Literature DB >> 19484275

Probing ligand binding modes of Mycobacterium tuberculosis MurC ligase by molecular modeling, dynamics simulation and docking.

C M Anuradha1, Chaitanya Mulakayala, Banaganapalli Babajan, M Naveen, Chikati Rajasekhar, Chitta Suresh Kumar.   

Abstract

Multi drug resistance capacity for Mycobacterium tuberculosis (MDR-Mtb) demands the profound need for developing new anti-tuberculosis drugs. The present work is on Mtb-MurC ligase, which is an enzyme involved in biosynthesis of peptidoglycan, a component of Mtb cell wall. In this paper the 3-D structure of Mtb-MurC has been constructed using the templates 1GQQ and 1P31. Structural refinement and energy minimization of the predicted Mtb-MurC ligase model has been carried out by molecular dynamics. The streochemical check failures in the energy minimized model have been evaluated through Procheck, Whatif ProSA, and Verify 3D. Further torsion angles for the side chains of amino acid residues of the developed model were determined using Predictor. Docking analysis of Mtb-MurC model with ligands and natural substrates enabled us to identify specific residues viz. Gly125, Lys126, Arg331, and Arg332, within the Mtb-MurC binding pocket to play an important role in ligand and substrate binding affinity and selectivity. The availability of Mtb-MurC ligase built model, together with insights gained from docking analysis will promote the rational design of potent and selective Mtb-MurC ligase inhibitors as antituberculosis therapeutics.

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Year:  2009        PMID: 19484275     DOI: 10.1007/s00894-009-0521-2

Source DB:  PubMed          Journal:  J Mol Model        ISSN: 0948-5023            Impact factor:   1.810


  23 in total

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  7 in total

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Journal:  J Mol Model       Date:  2011-11-19       Impact factor: 1.810

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Authors:  M Chaitanya; B Babajan; C M Anuradha; M Naveen; C Rajasekhar; P Madhusudana; Chitta Suresh Kumar
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3.  Identification of hotspot regions of MurB oxidoreductase enzyme using homology modeling, molecular dynamics and molecular docking techniques.

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Journal:  J Mol Model       Date:  2010-07-09       Impact factor: 1.810

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Journal:  BMC Genomics       Date:  2018-07-27       Impact factor: 3.969

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Authors:  Arundhati Maitra; Tulika Munshi; Jess Healy; Liam T Martin; Waldemar Vollmer; Nicholas H Keep; Sanjib Bhakta
Journal:  FEMS Microbiol Rev       Date:  2019-09-01       Impact factor: 16.408

  7 in total

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