Differential genome analyses of metabolic enzymes in Pseudomonas aeruginosa for drug target identification

Abstract

Complete genome sequences of several pathogenic bacteria have been determined, and many more such projects are currently under way. While these data potentially contain all the determinants of host-pathogen interactions and possible drug targets, computational tools for selecting suitable candidates for further experimental analyses are currently limited. Detection of bacterial genes that are non-homologous to human genes, and are essential for the survival of the pathogen represents a promising means of identifying novel drug targets. We used a differential pathway analyses approach (based on KEGG data) to identify essential genes from Pseudomonas aeruginosa. Our approach identified 214 unique enzymes in P. aeruginosa that may be potential drug targets and can be considered for rational drug design. About 40% of these putative targets have been reported as essential by transposon mutagenesis data elsewhere. Homology model for one of the proteins (LpxC) is presented as a case study and can be explored for in silico docking with suitable inhibitors. This approach is a step towards facilitating the search for new antibiotics.