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Research Article Open access CC BY 4.0

Density Functional Theory (DFT), Molecular Docking, and ADMET Studies on Acid Hydrazides and their VO(IV), Co(II), and Ni(II) Complexes with Antibacterial and Spectroscopic Insights

Oyekunle Azeez Ogundipe, Olalekan Wasiu Salawu, Kehinde Gabriel Obiyenwa, Banjo Semire

Asian Journal of Chemical Sciences · pp. 146–183 · Published 24 Dec 2025

10.9734/ajocs/2025/v15i6412

Abstract

Aims: To use computational methods to examine the spectroscopic characteristics and potential antibacterial activities of twelve previously synthesized acid hydrazides, as well as to explore how their electronic properties and molecular interactions relate to their biological activity. Study Design: An in silico approach, utilizing Density Functional Theory (DFT) calculations, molecular docking simulations, and ADMET profiling, was employed to evaluate novel acid hydrazide-based metal complexes for their antibacterial potential. Place and Duration of Study: The study was conducted at the Department of Chemistry, Faculty of Science, Federal University, Lokoja, from June to September 2025. Methods: DFT was used to model and optimize the molecular structures of the metal complexes. The spectroscopic and electronic properties were also calculated using DFT, while molecular docking of complexes against five bacterial protein targets was conducted using MOE. The drug-likeness and pharmacokinetic properties of the most active complexes were evaluated via ADMET simulations using the SwissADME platform. Results: Five complexes, [VO(4-ABAH)2]²⁺ (C1), [VO(IBAH)2]²⁺ (C3), [Ni(IBAH)2]²⁺ (C9), [Ni(4-CBAH·H2O)2]²⁺ (C11), and [Ni(IBAH·H2O)2]²⁺ (C12) demonstrated notable antibacterial activity as they were specifically active against Klebsiella pneumoniae (PDB ID: 1OSM) and Pseudomonas aeruginosa (PDB ID: 3ZMB). Conclusion: A strong correlation was observed between the experimental data and calculated spectroscopic properties of the metal complexes and their antibacterial activities, indicating that computational methods can be predictive of biological efficacy.

DFT molecular docking hydrazide metal (II) complexes

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