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ICIC 2017: Freeware and public databases: Towards a Wiki Drug Discovery?

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Fernando Huerta (RISE Bioscience & Materials, SE)
Alexander Minidis (Collaborative Drug Discovery - CDD VAULT, Sweden)
How much information does the scientists need to design new potential drugs?

A thorough overview of public scientific information sources (open access) and methods to collect, process, analyse and visualize this information will be presented. A direct application of such free available information in conjunction with freeware will be described in relation with the efforts of the scientific community to find effective medicines for the ZIKA virus.

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ICIC 2017: Freeware and public databases: Towards a Wiki Drug Discovery?

  1. 1. Research Institutes of Sweden FREEWARE & OPEN ACCESS DATABASES Fernando F Huerta Process and Pharmaceutical Development Division Bioscience and Materials High T&P Towards a Wiki Drug Discovery?
  2. 2. Research Institutes of Sweden Process and Pharmaceutical Development Division Bioscience and Materials High T&P
  3. 3. Research Institutes of Sweden FREEWARE & OPEN ACCESS DATABASES Fernando F Huerta Process and Pharmaceutical Development Division Bioscience and Materials High T&P Towards a Wiki Drug Discovery?
  4. 4. Is it possible to use “free” accesible information to run a drug design project? BACKGROUND
  5. 5. WHAT DO WE NEED? 1.What 2.Where 3.How 4.Example 5.Reference
  6. 6. WHAT DO WE NEED? 1.Drug Design 2.Where 3.How 4.Example 5.Reference
  7. 7. WHAT DO WE NEED? 1.Drug Design 2.Information 3.How 4.Example 5.Reference
  8. 8. WHAT DO WE NEED? 1.Drug Design 2.Information 3.Mining 4.Example 5.Reference
  9. 9. WHAT DO WE NEED? 1.Drug Design 2.Information 3.Mining 4.Zika 5.Reference
  10. 10. WHAT DO WE NEED? 1.Drug Design 2.Information 3.Mining 4.Zika 5.Reference FREE VS COMMERCIAL
  11. 11. Commercial SystemsFree / Open Source Systems FREE vs COMMERCIAL
  12. 12. WHAT DO WE NEED? 1.What 2.Where 3.How 4.Example 5.Reference
  13. 13. The Big Picture DRUG DISCOVERY & MOLECULAR PROPERTIES
  14. 14. DRUG DISCOVERY & MOLECULAR PROPERTIES
  15. 15. DRUG DISCOVERY & MOLECULAR PROPERTIES ENTER SYSTEMIC CIRCULATION (ABSORPTION)
  16. 16. DRUG DISCOVERY & MOLECULAR PROPERTIES TISSUE/ORGAN DISTRIBUTION
  17. 17. DRUG DISCOVERY & MOLECULAR PROPERTIES CELLULAR PERMEABILITY
  18. 18. DRUG DISCOVERY & MOLECULAR PROPERTIES BIND TO RECEPTOR
  19. 19. DRUG DISCOVERY & MOLECULAR PROPERTIES ELIMINATION
  20. 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. 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. 22. Chemical & Biological properties 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. 23. one more thing…
  24. 24. one more thing… Nature HTS Analogy Chemical Evolution Structures and associated data
  25. 25. WHAT DO WE NEED? 1.What 2.Where 3.How 4.Example 5.Reference
  26. 26. 1.What 2.Where 3.How 4.Example 5.Reference WHERE TO FIND THE INFORMATION Information Sources (open access) - easy integration with analytical platforms (free and commercial) - most popular (and up to date) … and many more
  27. 27. 1.What 2.Where 3.How 4.Example 5.Reference WHERE TO FIND THE INFORMATION ▪ Free ▪ NCBI ▪ FTP / API ▪ BioAssay / Compounds
  28. 28. 1.What 2.Where 3.How 4.Example 5.Reference WHAT DO WE NEED?
  29. 29. 1.What 2.Where 3.How 4.Example 5.Reference WHAT DO WE NEED? Data Mining & Visualization (open access) www.predictiveanalyticstoday.com
  30. 30. 1.What 2.Where 3.How 4.Example 5.Reference WHAT DO WE NEED? Data Mining & Visualization (open access) ▪ Popular ▪ User community ▪ Integration ▪ Compounds & reactions ▪ Flexible (applications)
  31. 31. 1.What 2.Where 3.How 4.Example 5.Reference WHAT DO WE NEED? … we do not have own data to compare with…
  32. 32. 1.What 2.Where 3.How 4.Example 5.Reference WHAT DO WE NEED? … 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. 33. 1.What 2.Where 3.How 4.Example 5.Reference WHAT DO WE NEED? … we do not have own data to compare with… STRUCTURAL ANALYSIS + ASSOCIATED DATA
  34. 34. 1.What 2.Where 3.How 4.Example 5.Reference WHAT DO WE NEED?
  35. 35. WHAT DO WE NEED? 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. 36. ZIKA: OPEN ACCESS DRUG 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. 37. ZIKA: OPEN ACCESS DRUG 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. 38. ZIKA: OPEN ACCESS DRUG 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. 39. ZIKA: OPEN ACCESS DRUG 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. 40. ZIKA: OPEN ACCESS DRUG 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. 41. ZIKA: OPEN ACCESS DRUG 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. 42. ZIKA: OPEN ACCESS DRUG 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. 43. 1.What 2.Where 3.How 4.Example 5.Reference WHAT DO WE NEED?
  44. 44. 1.What 2.Where 3.How 4.Example 5.Reference WHAT DO WE NEED? REAXYS API
  45. 45. 1.What 2.Where 3.How 4.Example 5.Reference WHAT DO WE NEED? REAXYS API ▪ CDKi’s ca 40000 structures (25x more) ▪ KIF11 inhibitors ca 4000 structures (1000 less) ▪ Equal amount of data ▪ Same conclusions
  46. 46. OUR ANSWERS Quality Accessibility Up to Date but … Is it possible to use “free” accesible information to run a drug design project? YES
  47. 47. OUR ANSWERS Towards a Wiki Drug Discovery? NO All others Unmet medical needs Orphan diseases YES Neglected diseases (Malaria)
  48. 48. FREE vs COMMERCIAL Commercial SystemsFree / Open Source Systems YOUR TASTE! YOUR NEEDS!
  49. 49. ICIC Heidelberg, October 23-24, 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!

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