Webinar by Aureus Sciences : "Predicting Pharmacology and Safety Profiles with AurPASS"

1. Make the right decisionswith data youcan trust

2. Instructionsforattendees Due to the High number of attendees: Before starting Use your full name for Identification We will mute your microphone during the webinar During the webinar Use the chat for questions At the End You can ask your questions orally We will answer them either in the webinar session or later on by email. 07/04/2011 2 AurPASS

3. PredictingPharmacology & Safety Profiles Using AurPASS

4. Agenda Aureus Sciences Knowledge-Based Pharmacological Profiling AurPROFILER: visualizing the Known Filling the Gap using AurPASS to Predict the Unknown AurPASS PASS Predictive Algorithm Added Value of AurSCOPE Knowledgebases AurPASS Ion Channels & AurPASS Kinase Live Demo: Applications for Safety Pharmacology Assessment Discussion 07/04/2011 4 AurPASS

5. Aureus at a Glance Aureus is a knowledge and information management solutions provider for the Life Science industry located in Paris. Over the past 10 years the company has developed a unique knowledge production platform which stores, indexes and organizes critical chemical and bioactivity information including experimental in vitro and in vivo protocols from the public or private literature. Aureus employees 20 highlevelscientists (PhD and MSc) includingscientific and IT project leaders and documentation analysts Aureus is funded by institutional investors like CDC Entreprise, AXA Provate Equity, OTC Asset Management and is part of the OSEO Excellence innovation team. 07/04/2011 5 AurPASS

6. Aureus Approach

7. AurSCOPE Knowledge Databases Target Pharmacological Space 2002 2004 2005 2008 2009 Nuclear Receptor Protease GPCR Kinase Ion Channel Publications Analyzed 13,303 including 6,966 patents 32,588 including 15,281 patents 4,668 including 2,484 patents 4,226 including 1,060 patents 10,206 including 6,806 patents Biological Activities 275,044 418,202 186,047 1,243,793 670,407 98,439 354,323 146,426 Unique Ligands 124,313 48,500 Biological Protocols Aureus Terminology, Glossary, Thesaurii >70 glossaries and dictionaries, 5-10 taxonomies, >65,000 terms and synonyms, IUPHAR, SwissPROT 07/04/2011 7 AurPASS

8. AurSCOPE Knowledge Databases ADME/DDI & TOX hERG ADME/DDI Hepatotox 12,165 including 200 FDA Reviews Publications Analyzed 2,291 including 547 Patents 3,600 Articles (67 patents, 75 FDA Studies) 70,035 Biological Activities 33,210 462,785 Unique Ligands 13,887 34,872 compounds including 4,050 metabolites 845 Drugs Biological Protocols Aureus Terminology, Glossary, Thesaurii >100 glossaries and dictionaries, 5-10 taxonomies, >65,000 terms and synonyms, IUPHAR, SwissPROT 07/04/2011 8 AurPASS

9. Make The Right Decision With Data You Can Trust AurPROFILER Data analysis & Navigation Medicinal Chemistry Space AurQUEST Data mining AurPASS Predict Biological Activities Spectra DDI Predict AurPASS

10. AurPROFILER – Pharmacology Profiles of 74 Drugs (Big Pharma) 07/04/2011 10 AurPASS

11. Filling the Gap Using AurPASS in silicoPredictions 07/04/2011 11 Aureus Prediction of Activity Spectra for Substances AurPASS

12. Predicting New Activities on Selectedbig Pharma Drugs 277 Ion Channels 86SelectedMoleculesfrom MERCK 07/04/2011 12 AurPASS

13. Over Forty Publications with Independent Confirmation of PASS Predictions… 07/04/2011 13 AurPASS

14. AurPASS Training Set SAR data extracted from individual AurSCOPE databases Chemical & biological post-processing Chemical Structures Multilevel Neighborhoods of Atoms (MNA) descriptors SAR Base Diverse chemical structures and associated MNA descriptors Associated qualitative biologicalactivity types Prediction Algorithm PASS Bayesian approach Models Validation LOO and L20%O validations External dataset 07/04/2011 14 AurPASS

