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ICIC 2017: Freeware and public databases: Towards a Wiki Drug Discovery?
The document discusses the potential of using free and open-access databases in drug design and discovery, highlighting various information sources and the integration of analytical platforms. It emphasizes the importance of data mining and visualization in identifying candidate drugs, particularly in the context of the Zika virus. Ultimately, it suggests that while challenges exist, utilizing accessible information for drug design projects is feasible.
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ICIC 2017: Freeware and public databases: Towards a Wiki Drug Discovery?
- 1. Research Institutes ofSweden FREEWARE & OPEN ACCESS DATABASES Fernando F Huerta Process and Pharmaceutical Development Division Bioscience and Materials High T&P Towards a Wiki Drug Discovery?
- 2. Research Institutes ofSweden Process and Pharmaceutical Development Division Bioscience and Materials High T&P
- 3. Research Institutes ofSweden FREEWARE & OPEN ACCESS DATABASES Fernando F Huerta Process and Pharmaceutical Development Division Bioscience and Materials High T&P Towards a Wiki Drug Discovery?
- 4. Is it possibleto use “free” accesible information to run a drug design project? BACKGROUND
- 5. WHAT DO WENEED? 1.What 2.Where 3.How 4.Example 5.Reference
- 6. WHAT DO WENEED? 1.Drug Design 2.Where 3.How 4.Example 5.Reference
- 7. WHAT DO WENEED? 1.Drug Design 2.Information 3.How 4.Example 5.Reference
- 8. WHAT DO WENEED? 1.Drug Design 2.Information 3.Mining 4.Example 5.Reference
- 9. WHAT DO WENEED? 1.Drug Design 2.Information 3.Mining 4.Zika 5.Reference
- 10. WHAT DO WENEED? 1.Drug Design 2.Information 3.Mining 4.Zika 5.Reference FREE VS COMMERCIAL
- 11. Commercial SystemsFree /Open Source Systems FREE vs COMMERCIAL
- 12. WHAT DO WENEED? 1.What 2.Where 3.How 4.Example 5.Reference
- 13. The Big Picture DRUGDISCOVERY & MOLECULAR PROPERTIES
- 14. DRUG DISCOVERY &MOLECULAR PROPERTIES
- 15. DRUG DISCOVERY &MOLECULAR PROPERTIES ENTER SYSTEMIC CIRCULATION (ABSORPTION)
- 16. DRUG DISCOVERY &MOLECULAR PROPERTIES TISSUE/ORGAN DISTRIBUTION
- 17. DRUG DISCOVERY &MOLECULAR PROPERTIES CELLULAR PERMEABILITY
- 18. DRUG DISCOVERY &MOLECULAR PROPERTIES BIND TO RECEPTOR
- 19. DRUG DISCOVERY &MOLECULAR PROPERTIES ELIMINATION
- 20. DRUG DISCOVERY &MOLECULAR PROPERTIES Pharmaco-kinetics & Pharmaco-dynamics ENTER SYSTEMIC CIRCULATION (ABSORPTION) TISSUE/ORGAN DISTRIBUTION CELLULAR PERMEABILITY BIND TO RECEPTOR ELIMINATION BIOLOGICAL PROPERTIES (measured) STRUCTURAL PROPERTIES PHYSICO CHEMICAL PROPERTIES (calculated) Chemical & Biological properties
- 21. DRUG DISCOVERY &MOLECULAR PROPERTIES Pharmaco-kinetics & Pharmaco-dynamics ENTER SYSTEMIC CIRCULATION (ABSORPTION) TISSUE/ORGAN DISTRIBUTION CELLULAR PERMEABILITY BIND TO RECEPTOR ELIMINATION BIOLOGICAL PROPERTIES (measured) STRUCTURAL PROPERTIES PHYSICO CHEMICAL PROPERTIES (calculated) Chemical & Biological properties CORRELATIONS
- 22. Chemical & Biologicalproperties Data Mining Available information (building correlations) New Potential Candidate Drug DRUG DISCOVERY & MOLECULAR PROPERTIES CORRELATIONS Structural Solubility logP / logD pKa PSA Docking exp* Lipinski Calculated Experimental Potency Selectivity caco2 Metabolism herg
- 23.
- 24. one more thing… Nature HTS Analogy ChemicalEvolution Structures and associated data
- 25. WHAT DO WENEED? 1.What 2.Where 3.How 4.Example 5.Reference
- 26. 1.What 2.Where 3.How 4.Example 5.Reference WHERE TO FINDTHE INFORMATION Information Sources (open access) - easy integration with analytical platforms (free and commercial) - most popular (and up to date) … and many more
- 27. 1.What 2.Where 3.How 4.Example 5.Reference WHERE TO FINDTHE INFORMATION ▪ Free ▪ NCBI ▪ FTP / API ▪ BioAssay / Compounds
- 28.
- 29. 1.What 2.Where 3.How 4.Example 5.Reference WHAT DO WENEED? Data Mining & Visualization (open access) www.predictiveanalyticstoday.com
- 30. 1.What 2.Where 3.How 4.Example 5.Reference WHAT DO WENEED? Data Mining & Visualization (open access) ▪ Popular ▪ User community ▪ Integration ▪ Compounds & reactions ▪ Flexible (applications)
- 31. 1.What 2.Where 3.How 4.Example 5.Reference WHAT DO WENEED? … we do not have own data to compare with…
- 32. 1.What 2.Where 3.How 4.Example 5.Reference WHAT DO WENEED? … drugs for the same target look alike… Norfloxacin (Noroxin™) Ciprofloxacin (Cipro™) Sparfloxacin (Zagam™) Grepafloxacin (Raxar™) Nexium® Rabeprazole® Pantoprazole® Seroquel®Loxapine® Drug Discovery Today 2011, 16, 722 Drug Discovery Today 2011, 16, 779
- 33. 1.What 2.Where 3.How 4.Example 5.Reference WHAT DO WENEED? … we do not have own data to compare with… STRUCTURAL ANALYSIS + ASSOCIATED DATA
- 34.
