Abstract

Antibiotic resistance in bacteria is rapidly increasing across the globe which warrants the development of new drugs to tackle this issue. Since alanine racemase is essential to bacterial survival, novel antibiotics could have efficacy targeting it, particularly in light of the growing prevalence of antibiotic resistance. This work employs cheminformatics and biophysics approaches to find and optimize new inhibitors of alanine racemase. The objective of the research is to effectively find strong inhibitors and advance the development of novel drugs to fight resistant bacterial infections by integrating virtual screening with molecular dynamics simulations. Herein, using clerodane furanolactones as a parent structure, we identified several derivatives of the compound to show the best binding with bacterial alanine racemase enzyme and block the biosynthesis of bacterial cell walls. Three compounds; Top-1, Top-2, and Top-3 with a binding affinity (in kcal/mol) of - 8.7, -8.6, and -8.5, respectively were identified. The compounds were classified as good drug-like molecules as they clear parameters of Lipinski, Ghose Muegge, Vber, Egan, and MDDR drug-like rules. According to molecular dynamics simulation findings, the enzyme remained in good stable dynamics in the presence of compounds throughout the length of simulation time with average RMSD within the 3 Å range. Further observation noticed the enzyme residues in good overall stable behavior, particularly the active site residues. The intermolecular strength of interactions between the enzyme and compound was additionally crossvalidated by binding free energy analysis. The net binding free energy (in kcal/mol) of Top-1, Top-2, and Top-3 is -22, -25.21, and -17, respectively in the MM-GBSA method and -32.14 (Top-1),-29.45 (Top-2) and -32.87 (Top-3) in WaterSwap. Together this study indicated the screened compounds as promising antibacterial and might be investigated in the experimental analysis for biological activity.

Keywords: Alanine Racemase; Molecular docking; Auto-dock Vina; Molecular Dynamic Simulation; Water Swap