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Volume 4


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In Silico Biology 4, 0028 (2004); ©2004, Bioinformation Systems e.V.  



A novel genomics approach for the identification of drug targets in pathogens, with special reference to Pseudomonas aeruginosa

Kishore R. Sakharkar1, Meena K. Sakharkar2 and Vincent T. K. Chow3*

1 BioInformatics Institute, Biopolis Street, Singapore
2 Nanyang Center for Supercomputing and Visualization, School of Mechanical and Production Engineering, Nanyang Technological University, Singapore
3 Human Genome Laboratory, Department of Microbiology, Faculty of Medicine, National University of Singapore, Kent Ridge, Singapore; Email: micctk@nus.edu.sg

*  corresponding author


Edited by E. Wingender; received March 06, 2004; revised May 14, 2004; accepted May 16, 2004; published May 31, 2004


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 have used three-way genome comparisons to identify essential genes from Pseudomonas aeruginosa. Our approach identified 306 essential genes that may be considered as potential drug targets. The resultant analyses are in good agreement with the results of systematic gene deletion experiments. This approach enables rapid potential drug target identification, thereby greatly facilitating the search for new antibiotics. These results underscore the utility of large genomic databases for in silico systematic drug target identification in the post-genomic era.

Key words: Pseudomonas, bacterial pathogen, essential genes, Database of Essential Genes (DEG), comparative microbial genomics, human genome, homology, drug targets, antibiotics