- 35. WHAT DO WENEED? 1.What 2.Where 3.How 4.Example 5.Reference www.healthmap.org Spread by the bite of Aedes species mosquito Harmless symptoms Transferred to fetus (birth defects) 1947 and 2016 No vaccine / medicine ZIKA VIRUS
- 36. ZIKA: OPEN ACCESSDRUG DISCOVERY PROJECT www.openzika.ufg.br http://bioinfo.imtech.res.in/manojk/zikavr/index.php Collection of biological & chemical data 464 potential drug targets Direct mining possible (not straightforward) Download data for external mining www.nature.com/scientificreports (DOI: 10.1038/srep32713) ZIKA Genome Known Viruses Genome Comparison Potential Candidate Drugs FDA approved ready for clinical trials
- 37. ZIKA: OPEN ACCESSDRUG DISCOVERY PROJECT DB01693 DB01752 DB03996 DB04331 DB07064 DB08032 DB08033 DB08037 DB08198 DB08239 DB08244 DB08246 DB08250 DB04473 http://bioinfo.imtech.res.in/manojk/zikavr/index.php 3 main biological targets: Interleukin-4-receptor subunit alpha Genome polyprotein Kinesin-like protein KIF11 1 structural “coincidence” 6 Molecules share the same subgraph
- 38. ZIKA: OPEN ACCESSDRUG DISCOVERY PROJECT Nature Medicine, vol 22, 10, 2016, 1101 (doi:10.1038/nm.4184 ) Emricasan PHA-690509 Niclosamide pan-caspase inhibitor neuroprotective activity not suppress ZIKV replication cyclic-dependent kinase inhibitor (CDKi)* antiviral activity FDA-approved drug treatment of worm infections *Ten structurally unrelated CDKis inhibit ZIKA replication
- 39. ZIKA: OPEN ACCESSDRUG DISCOVERY PROJECT Taken together … 1 structural “coincidence” ▪ Interleukin-4-receptor subunit alpha ▪ Genome polyprotein ▪ Kinesin-like protein KIF11 cyclic-dependent kinase inhibitor (CDKi) Nature Medicine 22, 10, 2016, 1101http://bioinfo.imtech.res.in/manojk/zikavr/index.php Ten structurally unrelated CDKis inhibit ZIKA replication 1. Search bioactives related to the subgraph 2. Search for KIF11 inhibitors (Structural comparison) 3. Search for CDK inhibitors (Structural comparison) subgraph http://www.pharmakarma.org/
- 40. ZIKA: OPEN ACCESSDRUG DISCOVERY PROJECT CDKi’s (27 molecules) Nature Medicine 22, 10, 2016, 1101 13/27 11/27 4/27 Ten structurally unrelated CDKis inhibit ZIKA replication 257 structurally unrelated CDKi’s (based on subgraph) …structures and bio-assay data available 1452 CDKi’s found (CDK1-CDK20) http://www.pharmakarma.org/
- 41. ZIKA: OPEN ACCESSDRUG DISCOVERY PROJECT 14 Molecules in www.drugbank.ca 1 structural “coincidence” ▪ Interleukin-4-receptor subunit alpha ▪ Genome polyprotein ▪ Kinesin-like protein KIF11 http://bioinfo.imtech.res.in/manojk/zikavr/ index.php subgraph http://www.pharmakarma.org/ 7/14 6/14 0/5776 KIF11 inhibitors found: Graph analogues found: 1100 ▪ 18 reported as Kinesin like protein 1 ▪ Kinesin superfamily (non-standard names) ▪ >1000 compounds (Tanimoto >0.7)
- 42. ZIKA: OPEN ACCESSDRUG DISCOVERY PROJECT Nature Medicine 22, 10, 2016, 1101 http://bioinfo.imtech.res.in/manojk/zikavr/index.php Match Pairs SAR Lipinski R-Group Decomposition Pharmacophore Summary ▪ Analogues with same subgraph (Tanimoto >0.7) ▪ Non related structures active on same targets ▪ Bioassay data ▪ Other analysis possible
- 43.
- 44. 1.What 2.Where 3.How 4.Example 5.Reference WHAT DO WENEED? REAXYS API
- 45. 1.What 2.Where 3.How 4.Example 5.Reference WHAT DO WENEED? REAXYS API ▪ CDKi’s ca 40000 structures (25x more) ▪ KIF11 inhibitors ca 4000 structures (1000 less) ▪ Equal amount of data ▪ Same conclusions
- 46. OUR ANSWERS Quality Accessibility Up toDate but … Is it possible to use “free” accesible information to run a drug design project? YES
- 47. OUR ANSWERS Towards aWiki Drug Discovery? NO All others Unmet medical needs Orphan diseases YES Neglected diseases (Malaria)
- 48. FREE vs COMMERCIAL CommercialSystemsFree / Open Source Systems YOUR TASTE! YOUR NEEDS!
- 49. ICIC Heidelberg, October23-24, 2017 • CHEMNOTIA • REAXYS • PUBCHEM • KNIME (& Contributors) • Alexander Minidis, PhD Collaborative Drug Discovery www.pharmakarma.org/blog ACKNOWLEDGEMTS Research Institutes of Sweden Process and Pharmaceutical Development Division Bioscience and Materials THANK YOU!