Abstract
The availability of complete genome sequences of many bacterial species is facilitating numerous computational approaches for understanding bacterial genomes. One of the major incentives behind the genome sequencing of many pathogenic bacteria is the desire to better understand their diversity and to develop new approaches for controlling human diseases caused by these microorganisms. This task has become even more urgent with the rapid evolution of antibiotic resistance among many bacterial pathogens. Novel drug targets are required in order to design new antimicrobials against antibiotic-resistant pathogens. The complete genome sequences of an ever increasing number of pathogenic microbes constitute an invaluable resource and provide lead information on potential drug targets. This review focuses on in silico analyses of microbial genomes, their host-specific adaptations, with specific reference to genome architecture, design, evolution, and trends in computational identification of microbial drug targets. These trends underscore the utility of genomic data for systematic in silico drug target identification in the post-genomic era.