Screening for early drug discovery and basic research in the project

Transcription

Screening for early drug discovery and basic research in the project
Moscow, April 13 2010
Screening for early drug discovery and basic
research in the project “Protein kinases – Novel
drug targets of post-genomic era.”
Peter Goekjian, Bernard Marquet
Universite de Lyon
MEDBIOTECH V
Broad Screening for Drug Discovery:
the early days
EurasiaBio 2010
Peter Goekjian, Université de Lyon
Drug Discovery Closer to Today
EurasiaBio 2010
Peter Goekjian, Université de Lyon
Individual Compounds
Storage boxes
(80 tubes)
Testing plates
1mM
Plate storage at -28°C
Distribution plate (96 well/80 cpds)
10 or 25mM
Testing plates
5 mM
Testing plates
10 mM
Mail formatted plates to biology-oriented groups
Bernard Marquet, Francois Liger
EurasiaBio 2010
Peter Goekjian, Université de Lyon
Microlab® STARlet
dilution robot (HAMILTON)
Plates 1-10 mM, 25µL
Plating made possible by a collaboration with the génopôle platform at the
Laboratoire DTAMB (Développement technologique et d’analyses moléculaire de la
biodiversité) – Pr Jean Jacques Madjar (UCB - Lyon 1) et Dr Christine Oger
37 plates formatted (10 mM, 25 mM)
EurasiaBio 2010
Bernard Marquet, Francois Liger
Peter Goekjian, Université de Lyon
Chemical Library of the « ICBMS »
Economic
development
EZUS, LST, CNRS
B. Marquet (manager)
F. Liger (assistant)
ICBMS
teams
Objectives
Local chemical
library and data
base
(MDL® Isis/Base)
• Manage the database in conjunction with
the CNRS national chemical library.
• Collect molécules intra or extra « Institut »
1800 compounds
• Generate and send microtitre plates,
syntheses of homologue compounds, analyses
of the results, reports and publications.
• Search for new biological tests and new
partners, pursue financial support
National
chemical library
CNRS
37 000 compounds
Academic or
industrial users
EurasiaBio 2010
Peter Goekjian, Université de Lyon
Bernard Marquet, Francois Liger
Evolution of nature and number of tests/ year
Pharmacy-Freiburg (Pr
Manfred Jung)Zinc dependent
histone deacetylases
NCI Milan
(Pr Carlo Gambacorti)
Tyrosine kinase receptors
9000
8000
CNRS/ ICSN (Dr Thierry
Cresteil) Cytotoxicity)
7000
IBS/Grenoble (Dr Frank
Kozielski) Molecular motors
6000
CNRS/ ICSN (Dr Daniel Guénard)
Acetyl/Butyryl cholinesterase
5000
CNRS/ Roscoff Dr (Laurent
Meijer) Cyclin-dependent
kinases
4000
3000
CEA Grenoble (Dr Laurence
Lafanechère) Cytoskelet targets
2000
INSA-UCB-Lyon1 (Pr
Philippe Lejeune) Biofilms
inhibition
1000
ENSCP/Paris (Pr Jean
Marc Paris) antibacterians
0
20
02
EurasiaBio 2010
20
03
20
04
20
05
20
06
20
07
20
08
UCB Lyon1 (Dr Laurent
Ségalat) Orphan diseases
Peter Goekjian, Université de Lyon
Protein Kinase Research Consortium Library
FP6 IP LSHB-CT-2004-503467, 2004-2009
PKRC Chemistry
teams
Individual
compounds
PKRC Chemical Library
B. Marquet (manager)
New
collaborations
Formatted plates
PKRC Biology
teams
Local chemical
library and data
base
(MDL® Isis/Base)
Non PKRC
Biology
teams
1077 compounds
Objectives:
EurasiaBio 2010
• « Second generation » biological tests/collaborations
• Maximize the production of biological data
• Compile biological data for meta-analysis
•Longer timescale than project
Peter Goekjian, Université de Lyon
Protein Kinase Research Consortium Library
•1077 compounds tested on over 94 targets including 88 human
protein kinases
•>136 351 enzymatic tests + 5 760 cellular tests
(129 604 Phil Cohen, University of Dundee)
•1455 hits (>80% inhibition at 10 uM). At least one hit on 71/75 kinases
Library quality for basic research:
•Manageable size for non HTS screening
•Structural diversity around a central design theme
•Structural clusters for preliminary hit validation
•Selectivity profile already established
•Chemists with the know-how and availability for further development
Bernard Marquet, Peter Goekjian
EurasiaBio 2010
Peter Goekjian, Université de Lyon
Protein Kinase Research Consortium Library
Have developed a limited number of these hits towards lead
compounds at this stage.
For example, optimized a potent and selective pim inhibitor
based on the hits identified in the PKRC screen. Pascale
Moreau, Universite Blaise Pascal – Clermont Ferrand, Päivi
Koskinen, University of Turku, Finland.
Optimized several cdk2 inhibitors. Benoit Joseph, Philippe
Belmont, Universite de Lyon, Laurent Meijer, Station Biologique
Roscoff
•PROBLEM: New bottleneck at hit validation and exploration
EurasiaBio 2010
Peter Goekjian, Université de Lyon
Early Drug Discovery
EurasiaBio 2010
Peter Goekjian, Université de Lyon
Data Meta-Analysis for Modeling
Pharmacophore modeling: fast,
structural analogy-based analysis.
