Proteomic Approaches to Studying Drug Targets and Resistance in Plasmodium
R. A. Cooper and D. J. Carucci
Affiliation: Department of Biological Sciences, 110 Mills Godwin Bldg. / 45th Street. Old Dominion University,Norfolk VA 23529, USA.
Ever increasing drug resistance by Plasmodium falciparum, the most virulent of human malaria parasites, is creating new challenges in malaria chemotherapy. The entire genome sequences of P. falciparum and the rodent malaria parasite, P. yoelii yoelii are now available. Extensive genome sequence data from other Plasmodium species including another important human malaria parasite, P. vivax are also available. Powerful research techniques coupled to genomic resources are needed to help identify new drug and vaccine targets against malaria. Applied to Plasmodium, proteomics combines high-resolution protein or peptide separation with mass spectrometry and computer software to rapidly identify large numbers of proteins expressed from various stages of parasite development. Proteomic methods can be applied to study sub-cellular localization, cell function, organelle composition, changes in protein expression patterns in response to drug exposure, drug-protein binding and validation of data from genomic annotation and transcript expression studies. Recent high-throughput proteomic approaches have provided a wealth of protein expression data on P. falciparum, while smaller-scale studies examining specific drug-related hypotheses are also appearing. Of particular interest is the study of mechanisms of action and resistance of drugs such as the quinolines, whose targets currently may not be predictable from genomic data. Coupling the Plasmodium sequence data with bioinformatics, proteomics and RNA transcript expression profiling opens unprecedented opportunities for exploring new malaria control strategies. This review will focus on pharmacological research in malaria and other intracellular parasites using proteomic techniques, emphasizing resources and strategies available for Plasmodium.
Keywords: malaria, parasite, mass Spectrometry, genomics
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