Prediction of the P. falciparum target space relevant to malaria drug discovery

PLoS Comput Biol. 2013;9(10):e1003257. doi: 10.1371/journal.pcbi.1003257. Epub 2013 Oct 17.


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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Antimalarials / chemistry
  • Antimalarials / metabolism
  • Computational Biology / methods*
  • Computer Simulation
  • Databases, Protein
  • Drug Discovery / methods*
  • Plasmodium falciparum / chemistry*
  • Protozoan Proteins / chemistry
  • Protozoan Proteins / metabolism


  • Antimalarials
  • Protozoan Proteins

Grant support

This work was supported by the Medicines for Malaria Venture (project no. MMV 12/0069), the Spanish Instituto de Salud Carlos III (Drugs4Rare project within the framework of the International Rare Disease Research Consortium), and the Spanish Ministerio de Ciencia e Innovación (project BIO2011-26669). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.