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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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