Programs
- M. Tech. in Automotive Engineering -
- Clinical Fellowship in Laboratory Genetics & Genomics - Fellowship
Publication Type : Journal Article
Thematic Areas : Nanosciences and Molecular Medicine
Publisher : Journal of Molecular Modeling
Source : Journal of Molecular Modeling, Volume 17, Number 5, p.939–953 (2011)
Url : https://doi.org/10.1007/s00894-010-0788-3
Campus : Kochi
School : Center for Nanosciences
Center : Amrita Center for Nanosciences and Molecular Medicine Move, Nanosciences
Department : Nanosciences and Molecular Medicine
Year : 2011
Abstract : Despite the availability of effective chemotherapy and a moderately protective vaccine, new anti-tuberculosis agents are urgently needed to decrease the global incidence of tuberculosis (TB) disease. The MurB gene belongs to the bacterial cell wall biosynthesis pathway and is an essential drug target in Mycobacterium tuberculosis (Mtb) that has no mammalian counterparts. Here, we present an integrated approach involving homology modeling, molecular dynamics and molecular docking studies on Mtb-MurB oxidoreductase enzyme. A homology model of Mtb-MurB enzyme was built for the first time in order to carry out structure-based inhibitor design. The accuracy of the model was validated using different techniques. The molecular docking study on this enzyme was undertaken using different classes of well known MurB inhibitors. Estimation of binding free energy by docking analysis indicated the importance of Tyr155, Arg156, Ser237, Asn241 and His304 residues within the Mtb-MurB binding pocket. Our computational analysis is in good agreement with experimental results of site-directed mutagenesis. The present study should therefore play a guiding role in the experimental design of Mtb-MurB inhibitors for in vitro/in vivo analysis.
Cite this Research Publication : V. Kumar, Saravanan, P., Arvind, A., and Dr. Gopi Mohan C., “Identification of Hotspot Regions of MurB Oxidoreductase Enzyme using Homology Modeling, molecular Dynamics and Molecular Docking Techniques”, Journal of Molecular Modeling, vol. 17, pp. 939–953, 2011.