Search 10^12 virtual compounds in minutes with a Bayesian model made from 10^6 combinatorial chemistry derived compounds. This work has been published: http://pubs.acs.org/doi/abs/10.1021/ci900072g

1. Exploring virtual compound space with Bayesian statistics Willem P van Hoorn Chemistry Pfizer Global Research and Development Sandwich UK [email_address] Pipeline Pilot UGM, San Diego, Mar 2007

4. Methods

7. Building the multi-category Bayesian models Pfizer compound database Pfizer library file: all compounds made in-house and externally by combinatorial chemistry: O(6) compounds, O(3) libraries 50% 50% 12.5K Pfizer singleton diversity subset

9. Multi-category Bayesian predictions A probe (UK-92480, Sildenafil) By default top 16 libraries is calculated: Singleton Library1 Library2 ... Library15 104.57 84.10 43.97 ... 12.63

10. Bayesian predictions are exemplified by Nearest Neighbour search Exemplify libraries by identifying nearest neighbours from library file, default top 6. Final output: 16 x 6 = 96 compounds (one-plate screenable hypothesis) 16 96 R1 R2 849914-95-0 139755-82-1 298214-47-8 no CAS 155879-54-2 223430-18-0 UK-A UK-B UK-C UK-D UK-E 1. Singleton (in file: 12500) Singleton Library1 Library2 ... Library15 104.57 84.10 43.97 ... 12.63

13. Validation

14. Random test set Exclude singleton library O(6) Random x%: 9452 Top 5 predicted library ID compared with real library ID V1 9411, 99.6% Found in top 5 41 , 0.4% 9068, 96% 9452 Not in top 5 Found in top 1 Test set

15. 41 compounds with correct library not in top 5 PF-A Internal Library 1 349 -29.0651987519029 Another PF number Internal Library 2 243 -13.3644982689003 Another PF number Internal Library 3 69 -0.400118961865439 Another PF number Internal Library 4 63 0.614583090788282 Another PF number Internal Library 1 53 -0.13987606970494 Another PF number Internal Library 5 50 -7.32271642948761 Another PF number Internal Library 1 35 3.41709994966454 Another PF number Internal Library 3 22 9.57829190295786 Another PF number Internal Library 1 22 10.0504136444794 Another PF number External Library 1 20 22.8956131731457 Another PF number External Library 2 19 18.8320528385981 Another PF number Internal Library 3 15 12.1074842056827 Another PF number Internal Library 1 14 54.6179465790837 Another PF number Internal Library 3 13 16.6244027916311 Another PF number Internal Library 1 12 6.74173586963795 Another PF number Internal Library 1 12 17.0964105412622 Another PF number Internal Library 1 11 58.7994305333701 Another PF number External Library 3 10 58.2193181435516 Another PF number Internal Library 1 10 12.5102031415206 Another PF number Internal Library 6 9 19.4093857882624 Another PF number Internal Library 1 8 20.6383651456158 Another PF number External Library 3 8 73.0633503114444 Another PF number External Library 4 8 18.5429747446516 Another PF number Internal Library 1 8 36.9730841061725 Another PF number Internal Library 1 7 34.8859762378176 Another PF number Internal Library 3 7 17.3617539873978 Another PF number Internal Library 1 7 30.8582847036755 Another PF number Internal Library 1 7 41.848859585633 Another PF number External Library 5 7 25.8587564812026 Another PF number External Library 6 6 33.5395919145182 Another PF number External Library 7 6 39.9074521984672 Another PF number External Library 8 6 32.3248563198852 Another PF number External Library 9 6 23.9421542596281 Another PF number External Library 10 6 95.1965176091739 Another PF number Internal Library 1 6 53.8715604224809 Another PF number Internal Library 1 6 28.2709230508615 Another PF number Internal Library 1 6 48.1827060771728 Another PF number Internal Library 1 6 17.7689907755174 Another PF number Internal Library 7 6 57.5694207876578 Another PF number Internal Library 7 6 53.9529913359943 Another PF number Internal Library 7 6 56.184768481901 compound_ID correct library_id ranked_as Bayesian score

16. PF-A Amide formation Monomer 2 Monomer 1 + No registration error Worst mispredicted: PF-A General remark: in-house libraries have broad scope, therefore harder to predict Internal library 1 29,800 compounds registered, monomers known for 28,670 120 of these contain Monomer 1, but only 1 compound contains Monomer 2: PF-A is atypical product

19. Recall of known library id as function of model Exclude singleton library O(6) Random x%: 9452 Top 5 predicted library ID compared with real library ID 205, 2.2% 9247, 97.8% 5692, 60% ECFP_Enrichment 85, 0.9% 9367, 99.1% 8920, 94% FCFP 13, 0.1% 9439, 99.9% 8372, 89% ECFP_EstPGood 108, 1.1% 9344, 98.9% 6093, 64% FCFP_Enrichment 9441, 99.9% 9411, 99.6% Found in top 5 11, 0.1% 8547, 90% FCFP_EstPGood 41, 0.4% 9068, 96% ECFP Not in top 5 Found in top 1 Model Test set

21. Interpreting the results

23. Probe is highlighted by what each library recognises 1. Singleton 2. In-house 1 3. In-house 2 4. External 1 5. External 2 6. External 3 7. External 4 8. External 5 9. External 6 10. External 7 11. External 8 12. External 9 13. External 10 14. External 11 15. External 12 16. External 13 In-house 2 yields compounds similar to left hand site of probe In-house 1 yields compounds similar to right hand site of probe

24. Highlighted probes compared to actual compounds retrieved 2. In-house 1 3. In-house 2 4. External 1

25. How about the singleton file?

28. Pfizer solids and vendor compounds have been mapped to libraries 7 unmapped libraries 6 unmapped libraries O(5) solid samples for which no liquid sample is available O(4) O(5) O(6) structures from ChemNavigator not in Pfizer files Singleton Singleton

30. Implementation

32. A happy user