School of Pharmacy, University College London, London WC1N 1AX, U.K.
Exscientia Ltd., The Schrödinger Building, Oxford Science Park, Oxford OX4 4GE, U.K.
J Med Chem. 2021 Nov 25;64(22):16450-16463. doi: 10.1021/acs.jmedchem.1c00313. Epub 2021 Nov 8.
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.
开源疟疾(OSM)联盟正在开发通过靶向寄生虫表面的必需离子泵 ATP4 来杀死人类疟疾寄生虫的化合物。ATP4 的结构尚未确定。在这里,我们描述了一项公开竞赛,旨在开发一种用于鉴定 ATP4 抑制剂的预测模型,从而降低与合成无活性化合物相关的项目成本。竞赛参与者可以在提交时看到所有条目。在最后一轮,由专门从事机器学习方法的私营部门参赛者参加,表现最佳的模型用于预测新的抑制剂,其中一些被合成并针对寄生虫进行了评估。有一半具有生物活性,其中一个具有一种模式,人类化学家熟悉这个系列的人可能会认为这是“不明智的”。由于所有数据和参与者的交互都保留在公共领域,因此这个研究项目“仍然存在”,并且其他人可以对其进行改进。