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

Autor:	Oyebamiji AK; Department of Industrial Chemistry, Bowen University PMB 284, Iwo, Osun State, Nigeria.; Good Health and Wellbeing Research Clusters (SDG 03), Bowen University PMB 284, Iwo, Osun State, Nigeria., Akintelu SA; Department of Industrial Chemistry, University of Ilesa Ilesa, Osun State, Nigeria.; Good Health and Wellbeing Research Clusters (SDG 03), Department of Industrial Chemistry, University of Ilesa Ilesa, Osun State, Nigeria., Olujinmi FE; Department of Industrial Chemistry, Bowen University PMB 284, Iwo, Osun State, Nigeria., Jinadu LA; Department of Industrial Chemistry, Bowen University PMB 284, Iwo, Osun State, Nigeria.; Department of Chemical Sciences, Fountain University Osogbo, Osun State, Nigeria., Ebenezer O; Department of Physics, University of Alberta Edmonton, AB, Canada., Aworinde JO; Department of Medical Laboratory Science, Lead City University Ibadan, Oyo State, Nigeria., Semire B; Department of Pure and Applied Chemistry, Ladoke Akintola University of Technology Ogbomoso, Oyo State, Nigeria., Babalola JO; Department of Industrial Chemistry, Bowen University PMB 284, Iwo, Osun State, Nigeria.
Jazyk:	angličtina
Zdroj:	International journal of biochemistry and molecular biology [Int J Biochem Mol Biol] 2024 Oct 15; Vol. 15 (5), pp. 127-140. Date of Electronic Publication: 2024 Oct 15 (Print Publication: 2024).
DOI:	10.62347/YLVH4793
Abstrakt:	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. Competing Interests: None. (IJBMB Copyright © 2024.)
Databáze:	MEDLINE
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