title: In silico prediction of drug targets in Vibrio cholerae.
abstract: Identification of potential drug targets is the first step in the process of modern drug discovery, subjected to their validation and drug development. Whole genome sequences of a number of organisms allow prediction of potential drug targets using sequence comparison approaches. Here, we present a subtractive approach exploiting the knowledge of global gene expression along with sequence comparisons to predict the potential drug targets more efficiently. Based on the knowledge of 155 known virulence and their coexpressed genes mined from microarray database in the public domain, 357 coexpressed probable virulence genes for Vibrio cholerae were predicted. Based on screening of Database of Essential Genes using blastn, a total of 102 genes out of these 357 were enlisted as vitally essential genes, and hence good putative drug targets. As the effective drug target is a protein which is only present in the pathogen, similarity search of these 102 essential genes against human genome sequence led to subtraction of 66 genes, thus leaving behind a subset of 36 genes whose products have been called as potential drug targets. The gene ontology analysis using Blast2GO of these 36 genes revealed their roles in important metabolic pathways of V. cholerae or on the surface of the pathogen. Thus, we propose that the products of these genes be evaluated as target sites of drugs against V. cholerae in future investigations.
authors.affiliation: Department of Bioscience and Biotechnology, Banasthali University, Banasthali, 304022, India. pmkatara@gmail.com
authors.forename: Pramod
authors.initials: P
authors.lastname: Katara
authors.forename: Atul
authors.initials: A
authors.lastname: Grover
authors.forename: Himani
authors.initials: H
authors.lastname: Kuntal
authors.forename: Vinay
authors.initials: V
authors.lastname: Sharma
mesh_terms: D000900:Anti-Bacterial Agents / Q000737:chemistry; D016000:Cluster Analysis; D019295:Computational Biology; D057225:Data Mining; D030541:Databases, Genetic; D015195:Drug Design; D020869:Gene Expression Profiling; D005798:Genes, Bacterial; D016366:Open Reading Frames; D014734:Vibrio cholerae / Q000187:drug effects / Q000235:genetics* / Q000472:pathogenicity; D014774:Virulence
chemical_list: D000900:Anti-Bacterial Agents