Prediction of the P. falciparum Target Space Relevant to Malaria Drug Discovery

Abstract

Malaria is still one of the most devastating infectious diseases, affecting hundreds of millions of patients worldwide. Even though there are several established drugs in clinical use for malaria treatment, there is an urgent need for new drugs acting through novel mechanisms of action due to the rapid development of resistance. Resistance emerges when the parasite manages to mutate the sequence of the drug targets to the extent that the protein can still perform its function in the parasite but can no longer be inhibited by the drug, which then becomes almost ineffective. The design of a new generation of malaria drugs targeting multiple essential proteins would make it more difficult for the parasite to develop full resistance without lethally disrupting some of its vital functions. The challenge is then to identify which set of Plasmodium falciparum proteins, among the millions of possible combinations, can be targeted at the same time by a given chemotype. To do that, we predicted first the targets of the close to 20,000 antimalarial hits identified recently in three independent phenotypic screening campaigns. All targets predicted were then projected onto the genome of P. falciparum using orthologous relationships. A total of 226 P. falciparum proteins were predicted to be hit by at least one compound, of which 39 were found to be significantly enriched by the presence and degree of affinity of phenotypically active compounds. The analysis of the chemically compatible target combinations containing at least one of those 39 targets led to the identification of a priority set of 64 multi-target profiles that can set the ground for a new generation of more robust malaria drugs.

Author Summary

There is an urgent need for new antimalarials acting through novel mechanisms of action that can overcome the increasing incidence of resistance observed for currently used drugs. In this respect, drug polypharmacology is emerging as an attractive strategy to reduce the chances of the parasite evolving drug resistance. Although there were close to 20,000 antimalarial hits recently identified from three independent phenotypic screenings, the molecular targets through which most of those active compounds exert their antimalarial action are unfortunately unknown at present. To address this issue, a computational approach was first used to predict their protein targets. Statistical analyses were applied to detect any enrichment of phenotypically active compounds in P. falciparum targets, leading to a final list of 39 putative high-priority targets for malaria drug discovery. The presence of at least one high-priority target in the target profile predicted for the antimalarial hits was then used as a constraint to identify a priority set of 64 multi-target profiles. Multi-target strategies based on such profiles can set the basis for designing a next generation of more robust malaria drugs.