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In silico genome‐scale modeling and analysis for identifying anti‐tubercular drug targets
Author(s) -
Lee DongYup,
Chung Bevan Kai Sheng,
Yusufi Faraaz N.K.,
Selvarasu Suresh
Publication year - 2011
Publication title -
drug development research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.582
H-Index - 60
eISSN - 1098-2299
pISSN - 0272-4391
DOI - 10.1002/ddr.20408
Subject(s) - in silico , computational biology , identification (biology) , context (archaeology) , drug discovery , genome , tuberculosis , drug , biology , mycobacterium tuberculosis , drug resistance , bioinformatics , genetics , gene , medicine , pharmacology , paleontology , botany , pathology
Mycobacterium tuberculosis is the deadly pathogen responsible for causing tuberculosis in humans, continuing to infect and kill millions of people globally. Despite the availability of a number of anti‐tuberculosis drugs and advances in high‐throughput drug discovery technology there is an urgent need for designing novel anti‐tubercular treatments due to growing parasite resistance and compromised immune systems in some patients. Therefore, it is highly necessary to develop systematic approaches that can facilitate the drug discovery by identification of drug targets in effective and efficient ways. In this sense, with the availability of whole genome sequence, application of genome‐scale modeling is becoming increasingly important for deriving rational drug target identification. This approach is indeed powerful in unraveling the metabolic behavior of pathogens and helps in identifying most relevant metabolites/genes as drug targets, which are experimentally testable. Herein, we present a review on the application of genome‐scale modeling and analysis in the context of identification of anti‐tubercular drug targets. Drug Dev Res 72: 121–129, 2011. © 2010 Wiley‐Liss, Inc.