Alexandre Varnek Faculté de Chimie, ULP, Strasbourg, FRANCE

1. Criblage virtuel Alexandre Varnek Faculté de Chimie, ULP, Strasbourg, FRANCE

2. computational Filtering, QSAR, Docking Small Library of selected hits Virtual Screening Hit Target Protein High Throughout Screening Large libraries of molecules experimental

3. Chemical universe: • 10200 molecules • 1060 druglike molecules Virtual screening must be fast and reliable Molecules are considered as vectors in multidimentional chemical space defined by the descriptors

4. Génomique Cible HTS Criblage à haut débit High-throughput screening Hits Analyse de données Lead Optimisation Candidat au développement Criblage à haut débit

5. Drug Discovery and ADME/Tox studies should be performed in parallel idea target combichem/HTS hit lead candidate drug ADME/Tox studies

6. Methodologies of a virtual screening

7. Platform for Ligand Based Virtual Screening Similaritysearch ~106 – 109 molecules • Filters ~103 - – 104 molecules • QSAR models Candidates for docking or experimental tests

8. Virtual Screening Molecules available for screening (1) Real molecules 1 - 2 millions in in-house archives of large pharma and agrochemical companies 3 - 4 millions of samples available commercially (2) Hypothetical molecules Virtual combinatorial libraries (up to 1060 molecules)

9. Methods of virtual High-Throughput Screening • Filters • Similarity search • Classification and regression structure – property models • Docking

10. Filters: Lipinski rules for drug-like molecules (« Rules of 5 ») • H-bond donors < 5 • (the sum of OH and NH groups); • MWT < 500; • LogP< 5 • H-bond acceptors < 10 (the sum of N and O atoms without H attached).

11. Example of different filters: Rules for Absorbable compounds

12. Similarity Search: unsupervised and supervised approaches

13. 2d (unsupervised) Similarity Search Tanimoto coef 1 0 1 0 0 0 1 0 0 1 1 1 0 1 1 0 1 0 1 0 0 1 0 0 0 1 0 0 1 1 1 0 1 1 0 1 0 1 molecularfingerprints

14. Structural Spectrum of Thrombin Inhibitors structural similarity “fading away” … reference compounds 0.56 0.72 0.53 0.84 0.67 0.52 0.82 0.64 0.39

15. discontinuous SARs continuous SARs gradual changes in structure result in moderate changes in activity • “rolling hills” (G. Maggiora) small changes in structure have dramatic effects on activity • “cliffs” in activity landscapes Structure-Activity Landscape Index: SALIij = DAij / DSij DAij(DSij) is the difference between activities (similarities) of molecules iand j R. Guha et al. J.Chem.Inf.Mod., 2008, 48, 646 Courtesy of Prof. J. Bajorath, University of Bonn

16. 6 nM MACCSTc: 1.00 Analog 2390 nM discontinuous SARs VEGFR-2 tyrosine kinase inhibitors small changes in structure have dramatic effects on activity • “cliffs” in activity landscapes • lead optimization, QSAR bad news for molecular similarity analysis... Courtesy of Prof. J. Bajorath, University of Bonn

17. Example of a “Classical” Discontinuous SAR Any similarity method must recognize these compounds as being “similar“ ... (MACCS Tanimoto similarity) Adenosine deaminase inhibitors

18. Screening library Virtual library Diverse Subset HTS Hits Design of focussed library Parallel synthesis or synthesis of single compounds Screening Virtual Screening ... when target structure is unknown