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International Journal of Computational Bioinformatics and In Silico Modeling
2013: Volume-2 Issue-3
ISSN: 2320-0634

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ABSTRACT   REFERENCES  
International Journal of Computational Bioinformatics and In Silico Modeling 2(3) 2013: 132-137

In silico drug target identification in Legionella pneumophila strain Paris: modelling and molecular dynamics simulation of a candidate enzyme phosphoglyceromutase (PGM)


Pramod Kumar Yadav* and Hemant Kumar Pandey

Department of Computational Biology and Bioinformatics, JSBB, Sam Higginbottom Institute of Agriculture, Technology & Sciences (DU), Allahabad-211007, India.

* Corresponding Author

ABSTRACT

Legionellosis is a potentially fatal infectious disease caused by gram negative aerobic bacteria belonging to the genus Legionella. Over 90% of legionellosis cases are caused by Legionella pneumophila which is a thin, aerobic, pleomorphic, flagellated, non-spore forming bacteria. The emergence of drug resistance of L. pneumophila has led to the search for novel drug targets. In the present research work, computational analysis of metabolic pathways of the bacteria and host was performed to identify novel drug targets non-homologous to Homo sapiens. All enzymes involved in the metabolic pathways of L. pneumophila strain Paris were searched against the proteome of Homo sapiens using the BLASTp program and the threshold of E-value was set to as 0.001. Total 45 unique putative targets were identified and encoding genes of these targets were further searched in the DEG database to recognize the essentiality of genes. It was found that 37 encoding genes were essential for the survival of the pathogen. Among those identified targets, it has been reported in literature that phosphoglyceromutase, phosphoglucosamine mutase and phosphomannomutase enzymes can be used as potential therapeutic drug target. The 3D structure of candidate enzyme phosphoglyceromutase (PGM) was predicted by comparative modeling method using the Swiss model, ModWeb and HHPred servers respectively. The stereochemical qualities of all predicted models were evaluated by the SAVES server. The best quality model was generated by the Swiss model server, which was further subjected to molecular dynamics simulation (MDS) to assess the stability of modeled structure. The MDS was performed at 100 pico second (ps) time scale and in 50000 steps using the Gromacs v4.06 program. The MDS results have shown the significant stability to the modeled structure of PGM. In future modeled structure of PGM might be exploited for the designing of novel inhibitors against L. pneumophila.

Copyright © 2013 | AIZEON publishers | All rights reserved

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Citation: PK Yadav and HK Pandey. (2013). In silico drug target identification in Legionella pneumophila strain Paris: modelling and molecular dynamics simulation of a candidate enzyme phosphoglyceromutase (PGM). Int J Comput Bioinfo In Silico Model 2(3): 132-137

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