A pH Fingerprint Assay to Identify Inhibitors of Multiple Validated and Potential Antimalarial Drug Targets.

New drugs with novel modes of action are needed to safeguard malaria treatment. In recent years, millions of compounds have been tested for their ability to inhibit the growth of asexual blood-stage Plasmodium falciparum parasites, resulting in the identification of thousands of compounds with antiplasmodial activity. Determining the mechanisms of action of antiplasmodial compounds informs their further development, but remains challenging. A relatively high proportion of compounds identified as killing asexual blood-stage parasites show evidence of targeting the parasite's plasma membrane Na+-extruding, H+-importing pump, PfATP4. Inhibitors of PfATP4 give rise to characteristic changes in the parasite's internal [Na+] and pH. Here, we designed a "pH fingerprint" assay that robustly identifies PfATP4 inhibitors while simultaneously allowing the detection of (and discrimination between) inhibitors of the lactate:H+ transporter PfFNT, which is a validated antimalarial drug target, and the V-type H+ ATPase, which was suggested as a possible target of the clinical candidate ZY19489. In our pH fingerprint assays and subsequent secondary assays, ZY19489 did not show evidence for the inhibition of pH regulation by the V-type H+ ATPase, suggesting that it has a different mode of action in the parasite. The pH fingerprint assay also has the potential to identify protonophores, inhibitors of the acid-loading Cl- transporter(s) (for which the molecular identity(ies) remain elusive), and compounds that act through inhibition of either the glucose transporter PfHT or glycolysis. The pH fingerprint assay therefore provides an efficient starting point to match a proportion of antiplasmodial compounds with their mechanisms of action.

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

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.