, P.R., Murata, M., Norris, V.A., Freeman, H.C.
Histidine residue.
(1986). Crystal Structure Analysis Of Reduced (Cu I) Poplar
Plastocyanin At Six ph Values. J.Mol. Biol 192 (1986): 361-387
Comments the big differences in
+
2+
Taylor, M.K., Stevenson, D.E., Berlouis, L.E.A., Kennedy, A.R.,
the distances of Cu and Cu to
Reglinski J. (2006). Modeling the Impact of Geometric Parameters
its ligands.
On The Redox Potential Of Blue Copper Proteins. Journal of
Inorganic Biochemistry 100: 250-259
Throughout this project, some studies that were considered to be not very accurate in what related to
copper proteins were found. On Table 14, there is a short example of some of the things that were
considered to be contradictory in relation to the results found in this project and also the references to
those studies.
4 | General Conclusions
The main objective of this project was to determine the quality of copper containing PDB files, for that
there is too few data available, it’s possible to observe certain tendencies looking at the statistics, but if
there were substantially more data to analyze, the conclusions would be much more reliable. This study
can be repeated once there are plenty high quality structures deposited in the PDB.
+
Looking at the statistics, it was possible to conclude that for Cu , the coordination numbers are different
from what has been said until now, it’s possible to see that the most often seen coordination numbers are
3, 4 and 5 and not 2, 3 and 4. Having into account, that in this analysis only PDB files with a resolution
better than 2.0 Å were used, the different conclusions can come from that fact. Ten years ago, it was
believed that copper ions tended to exhibit a square planar or distorted octahedral geometry, but in what
comes to the square planar geometry, it is possible nowadays to contradict that belief based on new
techniques and methods. Therefore, it’s reliable to affirm that cuprous and cupric ions both show a
preference for tetrahedral geometry. Also, there are no differences between the tetrahedral structures of
Cu + and Cu2+, it became clear that the oxidation state of the copper ions does not affect significantly the
structure of the active centers in copper proteins; this is something new, because older studies say
otherwise.
Furthermore, type I and type III copper centers are easily identifiable, but type II centers are not so well
described. For example, Promise database describes these centers as being able to bind till up to five
ligands , being these ligands either nitrogen, oxygen or sulfur donors. It’s common to find, for example, a
variable number of Histidines, two to four, and a water molecule or another residue, this is a very
subjective classification; actually there are type II centers that don’t even resemble. Thanks to this, copper
protein’s classification according to its centers should be revised, maybe a wider classification relying in
protein’s function or a reorganization of these considered to be type II centers.
It’s also worth noting that most articles from the past are wrong, for example, the work by Guss et al.
(1986) has made conclusion based on wrong structures and according to ISI Web of Knowledge, this
paper has been cited 362 times, this raises the question: how many studies have been relying in a totally
wrong structure? This is one of the reasons why older studies should all be reviewed because they are not
accurate enough since in the past there wasn’t enough technology to take valid conclusions, nowadays
with more powerful softwares and new methods it’s possible to correct past conclusions.
5 | Future Work
Since there weren’t detected any structural differences between Cu+ and Cu2+, the question that arises is if
there is some other thing that distinguishes between both oxidation states for copper or if the differences
are too small to be detected, or even if there is nothing at all to differentiate both states.
One of the possibilities to be studied would be the protonation states for Histidine and Cysteine, there
could also be other factors like protein bond.
6 | Bibliography
[1] Ando, K., (2008). Ligand-To-Metal Charge-Transfer Dynamic in A Blue Copper Protein Plastocyanin: A Molecular
Dynamics Study. J. Phys. Chem.B 112: 250-256
[2] Belle, C., Rammal, W., Pierre, J.L., (2005). Sulfur Ligation in Copper Enzymes and Models. Journal of Inorganic Biochemistry
99: 1929-1936
[3] Berman, H. M., Westbrook, J., Feng, Z., Gilliland, G., Bhat, T.N., Weissig, H., Shindyalov, I.N., Bourne, P. E. (2000). The Protein
Data Bank. Nucleic Acid Research 28(1): 235-242
[4] Branden, C., Tooze, J. 1998. Introduction to Protein Structure, 2 nd edition. Garland Publishing, Inc., New York, USA, pp. 410
[5] Brown, I.D., Wu, K.K., (1976). Empirical Parameters For Calculating Cation-Oxygen Bond Valences. Acta Cryst. B32: 19571959
[6] Decker, H., Schweikardt, T., Nillius, D., Salzbrunn, U.,Vaenicke, E., Tuczek, F. (2007) Similar Enzyme Activation and Catalysis
in Hemocyanins and Tyrosinases, Gene 389: 183-191
[7] Decker, H., Tuczek, F., (2000). Tyrosinase/Catechol Oxidase Activity of Hemocyanins: Structural Basis and Molecular
Mechanism. TIBS 25: 392-397
[8] Gerdemann, C., Eicken, C., Krebs, B., (2002). The Crystal Structure of Catechol Oxidase: New Insight into the Function of
Type-3 Copper Proteins. Acc. Chem.Res. 35(3): 183-191
[9] Gross, E.L. (1993). Plastocyanin: Structure and Function. Photosynthesis Research, 37:103-116
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Analysis of Copper in PDB files ANALYSIS OF COPPER IN PDB

Transcription

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