In Silico Drug Targets Identification Of Mycobacterium Leprae

Abstract

Leprosy remains the leading cause of mortality due to the bacterial pathogen. Recently there has been increase in the number of multi-drug resistance strains for this pathogen, Mycobacterium leprae. This precipitates the need for exploration of new potential anti-mycobacterial targets in order to design and synthesize novel and potential anti mycobacterial agents. Various bioinformatics tools have driven the comparative analysis of the genome sequences between species and within isolates. While drawing meaning conclusions from a large amount of raw material, computer-aided identification of suitable targets for further experimental analysis and characterization, has also led to the prediction of non-human homologous essential genes in bacteria as promising candidates for novel ill discovery. So this purpose we have adopted a systems approach for the analysis of Mycobacterium leprae. This would help in designing new anti-mycobacterial agents. Here, we present a comparative genomic analysis to identify essential genes of Mycobacterium leprae. Our In Silico prediction has identified 620 essential genes from DEG. These essential genes sequence from DEG were subjected to human genome. Finally, in this process we identified 34 genes which could also be potential drug candidates. These genes encode essential proteins to support the survival of Mycobacterium leprae including outer-inner membrane and surface structures, regulators, proteins involved pathogenenicity, adaptation, chaperones as well as degradation of small and macromolecules energy metabolism, information transfer, central/intermediate/miscellaneous metabolic pathways and some conserved hypothetical proteins of unknown function. Therefore, our In Silico approach has enabled rapid screening and identification of potential drug targets for further characterization in the laboratory.