An in-silico approach to target multiple proteins involved in anti-microbial resistance using natural compounds produced by wild mushrooms

Abstract

Bacterial resistance to antibiotics and the number of patients infected by multi-drug-resistant bacteria have increased significantly over the past decade. This study follows a computational approach to identify potential antibacterial compounds from wild mushrooms. Twenty-six known compounds produced by wild mushrooms were docked to assess their affinity with drug targets of antibiotics such as penicillin-binding protein-1a (PBP1a), DNA gyrase, and isoleucyl-tRNA synthetase (ILERS). Docking scores were further validated by multiple receptor conformer (MRC)-based docking studies. Based on the MRC-based docking results, eight molecules were shortlisted for ADMET analysis. Molecular dynamics (MD) simulations were further performed to evaluate the conformational stability of the ligand-protein complexes. Binding energies were computed by the gmx_MMPBSA method. The data were obtained in terms of root-mean square deviation, and root-mean square fluctuation justified the stability of Austrocortilutein A, Austrocortirubin, and Confluentin in complex with several proteins under physiological conditions. Among these, Austrocortilutein A displayed better binding affinity with PBP1a and ILERS when compared with their respective reference ligands. This study is preliminary and aims to help drive the search for compounds that have the capacity to overcome the anti-microbial resistance of prevalent bacteria, using natural compounds produced by wild mushrooms. Further experimental validation is required to justify the clinical use of the studied compounds.