Screening of promising molecules against MurG as drug target in multi-drug-resistant-Acinetobacter baumannii - insights from comparative protein modeling, molecular docking and molecular dynamics simulation. Issue 17 (21st November 2020)

• Record Type: Journal Article
• Authors: Amera, Gizachew Muluneh; Khan, Rameez Jabeer; Pathak, Amita; Jha, Rajat Kumar; Muthukumaran, Jayaraman; Singh, Amit Kumar
• Is Part Of: Journal of biomolecular structure & dynamics. Volume 38:Issue 17(2020)
• Page Start: 5230
• Page End: 5252
• Publication Date: 2020-11-21
• Subjects: Homology modeling -- hit selection -- virtual screening -- Acinetobacter baumannii -- MD simulation -- molecular docking -- MurG protein; Biomolecules -- Periodicals; Molecular structure -- Periodicals; Molecular Biology -- Periodicals; Biomechanics -- Periodicals; 572
• DOI: 10.1080/07391102.2019.1700167
• Languages: English
• ISSNs: 0739-1102

Abstract

Abstract: The UDP- N -acetylglucosamine- N -acetylmuramyl-(pentapeptide) pyrophosphoryl-undecaprenol N -acetylglucosamine transferase (MurG) is located in plasma membrane which plays a crucial role for peptidoglycan biosynthesis in Gram-negative bacteria. Recently, this protein is considered as an important and unique drug target in Acinetobacter baumannii since it plays a key role during the synthesis of peptidoglycan as well as which is not found in Homo sapiens. In this study, initially we performed comparative protein modeling approach to predict the three-dimensional model of MurG based on crystal structure of UDP- N -acetylglucosamine- N -acetylmuramyl-(pentapeptide) pyrophosphoryl-undecaprenol N-acetylglucosamine transferase (PDB ID: 1F0K) from E.coli K12. MurG model has two important functional domains located in N and C- terminus which are separated by a deep cleft. Active site residues are located between two domains and they are Gly20, Arg170, Gly200, Ser201, Gln227, Phe254, Leu275, Thr276, and Glu279 which play essential role for the function of MurG. In order to inhibit the function of MurG, we employed the High Throughput Virtual Screening (HTVS) and docking techniques to identify the promising molecules which will further subjected into screening for computing their drug like and pharmacokinetic properties. From the HTVS, we identified 5279 molecules, among these, 12 were passed the drug-like and pharmacokinetic screening analysis. Based on the interaction analysis in terms of binding affinity, inhibition constant and intermolecular interactions, we selected four molecules for further MD simulation to understand the structural stability of protein-ligand complexes. All the analysis of MD simulation suggested that ZINC09186673 and ZINC09956120 are identified as most promising putative inhibitors for MurG protein in A. baumannii. Communicated by Ramaswamy H. Sarma