Computational and preclinical prediction of the antimicrobial properties of an agent isolated from Monodora myristica: a novel DNA gyrase inhibitor - Onikanni, Sunday Amos; Lawal, Bashir; Fadaka, Adewale Oluwaseun; Bakare, Oluwafemi; Ezekiel, Adewole; Bakhtiar, Muhammad Taher; Khotib, Junaidi; Darnis, Deny Susanti; Oyinloye, Babatunji Emmanuel; Ajiboye, Basiru Olaitan; Ojo, Oluwafemi Adeleke; Sibuyi, Nicole Remaliah Samantha (Multidisciplinary Digital Publishing Institute (MDPI), 2023)
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 com- putational 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, Excre- tion (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 novo- biocin). The MD analysis results demonstrated that two molecules are highly compact when com- pared 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 gy- rase and could pave the way for the discovery of new drugs for the treatment of multi-resistant bacterial infections.