Performance prediction of polypeptide derivatives as efficient potential microbial inhibitors: a computational approach.

Abstract

Lately, various scientists have been paying a lot of consideration to the design of operational antimicrobial agents due to the rise of multiple drug-resistant strains. Therefore, this work is aimed at discovering the biochemical behavior of the analyzed polypeptides in relation to glutamine amidotransferase GatD (pdb id: 5n9m) for gram positive bacteria and beta-lactamase class A (pdb id: 5fqq) for gram negative bacteria. Additionally, this study aims to identify the specific atoms involved in the observed biochemical interactions between the studied complexes using computational methods. In this work, five polypeptides were studied using insilico approach via Spartan 14 software, molecular operating environment, ADMETSar, and Gromacs. The descriptors obtained revealed the activities of the studied compounds, the molecular interaction between the studied ligands as well as glutamine amidotransferase GatD (pdb id: 5n9m) and beta-lactamase class A (pdb id: 5fqq) which thereby exposed compound 1 and 5 to be the compounds with greatest ability to inhibit the studied targets among other studied compounds. Our discoveries may open door for the design of collection of proficient polypeptide-based drug-like compounds as potential anti-microbial agents.