Informatics in Medicine Unlocked (Jan 2018)
Molecular modelling and dynamic simulation of UDP-N-acetylglucosamine 1-carboxyvinyltransferase (MurA) from Mycobacterium tuberculosis using in silico approach
Abstract
UDP-N-acetylglucosamine 1-carboxyvinyltransferase (MurA) catalyses the biosynthesis of peptidoglycans in Mycobacterium tuberculosis (MTB) cell wall by adding enolpyruvyl to UDP-N-acetylglucosamine through an addition and elimination process. In this study, novel inhibitors of MurA were identified using an in silico approach. The three dimensional (3D) structure of MurA was determined based upon the principle of homology modelling, using a template (3SG1) obtained from Bacillus anthracis. Structural analysis revealed that three residues (Arg93, Asp305, and Val327) were involved in the UDP-N-acetylglucosamine binding site and one residue (Asp117) was involved in the direct catalysis. These residues were utilized as a prime target for the inhibitors during virtual screening and molecular docking analysis. A total of seven thousand five hundred and twenty-nine (7529) ligands were obtained from public databases, capable of binding to MurA. These compounds were further filtered for physicochemical properties (Lipinski rule of five), molecular docking analysis, and pharmacokinetic properties. Eleven (11) ligands with good binding energies ranging between ─10.73 and ─8.17 kcal/mol were obtained. Further, four compounds with good binding energies (ZINC20256175 = ─10.66 kcal/mol, ZINC12283251 = ─10.58 kcal/mol, ZINC14538153 = ─9.90 kcal/mol and ZINC12217441 = ─9.73 kcal/mol) out of the 11, were selected and used for Molecular Dynamic (MD) Simulation and Molecular Generalized Born Surface Area (MM-GBSA) analyses. The results of the analyses revealed that all four compounds achieved a differing level of stability during the 50ns MD simulation. Therefore, these compounds could be considered as potential inhibitors for MTB after successful experimental validation. Keywords: MurA, Homology modelling, Docking, MTB, MD simulation and MM-GBSA