Inhibitor binding studies of Mycobacterium tuberculosis MraY (Rv21 56c): Insights from molecular modeling, docking, and simulation studies

6Citations
Citations of this article
41Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Tuberculosis (TB) is a contagious disease caused by Mycobacterium tuberculosis (M.tb) or tubercule bacillus, and H37Rv is the most studied clinical strain. The recent development of resistance to existing drugs is a global health-care challenge to control and cure TB. Hence, there is a critical need to discover new drug targets in M.tb. The members of peptidoglycan biosynthesis pathway are attractive target proteins for antibacterial drug development. We have performed in silico analysis of M.tb MraY (Rv2156c) integral membrane protein and constructed the three-dimensional (3D) structure model of M.tb MraY based on homology modeling method. The validated model was complexed with antibiotic muraymycin D2 (MD2) and was used to generate structure-based pharmacophore model (e-pharmacophore). High-throughput virtual screening (HTVS) of Asinex database and molecular docking of hits was performed to identify the potential inhibitors based on their mode of interactions with the key residues involved in M.tb MraY–MD2 binding. The validation of these molecules was performed using molecular dynamics (MD) simulations for two best identified hit molecules complexed with M.tb MraY in the lipid bilayer, dipalmitoylphosphatidyl-choline (DPPC) membrane. The results indicated the stability of the complexes formed and retained non-bonding interactions similar to MD2. These findings may help in the design of new inhibitors to M.tb MraY involved in peptidoglycan biosynthesis.

Cite

CITATION STYLE

APA

Mallavarapu, B. D., Abdullah, M., Saxena, S., & Guruprasad, L. (2019). Inhibitor binding studies of Mycobacterium tuberculosis MraY (Rv21 56c): Insights from molecular modeling, docking, and simulation studies. Journal of Biomolecular Structure and Dynamics, 37(14), 3751–3763. https://doi.org/10.1080/07391102.2018.1526715

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free