Computer assisted searches for drug targets with emphasis on malarial proteases and their inhibitors.
The creation of databases that make enormous and diverse amounts of information available, the coding of algorithms that allow the collection and investigation of these data and the wide availability of desktop computers capable of handling the data and running the algorithms have set the stage for innovative approaches to drug target identification. Here we review the main currents in this new field, providing an overview of some of the databases and software used to generate and shorten the lists of potential drug targets using in silico methods. As a case study, we look at the identification and investigation of malarial proteases as therapeutic targets in the Plasmodium spp. parasites.
Wang
Yufeng
Y
Department of Biology, University of Texas at San Antonio, 6900 North Loop 1604 West, San Antonio, Texas 78249, USA. ywang@utsa.edu
Wu
Yimin
Y
D000465:Algorithms; D000818:Animals; D000962:Antimalarials / Q000494:pharmacology*; D005075:Biological Evolution; D019295:Computational Biology; D003201:Computers; D016208:Databases, Factual; D015195:Drug Design; D010450:Endopeptidases / Q000187:drug effects*; D018503:Genome, Protozoan; D023281:Genomics; D006801:Humans; D008288:Malaria / Q000188:drug therapy; D016778:Malaria, Falciparum / Q000188:drug therapy; D010963:Plasmodium falciparum / Q000187:drug effects; D011480:Protease Inhibitors / Q000494:pharmacology*; D040901:Proteomics; D012984:Software
D000962:Antimalarials; D011480:Protease Inhibitors; D010450:Endopeptidases