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Cheminformatics &  The evolving relationship between data in the public domain & pharma Dana Vanderwall Cheminformatics, Bristol-Myers Squibb
How do we start to find a new chemical that might be the next drug? ,[object Object],[object Object],[object Object],[object Object]
This is where drug discovery gets  really  modern ,[object Object]
Compound optimization ,[object Object],[object Object],1-3 years >2 million   compounds   tested in primary assay Make another 2-10,000
Getting ready for the clinic ,[object Object],[object Object],[object Object],[object Object],[object Object],1-3 years 2-3 years
Profiling Assays and Lead Op Progression 2M 2K 200 1-10 1 2-5 10-50 300-600 HTS Hit Triage Early Lead Op Late Lead Op Target to Hit  Hit to Lead   Lead to Candidate # Compounds # Assays
Chemical Structures are the Intellectual Property ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
GlaxoSmithKline moves to stimulate public-private partnerships for R&D in neglected tropical diseases ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Malaria ,[object Object],[object Object],[object Object],http://www.mcwhealthcare.com/malaria_drugs_medicines/life_cycle_of_plasmodium.htm
The Complexity of Cell Biology The assumption is: One target    One consequence Target ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Target
Emerging paradigm- look for the cellular activity first ,[object Object],[object Object],[object Object]
Supporting black-box HTS for anti-malarials ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],F-J Gamo  et al.   Nature   465 , 305-310 (2010) doi:10.1038/nature09107
Characterizing the hits ,[object Object],[object Object],[object Object]
Three-dimensional plot of some of the  novel chemical diversity present in TCAMS F-J Gamo  et al.   Nature   465 , 305-310 (2010) doi:10.1038/nature09107
Characterizing the hits ,[object Object],[object Object],[object Object],[object Object]
Can we leverage the historical target data on compounds? ,[object Object],[object Object],Can we use the data to figure out which targets lead to which biological response? ? stimulant readout ,[object Object],[object Object],kinase_1 kinase_2 kinase_3 kinase_4 7TM_1 7TM_2 NR_3 NR_2 NR_1
Can we leverage the historical target data on compounds? ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Finding targets ‘enriched’ among the anti-malarials ,[object Object],[object Object],[object Object]
Narrowing down the possible candidates ,[object Object],[object Object],[object Object],>2 fold enrichment F-J Gamo  et al.   Nature   465 , 305-310 (2010) doi:10.1038/nature09107
Targets with homologues in  P. falciparum  genome Aspartic protease Methionyl-tRNA synthetase b-Ketoacid reductase Phenylalanyl-tRNA synthetase Calcium/calmodulin-dependent kinase Phosphatidylinositol 3-kinase Cysteine protease Plasmodium electron transport chain Dihydrofolate reductase Ribosome Dihydroorotate dehydrogenase Ser/Thr protein kinase DNA gyrase Tyrosyl-tRNA synthetase Isoleucyl-tRNA synthetase
Targets with NO homologues in  P. falciparum  genome GPCR: Adrenergic antag Nuclear Receptor ag/antag GPCR: Cannabanoid antag Ion Channel inh GPCR: Chemokine antag Phospholipse inh GPCR: Cholinergic ag Lipid amide hydrolase inh GPCR: Free Fatty Acid ag Serine protease inh GPCR: Serotonin ag/antag Toll-like receptor ag GPCR: Opiod ag/antag GPCR: Peptide hormone receptor ag/antag
Data publicly available ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
And the raw target data used to develop hypotheses? ,[object Object],[object Object],[object Object],[object Object],[object Object]
Surrogates for internal data ,[object Object],[object Object],[object Object],[object Object]
Acknowledgements Anti-malarial HTS ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

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Vanderwall cheminformatics Drexel Part 1

  • 1. Cheminformatics & The evolving relationship between data in the public domain & pharma Dana Vanderwall Cheminformatics, Bristol-Myers Squibb
  • 2.
  • 3.
  • 4.
  • 5.
  • 6. Profiling Assays and Lead Op Progression 2M 2K 200 1-10 1 2-5 10-50 300-600 HTS Hit Triage Early Lead Op Late Lead Op Target to Hit Hit to Lead Lead to Candidate # Compounds # Assays
  • 7.
  • 8.
  • 9.
  • 10.
  • 11.
  • 12.
  • 13.
  • 14. Three-dimensional plot of some of the novel chemical diversity present in TCAMS F-J Gamo et al. Nature 465 , 305-310 (2010) doi:10.1038/nature09107
  • 15.
  • 16.
  • 17.
  • 18.
  • 19.
  • 20. Targets with homologues in P. falciparum genome Aspartic protease Methionyl-tRNA synthetase b-Ketoacid reductase Phenylalanyl-tRNA synthetase Calcium/calmodulin-dependent kinase Phosphatidylinositol 3-kinase Cysteine protease Plasmodium electron transport chain Dihydrofolate reductase Ribosome Dihydroorotate dehydrogenase Ser/Thr protein kinase DNA gyrase Tyrosyl-tRNA synthetase Isoleucyl-tRNA synthetase
  • 21. Targets with NO homologues in P. falciparum genome GPCR: Adrenergic antag Nuclear Receptor ag/antag GPCR: Cannabanoid antag Ion Channel inh GPCR: Chemokine antag Phospholipse inh GPCR: Cholinergic ag Lipid amide hydrolase inh GPCR: Free Fatty Acid ag Serine protease inh GPCR: Serotonin ag/antag Toll-like receptor ag GPCR: Opiod ag/antag GPCR: Peptide hormone receptor ag/antag
  • 22.
  • 23.
  • 24.
  • 25.