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, G. J. Conduit, Mykola Galushka, Davy Guan, Irene Hallyburton, Benedict 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. Robertson, Vito Spadavecchio, Vasileios Tatsis, Willem P. van Hoorn, Alexander D. Wade, Thomas M. Whitehead, Paul Willis, Matthew H. Todd
Abstract
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.