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Internet Electronic Journal of Molecular Design - IEJMD, ISSN 1538-6414, CODEN IEJMAT
ABSTRACT - Internet Electron. J. Mol. Des. April 2009, Volume 8, Number 4, 42-62

Computational Prediction of Potent Therapeutic Targets of Pseudomonas aeruginosa and In Silico Virtual Screening for Novel Inhibitors
Pradeep K. Naik, Seneha Santoshi, and Ashima Birmani
Internet Electron. J. Mol. Des. 2009, 8, 42-62

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Abstract:
Pseudomonas aeruginosa is an ubiquitous pathogen capable of infecting virtually all tissues. The complete genome sequence of pathogen has provided a plethora of potential drug targets. While these data potentially contain all the determinants of host-pathogen interactions and possible drug targets, computational methods for selecting suitable candidates for further experimental analyses are currently limited. We have performed comparative analysis of whole genomes and metabolic pathways of the pathogen P. aeruginosa and the host Homo sapiens including symbiotic organisms. Moreover, the entire approach was built on the assumption that the potential target must play an essential role in the pathogen's survival and constitute a critical component in its metabolic pathway. We have predicted 6 unique essential genes in the pathogen using comparative genomics and 20 unique metabolic pathways based on comparative metabolomics. After critical evaluations of the targets we have finally considered dapD, gspL and pilA as the potent targets for virtual screening of lead molecules. Virtual screening was carried out using the high throughput virtual screening module of Glide and the hits with better glide score were further optimized by Glide-XP module. The PubChem molecule libraries (ChemDivision database, Diversity dataset, Kinase inhibitor database) were used for screening process. Along with the high scoring results, the interaction studies provided promising ligands for future experimental screening to inhibit the proliferation of Pseudomonas aeruginosa.

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