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A knowledge-based approach for reaction generation

A knowledge-based approach for reaction generation. Development, validation and applications Dimitar Hristozov, 04.06.2009. public reaction databases. commercial reaction databases. Motivation. wealth of reaction data extract some of the knowledge hidden in these data

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A knowledge-based approach for reaction generation

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  1. A knowledge-based approach for reaction generation Development, validation and applications Dimitar Hristozov, 04.06.2009

  2. public reaction databases commercial reaction databases Motivation • wealth of reaction data • extract some of the knowledge hidden in these data • use this knowledge to assist the medicinal chemist • suggest new, synthetically feasible molecules with desired bio profile lab notebooks (eLN) medicinal chemists U >1,500,000 reactions covering general organic chemistry large number of reactions per year, strong medicinal chemistry bias proprietary reaction databases public data

  3. Reaction vectors From reaction database to knowledge base R1 R2 P reactant vector, R = (R1 + R2) product vector, P 1 1 1 2 2 2 3 3 3 4 4 4 Bond Bond Bond C-C C-C C-C C=O C=O C=O C-OH C-OH C-OH C-OR C-OR C-OR reaction vector, D = P - R # # # 4 0 4 1 1 0 0 -2 2 0 2 2 Patel, H., Bodkin, M.J., Chen, B., Gillet, V.J.A Knowledge-Based Approach to De Novo Design Using Reaction Vectors, J. Chem. Inf. Model., 2009, ASAP article

  4. From reaction vector to products (I) • The reaction vector, D, equals the difference between the product vector, P, and the reactant vector, R D = P – R • Given a reaction vector, D, and a reactant vector, R, the product vector, P, can be obtained P = D + R • Given a product vector, P, can we reconstruct the product molecule(s)? better descriptor is required 1 2 3 4 Bond C-C C=O C-OH C-OR # 4 1 0 2

  5. Extended atom pairs atom types atom pairs n: number of bonds to heavy atoms p: number of π bonds r: number of ring memberships AP2: atoms 1 bond away AP3: atoms 2 bonds away

  6. From reaction vector to products (II) “wrong” or “missing” atom pairs product vector (P = D + R) C(2,1,0)-2(2)-O(1,1,0) C(3,1,0)-2(1)-O(2,0,0) C(3,0,0)-2(1)-O(2,0,0) C(3,1,0)-2(1)-O(2,0,0)

  7. Reaction vectors in action Reaction APs “Lost” APs “Gained” Reaction Vector C(2,0,0)-2(1)-O(1,0,0) -1 C(2,1,0)-2(1)-C(2,0,0) +1 C(2,0,0)-2(1)-C(2,0,0) -2 C(2,1,0)-2(2)-C(1,1,0) +1 Starting Molecule Product Atoms/bonds selected for removal using APs lost New atoms/bonds added using APs gained

  8. Advantages • Does not require manual atom-atom mapping of the reaction centre • Makes use of the synthetic chemistry data collected through the years • Accounts for the synthetic accessibility of the proposed molecules – all transformations are derived from successful reactions • Is fast to apply – no substructure searching is required

  9. Good approach… so how is it… implemented?

  10. Optimisation made easy • build as an Eclipse plug-in => 100% Java

  11. KNIME meets Chemaxon

  12. Sketcher

  13. File reader

  14. Reaction generator

  15. Convertor

  16. Multi-objective ranking

  17. File writer

  18. Marvin Views

  19. Looks great… but does it … work?

  20. 1 create knowledge base 5,695 diverse reactions 2,902 reaction vectors 2 for each reaction 3 retrieve its reaction vector -H2O 5 is the product obtained in less than 30 seconds? 4 apply the reaction vector to the starting materials Reproducing reactions +

  21. How well did it work? • Products generated for ~90% of the 5,695 reactions

  22. How fast did it work? • Median run time: 0.015 seconds per reaction

  23. Epoxide reduction Epoxide reduction • reproduced in large variety of environments (350 reactions) • only one reaction was not reproduced

