title: Computational methods to identify new antibacterial targets.
abstract: The development of resistance to all current antibiotics in the clinic means there is an urgent unmet need for novel antibacterial agents with new modes of action. One of the best ways of finding these is to identify new essential bacterial enzymes to target. The advent of a number of in silico tools has aided classical methods of discovering new antibacterial targets, and these programs are the subject of this review. Many of these tools apply a cheminformatic approach, utilizing the structural information of either ligand or protein, chemogenomic databases, and docking algorithms to identify putative antibacterial targets. Considering the wealth of potential drug targets identified from genomic research, these approaches are perfectly placed to mine this rich resource and complement drug discovery programs.
authors: School of Chemistry, University of Leeds, Leeds, LS2 9JT, UK.
authors: Martin J
authors: MJ
authors: McPhillie
authors: Ricky M
authors: RM
authors: Cain
authors: Sarah
authors: S
authors: Narramore
authors: Colin W G
authors: CW
authors: Fishwick
authors: Katie J
authors: KJ
authors: Simmons
mesh_terms: D000900:Anti-Bacterial Agents / Q000737:chemistry*; D019295:Computational Biology; D016503:Drug Delivery Systems; D015195:Drug Design; D055808:Drug Discovery / Q000379:methods*; D008954:Models, Biological
chemical_list: D000900:Anti-Bacterial Agents
keywords: cheminformatics; molecular modeling; proteomics; therapeutic target