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ICIC 2014 Knowledge-Based De Novo Molecular Design Using ICSYNTH FRP

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A new knowledge-based approach to the de novo design of synthetically feasible molecules is described. The method is based on specifically designed transform libraries abstracted from reaction databases. The structure generation process is based on conceptual chemistry and the degree of complexity introduced in the new structures can be modulated using specific parameters. Furthermore, this new system allows the integration of the results obtained in different workflows to calculate/predict other important physico-chemical properties of the new suggested molecules.

Publicado en: Salud y medicina
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ICIC 2014 Knowledge-Based De Novo Molecular Design Using ICSYNTH FRP

  1. 1. Knowledge-based Compound Design Fernando F. Huerta Chemnotia AB powered by InfoChem GmbH
  2. 2. QSAR models Ligand Based Pharmacophore models Structure Based HTS Compound (Drug) Design Fragment Based
  3. 3. How Drugs Look? HN N N N O S O OH NH2 O O F F N HN N O OH HN N NH2 O F F N O HN O O N O OH NH2 O F F N HN HN N O OH O F F N HN Norfloxacin (Noroxin™) Ciprofloxacin (Cipro™) Sparfloxacin (Zagam™) Grepafloxacin (Raxar™) N Drug Discovery Today 2011, 16, 722 Drug Discovery Today 2011, 16, 779 N S O N O O N S O N F O F Nexium® Rabeprazole® PANTOPRAZOLE® O N N Cl S N N O HO Loxapine® Seroquel®
  4. 4. Why Do Drugs Look Similar? Protein Binding Site Drug Design Paradigm Activity, Selectivity, ADMET,.. Similar structural motif share similar properties(?)
  5. 5. Compound (Drug) Design What would you do?
  6. 6. Knowledge-based Compound Design
  7. 7. Transforms from Reaction Databases Reaction database e.g. SPRESI proprietary databases commercial databases 1. Pre-processing Template (2 levels): Transform: Transform library Automatic transform extraction (ICMAP/CLASSIFY) N Remove bond 1-3 1 11 R1 12 R2 10 9 2 6 3 4 O 5 7 8 13 14 Remove bond between atoms 3 and 6. Make new single bond bReetwmeoevne abtoonmds 1 3- 2and 5 Decrease bond order of double bond 2=4 by 1. Make new single bond between atoms 3 and 4 Make new single bond between atoms 2 and 6. Add group to atom 3: -OH 2. Retrosynthesis Lookup stored example reactions H O O H Target molecule Precursor(s) 1 Precursor(s) 2 ... Precursor(s) n Transform x Transform y ... Transform z
  8. 8. Transforms from Reaction Databases Reaction database e.g. SPRESI proprietary databases commercial databases Transform library 2. Forward Reaction Lookup stored example reactions Starting Material or Reactant Transform x Transform y Transform z Product(s) 1 Product(s) 2 ... Product(s) n ... N Cl N O
  9. 9. Retrosynthetic Analysis • Target orientated • Complexity reduction • Availability of starting materials • Multistep process Reaction Prediction • Unknown product molecules • Molecular size • Reagents • Single reaction step
  10. 10. Forward Reaction Prediction (cont.) • Number of transforms NH N 2 O S OH O O N OH H H
  11. 11. ICSYNTH Strategy Parameters • Strategy: defined by a set of parameters • Rating of generated precursors/products • 42 parameters (Retrosynthesis / FRP) ICSYNTH FRP Parameters O OH Reactant Transform Product(s)
  12. 12. Strategy Parameters Optimization 42 parameters (reactant, transform, product) optimization algorithm
  13. 13. ICSYNTH FRP Strategies Reactivity Mapping FG Library Design Ring Introduction Scaffold Modification: Not Scaffold Hopping!!
  14. 14. FRP Examples / Applications Reactivity Mapping N N O N NH O N N O N NH O R N O R N N N NH N N O N NH O Hal N N O N N O N N O O N NH O R
  15. 15. FRP Examples / Applications FG Library Design N HO O N NH reaction center
  16. 16. Knowledge-based Compound Design Other Databases
  17. 17. Knowledge-based Drug Design • One synthetic step (reliable?) • Novelty • Drug like • Physicochemical properties • Lipinski
  18. 18. Knowledge-based Drug Design inspired by “de novo design using reaction vectors” Example 1 HN O N S OH O O Penicillin G Example from J. Chem. Inf. Model., Vol. 49, No. 5, 2009, 1163-­‐1184
  19. 19. Knowledge-based Drug Design inspired by “de novo design using reaction vectors” Example 1 HN O N S OH O O Penicillin G Example from J. Chem. Inf. Model., Vol. 49, No. 5, 2009, 1163-­‐1184 HN O N S OH O O Reaction Vectors ICSYNTH FRP (precision Medium) ICSYNTH FRP (precision High)
  20. 20. Knowledge-based Drug Design Example 1
  21. 21. Knowledge-based Drug Design Example 1 • 30 suggested cpds from ICSYNTH vs 1000 cpds (Reaxys, penicillinG sss) • Fingerprint similarities calculated (30000) • Identical compounds filtered off (similarity = 1) • Compounds with Tanimoto distance between 0.5-0.9 were selected • Synthetic data (ICSYNTH) available • Calculated med chem properties of new suggestions as well as med chem properties of previously reported ones available for analysis
  22. 22. Knowledge-based Drug Design Example 2 N Cl N O Core Structure (Diazepam) Reaxys search 214 reactions / products N Cl N F O N Cl HO O N O N O O N O N Cl O NH O NH … Cl N N O 100 suggestions
  23. 23. Knowledge-based Drug Design Example 2 Processing Information • 80 new reactions identified • 10 Identical matches • 8 suggested products with a Tanimoto distance <0.2 • 2 abstraction errors (knime) but… it’s not enough for compound design…
  24. 24. Knowledge-based Drug Design Example 2 (part II) N Cl N O Core Structure (Diazepam) 80 new suggested reactions/products versus Reaxys substructure search 2564 related compounds
  25. 25. Knowledge-based Drug Design Example 2 (part II) • Fingerprints calculated • Identical compounds filtered off (Tanimoto = 1) • 13 suggested products with a Tanimoto 0.7-0.9 • Physicochemical properties calculated and compared New “suggested” molecules show similar properties to the known-ones
  26. 26. Knowledge-based Drug Design Example 3 Cl N O N N Cl HN O O Intermediate* used for ICSynth FRP and Reaxys sss Loxapine® • 61 suggestions ICSYNTH FRP (one synthetic step away from intermediate) • 922 related compounds in the literature (Loxapine included) • 6 new compounds with Tanimoto distance between 0.5-0.9 were suggested N O R N N Cl O * Not real precursor for the final molecule N N Cl Ar Z O NH Cl Ar O X Cl
  27. 27. One more thing… building synthetic confidence filtering ICSYNTH cpds with low synthetic background • number of precedent reactions of the same type • precedent yield reported • level of similarity from the original reaction
  28. 28. Summary
  29. 29. ACKNOWLEDGMENTS InfoChem Peter Loew Heinz Saller Christoph Oppawsky Mike Hutchings Hans Kraut Valentina Eigner-Pitto Josef Eiblmaier Ulf Frieske Stephanie North Chemnotia Anders Bogevig Tobias Rein THANK YOU

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