Pharmacophore models for
protein kinases and other targets.
Validate pharmacopore models
and identify potential secondary
targets.
LigandScout® Inte:ligand Gmbh.
Protein Docking: Generation of multiple protein models and
validation using SAR. Identify compound binding subgroups.
Meta-analysis of kinase selectivity profiles
EurasiaBio 2010
Peter Goekjian, Université de Lyon
Selectivity Screening by Affinity
Chromatography
Immobilized inhibitors can be used to “fish out” potential cellular targets
from cell extracts. Reflect the distribution and post-transductional
modification state of the cell.
N
O
N
O
O
N
H
N
O
N
N
O
O
GP
FBP1
GSK-3α
GSK-3β
Erk1
Erk2
Cdk5
PDXK
CH3
EurasiaBio 2010
Peter Goekjian, Université de Lyon
Non Protein Kinase Targets
Caloric Restriction: an extremely low calorie diet results in
extended lifespan, lower fat, higher mobility. Have identified a
negative regulator in C. elegans whose inhibition could
maintain these benefits without the need for caloric restriction.
Identified a potent inhibitor of this enzyme by screening the
PKRC library that is active in vivo, and is able to reproduce
the desired effect.
Identified two other inhibitors that exhibit the same effect, but
whose target is not the same mediator. Upstream or
downstream target?
Hugo Aguilaniu, ENS Lyon and Conrad Kunick, Technische
Universität Braunschweig
EurasiaBio 2010
Peter Goekjian, Université de Lyon
Non Protein Kinase Targets
ATP-competitive inhibitors also inhibit NAD-dependent
enzymes. For example, bis(indolyl)maleimides were found to
be potent inhibitors of Sirt2. The SAR is quite different from
that of protein kinases. Manfred Jung, Albert-LudwigsUniversität Freiburg, Conrad Kunick, Technische Universität
Braunschweig and Peter Goekjian, Universite de Lyon.
Trapp et al. J. Med. Chem. 2006, 49, 7307-7316.
NovoCib screened the PKRC library against enzymes
involved in nucleotide biosynthesis. Have identified a number
of exploitable hits, both NADH and non-NADH mimetic.
Larissa Balakireva, NovoCIB Lyon, Pascale Moreau,
Universite Blaise Pascal Clermond Ferrand, Peter Goekjian,
Universite de Lyon.
EurasiaBio 2010
Peter Goekjian, Université de Lyon
Fragment Based Drug Design
Fragment
Library
Molecular weight ≤ 300 g/mol
cLogP ≤ 3
hydrogen bond donors ≤ 3
hydrogen bond acceptors ≤ 3
3D Structure of the
target
2) Structure
based design
Optimisation
Active
molecules
3) Evolution
Combination
Guanidino kinase of Schistosoma mansoni. Jean-Marc Lancelin, Olivier
Marcillat, Peter Goekjian, Universite de Lyon and Colette Dissous, Institut
Pasteur Lille.
EurasiaBio 2010
Peter Goekjian, Université de Lyon
Sructure-Based Drug Design
Generated homology models of NMP-ALK in the inactive, resting
(intermediate) and catalytic (active) conformations.
Virtual screening of the Maybridge database identified 100 commercial
compounds for screening, yielding a good number of hits. Progressive
cycles of refining improved model predictiveness.
Hit optimization and scaffold hopping have provided two classes of lead
compounds. Carlo Gambacorti, University of Milan-Biccoca, Leonardo
Scapozza, Universite de Geneve, Peter Goekjian, Universite de Lyon
EurasiaBio 2010
Peter Goekjian, Université de Lyon
Outlook
Both low-throughput and high-throughput screening are essential
elements of early drug discovery and basic research, and libraries
should be formatted for both. Delocalized and standardized.
Screening must be integrated into an overall process from target
identification to lead compound. Screening alone will generate a huge
number of unexploited hits.
Scientific bottleneck: hit evaluation. Need new tools to predict the
potential for activity and selectivity at the lead compound or preclinical
candidate stage based on a hit structure or a small cluster
Structural bottlenecks: (a) funding mechanisms from the hit to early
lead; (b) optimizing and anticipating the transitions between stages.
EurasiaBio 2010
Peter Goekjian, Université de Lyon
Acknowledgements
European Commission, Protein Kinase Research FP6 IP LSHB-CT2004-503467, 2004-2009. Pr. Raimo Tuominen, University of Helsinki
•Conrad Kunick, Technische Universität Braunschweig
•Pascale Moreau, Michelle Prudhomme, Universite Blaise Pascal
•Jari Yli-Kauhaluoma, University of Helsinki
•Philippe Belmont, Olivier Piva, Benoit Joseph, Universite de Lyon
•Maria Preobrazhenskaya, Gause Institute of Antibiotics, RAMS
•Valeriy Danilenko, Vavilov Institute of General Genetics, RAS
•Andrew Marston, University of Geneva
•Sir Philip Cohen, University of Dundee
•Laurent Meijer, Station Biologique Roscoff
•Manfred Jung, Albert-Ludwigs-Universität Freiburg
•AB Science, Marseille
•NovoCib, Lyon
•Hugo Aguilaniu, Ecole Normale Superieure de Lyon
•Janos Szollosi and Gyorgy Vereb, University of Debrecen
Bernard Marquet, Francois Liger
EurasiaBio 2010
Peter Goekjian, Université de Lyon