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