Comparative genomics study of Salmonella Typhimurium LT2 for the identification of putative therapeutic candidates. (21st March 2015)

• Record Type: Journal Article
• Authors: Samal, Himanshu Bhusan; Prava, Jyoti; Suar, Mrutyunjay; Mahapatra, Rajani Kanta
• Is Part Of: Journal of theoretical biology. Volume 369(2015)
• Page Start: 67
• Page End: 79
• Publication Date: 2015-03-21
• Subjects: S. Typhimurium LT2 -- Comparative genomics -- Metabolic pathways -- Drug targets -- Antibiotics; Biology -- Periodicals; Biological Science Disciplines -- Periodicals; Biology -- Periodicals; Biologie -- Périodiques; Theoretische biologie; Biology; Periodicals; 571.05
• DOI: 10.1016/j.jtbi.2015.01.022
• Languages: English
• ISSNs: 0022-5193

Abstract

Abstract: A computational, comparative genomics workflow was defined for the identification of novel therapeutic candidates against Salmonella Typhimurium LT2, with the aim that the selected targets should be essential to the pathogen, and have no homology with the human host. Bioinformatics analysis identified 43 proteins as non-host essential, which could serve as potential drug and vaccine targets. Additional prioritization parameters characterized 13 proteins as vaccine candidates while druggability of each of the identified proteins was evaluated by the Drug Bank database prioritized same number proteins suitable for drug targets. As a case study we built a homology model of one of the potential drug targets MurD ligase using MODELLER (9v12) software. The model has been further explored for in silico docking study with the inhibitors having druggability potential from the Drug Bank database. Results from this study could facilitate selective S. Typhimurium LT2 proteins for drug design and vaccine production pipelines. Highlights: Drug and vaccine targets prediction in S. Typhimurium LT2 through comparative genomics. 43 Non-homologous essential proteins were identified. 13 Proteins were predicted as vaccine and drug targets, respectively. Homology modeling followed by in silico docking study of MurD enzyme.