15. Training Set SAR data extracted from individual AurSCOPEknowledgebases Chemical & biological post-processing Chemical Structures Multilevel Neighborhoods of Atoms (MNA) descriptors SAR Base Diverse chemical structures and associated MNA descriptors Associated qualitative biologicalactivity types Prediction Algorithm PASS Bayesian approach Models Validation LOO and L20%O validations External dataset AurPASS 07/04/2011 15 AurPASS

17. No mixtures

18. Inorganic and metalo-organicremoval

20. Target hierarchy

21. Target species, celllinesand tissues

22. Biologicalactivityparameters

23. Ligand action on targetAurPASS

24. 07/04/2011 17 AssigningActivity Classes AurPASSActivity Types AurPASS

26. The first level MNA descriptor include the atom’s zero level descriptors and zero-level descriptors of its neighboring atoms sorted lexicographically … Encoding Chemical Structures: MNA Descriptors 07/04/2011 18 MNA descriptorsdictionary AurPASS

27. Encoding Chemical Structures: MNA Descriptors 07/04/2011 19 MNA/2 C(C(CC-H)C(CC-C)-H(C)) C(C(CC-H)C(CN-H)-H(C)) C(C(CC-H)C(CN-H)-C(C-O-O)) C(C(CC-H)N(CC)-H(C)) C(C(CC-C)N(CC)-H(C)) N(C(CN-H)C(CN-H)) -H(C(CC-H)) -H(C(CN-H)) -H(-O(-H-C)) -C(C(CC-C)-O(-H-C)-O(-C)) -O(-H(-O)-C(C-O-O)) -O(-C(C-O-O)) MNA/0: C MNA/1: C(CN-H) MNA/2: C(C(CC-H)N(CC)-H(C)) AurPASS

28. PASS Approach for Biological Activity Prediction 07/04/2011 20 According to the Bayes' theorem, the probability P(A|S) that the compound S has activity (or inactivity) A, equals to: P(A|S) = P(S|A)•P(A)/P(S) If the descriptors of organic compound D1, ..., Dm are independent, then: P(S|A) = P(D1, ..., Dm|A) = ПiP(Di|A) P(A)andP(A|Di)are calculated as sums through all compounds of the training set: AurPASS Filimonov D.A., Poroikov V.V. (2008). Probabilistic Approach in Virtual Screening. In: Chemoinformatics Approaches to Virtual Screening. Alexander Varnek and Alexander Tropsha, Eds. RSC Publishing.

29. The list of activities which are probable for a particular compound with the estimates for each activity of : Pa: probability to be active Pi: probability to be inactive Pa and Pi are calculated independently: Pa + Pi  1 Pa (Pi) can be considered as the probability of the compound belonging to classes of active (inactive) compounds PASS Approach for Biological Activity Prediction 07/04/2011 21 AurPASS

30. AurPASS Ion Channels – Version 1.2.1 07/04/2011 22 Training Set 47 938 molecules 517 Activity Types Mean Accuracy of Prediction: 98% Test Set 2244 molecules 113 Activity types Mean Accuracy of Prediction: 90% AurPASS

31. PredictionAccuracyusingAurPASS

32. How AurPASS Works? 07/04/2011 24 Ion Channels Kinases GPCRs Proteases NuclearReceptors Off-Targets AurPASS

33. AurPASS Ion Channels 07/04/2011 25 Live Demo AurPASS

34. AurPASS Product Line 07/04/2011 26 AurPASS Application Note and Evaluation Software available Under Request May, 2011 AurPASS Off-Targets AurPASS GPCR AurPASS Nuclear Receptors

35. Thank you for your attention Aureus Sciences 174, Quai de Jemmapes 75010 Paris, FRANCE www.aureus-pharma.com 07/04/2011 27 AurPASS