Computational and preclinical prediction of the antimicrobial properties of an agent isolated from monodora myristica: A novel dna gyrase inhibitor
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.
Antibiotics, Conformational, Levofloxacin, Monodora myristica, Schrödinger
Onikanni, S.A.; Lawal, B.; Fadaka, A.O.; Bakare, O.; Adewole, E.; Taher, M.; Khotib, J.; Susanti, D.; Oyinloye, B.E.; Ajiboye, B.O.; et al. Computational and Preclinical Prediction of the Antimicrobial Properties of an Agent Isolated from Monodora myristica: A Novel DNA Gyrase Inhibitor. Molecules 2023, 28, 1593. https://doi.org/10.3390/ molecules28041593