Title: To study percentage distribution of target genes encoding proteins of different classes in Helicobacter pylori strain J99 and identification of potential therapeutic targets to reduce its proliferation

Authors: Megha Vaidya; Hetalkumar Panchal

Addresses: Department of Computer Science, Sardar Patel University, Vallabh Vidyanagar, 388120, Gujarat, India ' Department of Computer Science, Sardar Patel University, Vallabh Vidyanagar, 388120, Gujarat, India

Abstract: Helicobacter pylori are one of the most common bacterial pathogens in humans whose seropositivity increases with age and low socio-economic status. Due to presence of its pathogenic-island causes chronic persistent and atrophic gastritis in adults and children that often culminate in development of gastric and duodenal ulcers. Studies indicate that infected individuals have two to sixfold increased risk of developing gastric cancer and mucosal associated lymphoid tissue lymphoma compared to their uninfected counterparts. The complete genome sequences have provided a plethora of potential drug targets. Subtractive study holds the promise of providing a conceptual framework for identification of potential drug targets and providing insights to understand the biological regulatory mechanisms in diseases, which are playing an increasingly important role in searching for novel drug targets from the information contained in genomics. In this paper, we discuss subtractive study approaches for identifying drug targets, with the emphasis on the modelling of target protein and docking of the modelled protein with probable ligand by using computational tools.

Keywords: MurA; Helicobacter pylori J99; subtractive study; docking; target identification; protein modelling; drug targets; ligands; bioinformatics; target genes.

DOI: 10.1504/IJBRA.2015.067335

International Journal of Bioinformatics Research and Applications, 2015 Vol.11 No.1, pp.1 - 9

Received: 29 May 2012
Accepted: 09 May 2013
Published online: 06 Feb 2015 *

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