Title: Identifying drug-like inhibitors of Mycobacterium tuberculosis H37Rv Seryl tRNA synthetase based on bioassay dataset: homology modelling, docking and molecular dynamics simulation
Authors: V.K. Adarsh; A. Santhiagu
Addresses: School of Biotechnology, National Institute of Technology, Calicut, Kerala-673601, India ' School of Biotechnology, National Institute of Technology, Calicut, Kerala-673601, India
Abstract: Resistance to existing drugs of tuberculosis bacteria demands an immediate requirement to develop effective new chemical entities acting on emerging targets. Seryl-tRNA synthetase (SerRS) is essential for the viability of Mycobacterium tuberculosis (MTB). In this study, we have attempted to develop the tertiary structure of SerRS through homology modelling and to elucidate the active site interactions of inhibitor compounds aided by docking. Homology modelling using PDB ID: '2DQ3: A' chain as template and validation of the model was carried out with Modeller V9.13 and SAVES online server respectively. About 1248 compounds from a putative kinase compound library of PubChem database found active in whole cell bioassay (AID2842) on MTB - H37Rv was used in docking studies using 'AutoDock'. Out of the tested molecules, nine showed docking scores ≤-10 kcal/mol with good drug-like properties were further subjected to molecular dynamics (MD) simulations and found three of the compounds have stable interactions.
Keywords: drug design; homology modelling; modeller; AutoDock; multidrug-resistant Mycobacterium tuberculosis; MDR-TB; multidrug-resistant tuberculosis; SerRS; seryl-tRNA synthetase; PubChem; molecular docking; molecular dynamics.
International Journal of Computational Biology and Drug Design, 2019 Vol.12 No.4, pp.373 - 402
Received: 04 Oct 2018
Accepted: 25 Feb 2019
Published online: 13 Nov 2019 *