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An Open Drug Discovery Competition: Experimental Validation of Predictive Models in a Series of Novel Antimalarials.

Edwin G TseLaksh AithaniMark AndersonJonathan Cardoso-SilvaGiovanni CincillaGareth J ConduitMykola GalushkaDavy GuanIrene HallyburtonBenedict W J IrwinKiaran KirkAdele M LehaneJulia C R LindblomRaymond LuiSlade MatthewsJames McCullochAlice MotionHo-Leung NgMario ÖerenMurray N RobertsonVito SpadavecchioVasileios A TatsisWillem P van HoornAlexander D WadeThomas M WhiteheadPaul WillisMatthew H Todd
Published in: Journal of medicinal chemistry (2021)
The Open Source Malaria (OSM) consortium is developing compounds that kill the human malaria parasite, Plasmodium falciparum, by targeting PfATP4, an essential ion pump on the parasite surface. The structure of PfATP4 has not been determined. Here, we describe a public competition created to develop a predictive model for the identification of PfATP4 inhibitors, thereby reducing project costs associated with the synthesis of inactive compounds. Competition participants could see all entries as they were submitted. In the final round, featuring private sector entrants specializing in machine learning methods, the best-performing models were used to predict novel inhibitors, of which several were synthesized and evaluated against the parasite. Half possessed biological activity, with one featuring a motif that the human chemists familiar with this series would have dismissed as "ill-advised". Since all data and participant interactions remain in the public domain, this research project "lives" and may be improved by others.
Keyphrases
  • plasmodium falciparum
  • endothelial cells
  • drug discovery
  • machine learning
  • healthcare
  • quality improvement
  • induced pluripotent stem cells
  • pluripotent stem cells
  • big data
  • health insurance
  • drug induced