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

Objective: 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.

Methods: In this work, five polypeptides were studied using insilico approach via Spartan 14 software, molecular operating environment, ADMETSar, and Gromacs.

Results: 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.

Conclusion: Our discoveries may open door for the design of collection of proficient polypeptide-based drug-like compounds as potential anti-microbial agents.