Computational and Preclinical Prediction of the Antimicrobial Properties of an Agent Isolated from Monodora myristica: A Novel DNA Gyrase Inhibitor

Autor: Sunday Amos Onikanni, Bashir Lawal, Adewale Oluwaseun Fadaka, Oluwafemi Bakare, Ezekiel Adewole, Muhammad Taher, Junaidi Khotib, Deny Susanti, Babatunji Emmanuel Oyinloye, Basiru Olaitan Ajiboye, Oluwafemi Adeleke Ojo, Nicole Remaliah Samantha Sibuyi
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Molecules, Vol 28, Iss 4, p 1593 (2023)
Druh dokumentu: article
ISSN: 28041593
1420-3049
DOI: 10.3390/molecules28041593
Popis: The African nutmeg (Monodora myristica) is a medically useful plant. We, herein, aimed to critically examine whether bioactive compounds identified in the extracted oil of Monodora myristica could act as antimicrobial agents. To this end, we employed the Schrödinger platform as the computational tool to screen bioactive compounds identified in the oil of Monodora myristica. Our lead compound displayed the highest potency when compared with levofloxacin based on its binding affinity. The hit molecule was further subjected to an Absorption, Distribution, Metabolism, Excretion (ADME) prediction, and a Molecular Dynamics (MD) simulation was carried out on molecules with PubChem IDs 529885 and 175002 and on three standards (levofloxacin, cephalexin, and novobiocin). The MD analysis results demonstrated that two molecules are highly compact when compared to the native protein; thereby, this suggests that they could affect the protein on a structural and a functional level. The employed computational approach demonstrates that conformational changes occur in DNA gyrase after the binding of inhibitors; thereby, this resulted in structural and functional changes. These findings expand our knowledge on the inhibition of bacterial DNA gyrase and could pave the way for the discovery of new drugs for the treatment of multi-resistant bacterial infections.
Databáze: Directory of Open Access Journals
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