Browsing by Author "Onikanni, Sunday Amos"

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    Computational and preclinical prediction of the antimicrobial properties of an agent isolated from monodora myristica: A novel dna gyrase inhibitor
    (MDPI, 2023) Onikanni, Sunday Amos; Lawal, Bashir; Fadaka, Adewale Oluwaseun; Bakare, Oluwafemi
    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.
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    Interference of a phytoconstituent from Nymphaea lotus-derived ligand N-acetyl glucosamine with signaling receptors in diabetes mellitus development: a targeted computational analysis
    (Elsevier B.V., 2025) Fadaka, Adewale Oluwaseun; Onikanni, Sunday Amos; Dao, Tran Nhat-Phong
    Diabetes mellitus is a world-wide health concern with several millions affected in all ages. Computer-aided drug design (CADD) is a powerful tool that has revolutionized the process of discovering and developing new drugs. It provides innovative methods that can speed up drug discovery and lower costs thereby results to increase enthusiasm at developing instinctive antidiabetic agents as alternatives for managing diabetes. Nymphaea lotus, a plant with medicinal properties known for its anti-diabetic effects, contains bioactive components like N-acetyl glucosamine. An in silico study was conducted to investigate its potential in targeting proteins related to diabetes. Molecular docking studies, toxicity prediction, examination of drug depiction, and Molecular Dynamics Simulation (MDs) of the ligands with the identified receptor target were conducted using the Schrödinger platform. The receptor-ligand complex of Nymphaea lotus was compared with known inhibitors. Molecular dynamics simulation, principal component analysis, and free energy landscape analysis showed that the binding affinity of the Nymphaea lotus complex was higher than that of reference ligands. This suggests that Nymphaea lotus and its bioactive compounds have promising medicinal value for managing type 2 diabetes, warranting further research into their therapeutic potential