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

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

Keywords:

• Homology modeling
• hit selection
• virtual screening
• Acinetobacter baumannii
• MD simulation
• molecular docking
• MurG protein

Acknowledgements

The authors thank Prof. B. Jayaram (Coordinator of the Supercomputing Facility for Bioinformatics & Computational Biology, IIT Delhi) for supporting and providing computational facilities to carry out the MD simulation of protein and protein-ligand complexes. Dr. Amit Kumar Singh thanks the Department of Science and Technology (DST) and Indian National Science Academy (INSA), New Delhi, India. Gizachew Muluneh Amera thanks the College of Natural Science, Wollo University, Dessie, Ethiopia for the sponsorship.

Disclosure statement

No potential conflict of interest was reported by the authors.

Ethical standards

Ethical standards is compulsory for studies relating to human and animal subjects.