An open drug discovery competition: experimental validation of predictive models in a series of novel antimalarials

Edwin G. Tse, Laksh Aithani, Mark Anderson, Jonathan Cardoso-Silva, Giovanni Cincilla, Gareth J. Conduit, Mykola Galushka, Davy Guan, Irene Hallyburton, Benedict W. J. Irwin, Kiaran Kirk, Adele M. Lehane, Julia C. R. Lindblom, Raymond Lui, Slade Matthews, James McCulloch, Alice Motion, Ho Leung Ng, Mario Öeren, Murray N. RobertsonVito Spadavecchio, Vasileios A. Tatsis, Willem P. van Hoorn, Alexander D. Wade, Thomas M. Whitehead, Paul Willis, Matthew H. Todd

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)
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The Open Source Malaria (OSM) consortium is developing compounds that kill the human malaria parasite, , by targeting ATP4, an essential ion pump on the parasite surface. The structure of ATP4 has not been determined. Here, we describe a public competition created to develop a predictive model for the identification of ATP4 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.
Original languageEnglish
Pages (from-to)16450-16463
Number of pages14
JournalJournal of Medicinal Chemistry
Issue number22
Early online date8 Nov 2021
Publication statusPublished - 25 Nov 2021


  • Plasmodium falciparum
  • predictive model
  • PfATP4 inhibitors


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