  24. Works like a charm… More than 95% reproduced successfully epoxide reduction epoxide formation ester to amide alcohol dehydration acid to aldehyde nitrile to aldehyde Friedel-Crafts acylation nitrile hyrdrolysis alcohol amination nitro reduction aldol condensation alkene oxidation

  25. Still works like a charm… More than 90% reproduced successfully olefin metathesis amide reduction ether halogenation ozonolysis Beckmann rearrangement Claisen rearrangement alkene halogenation Dieckmann condensation olefination Wittig-Horner Robinson annulation

  26. Claisen condensation • variety of environments were tested • 79 out of 100 reactions were successfully reproduced • 21% of the reactions were not reproduced • mainly condensations (intra- and intermolecular) which result in ring closures

  27. Still works More than 50% reproduced successfully • A large variety of reactions successfully reproduced • Small difficulties with complex cycle formations • improvements are on their way Cope rearrangement (67% success) hetero Diels-Alder (73% success) Claisen condensation (79% success) Diels-Alder cycloaddition (49% success) Fischer indole synthesis (57% success)

  28. Wow! Cool! It works! but what is its… use?

  29. Knowledge base Reagents database Generating new molecules Starting molecule Select reaction transform Is a second reagent required? yes Select suitable reagent no Can the transform be applied? no Discard reaction vector yes Apply reaction transform New molecule

  30. Multi-objective de novo design • rank the proposed new molecules • direct the generation towards desired new molecules

  31. Use case one: Lead optimisation Here is my starting material. What kind of (feasible) one step transformations may I make? • starting molecule: Pencillin G An example from Patel, H., Bodkin, M.J., Chen, B., Gillet, V.J. A Knowledge-Based Approach to De Novo Design Using Reaction Vectors, J. Chem. Inf. Model., 2009, ASAP article

  32. Lead optimisation (cntd.) Penicillin G An example from Patel, H., Bodkin, M.J., Chen, B., Gillet, V.J. A Knowledge-Based Approach to De Novo Design Using Reaction Vectors, J. Chem. Inf. Model., 2009, ASAP article

  33. Use case two: Synthetic route I have this (active) fragment. Is there a route from it to the molecule I have in mind? • reproducing known synthetic route – Plavix 1 2 3 4 Synthetic route from Wang, L. et al., Synthetic Improvements in the Preparation of Clopidogrel, Org. Process Res. Dev., 2007, 11 (3), 487-489 An example from Patel, H., Bodkin, M.J., Chen, B., Gillet, V.J. A Knowledge-Based Approach to De Novo Design Using Reaction Vectors, J. Chem. Inf. Model., 2009, ASAP article

  34. Use case three: Library design With which of these reagents will my starting material undergo reaction X? • enumerate a library using a single reaction and a number of different reagents starting material reaction X (X = Suzuki coupling) 628 boronic acids as reagents An example from Patel, H., Bodkin, M.J., Chen, B., Gillet, V.J. A Knowledge-Based Approach to De Novo Design Using Reaction Vectors, J. Chem. Inf. Model., 2009, ASAP article

  35. Library design (cntd.) 292 products generated

  36. Summary • The reaction vectors offer good way to explore the knowledge hidden inside reaction databases • A variety of chemical reactions can be reproduced with this approach • The method works fast • The is applicable in different medicinal chemistry related scenarios • The use of the method is made easy by variety of KNIME nodes which have been implemented

  37. Acknowledgements • Michael Bodkin • for his continuous support both in and outside my daily work • Hina Patel • for creating the first prototype which sprung the reaction vectors into live (http://pubs.acs.org/doi/abs/10.1021/ci800413m) • Dave Evans, Fred Ludlow, Swanand Gore, Dave Thorner, Maria Whatton, Juliette Pradon • for many stimulating discussions and for their continuous support

  38. Thank You! do you have any… questions, comments, recommendations?

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