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.
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.
authors: Department of Computer Science, Sardar Patel University, Vallabh Vidyanagar, 388120, Gujarat, India.
authors: Megha
authors: M
authors: Vaidya
authors: Department of Computer Science, Sardar Patel University, Vallabh Vidyanagar, 388120, Gujarat, India.
authors: Hetalkumar
authors: H
authors: Panchal
mesh_terms: D000595:Amino Acid Sequence; D000900:Anti-Bacterial Agents / Q000737:chemistry*; D001426:Bacterial Proteins / Q000737:chemistry* / Q000235:genetics; D001665:Binding Sites; D049109:Cell Proliferation / Q000235:genetics; D057225:Data Mining; D030562:Databases, Protein; D015195:Drug Design; D018390:Gene Targeting / Q000379:methods; D016480:Helicobacter pylori / Q000502:physiology*; D008956:Models, Chemical; D062105:Molecular Docking Simulation / Q000379:methods*; D008969:Molecular Sequence Data; D011485:Protein Binding; D020539:Sequence Analysis, Protein / Q000379:methods*
chemical_list: D000900:Anti-Bacterial Agents; D001426:Bacterial Proteins
keywords: Helicobacter pylori J99; MurA; bioinformatics; docking; drug targets; ligands; protein modelling; subtractive study; target genes; target identification