Molecular Docking and Binding Mechanism Analysis of Levofloxacin Structural Derivatives with DNA Gyrase and Topoisomerase IV

Persistent microbial antibiotic resistance, together with the growing frequency of pandemics, fuels the demand for new antimicrobial agents (AntAg). Given the AntAg shortfall, studies aimed at developing rapid strategies for identifying novel drug candidates are highly relevant. The present investigation is designed to carry out an in silico examination of the biological activity spectrum along with the molecular binding interactions of four structurally distinct levofloxacin (Lvf) variants engaging bacterial type IIA topoisomerase targets (DNA gyrase and topoisomerase IV), with the broader aim of aiding the creation of pharmaceuticals possessing an improved safety profile characterization. A suite of computational tools was harnessed for this purpose, notably ChemicPen v. 2.6, PyMol 2.5, Avogadro 1.2.0, PASS, and AutoDockTools 1.5.7 paired with the next-generation engine Autodock Vina. Collectively, these applications represent a pioneering set, made accessible for cluster visualization, featuring ligand-receptor binding affinity quantification, clustering coordinates, and hypothesized mechanisms of action. One authentic Lvf structure, specifically a decarboxylated derivative, was generated through tribochemical (TrbCh) treatment. The range of molecular ligand activity is depicted using a Bayesian probability-based activity estimation model (PASS software, Version 2.0). Both predicted and real (PMS and RMS) molecular configurations of Lvf, arranged in descending order of structural complexity, were encoded using Wiener (W), Balaban (Vs), Detour (Ip), and Electropy indices. Two-dimensional «structure-activity» plots served to discriminate among closely analogous levofloxacin forms. PMS and RMS were rendered as three-dimensional models of the respective ligand-receptor assemblies. The interfacial zones where RMS and PMS engage crucial amino acid residues—namely SER-79, DT-15, DG-1, DA-1—were illustrated. Details on intra- and intermolecular contact regions, free energy values (affinity, expressed in kcal/mol), the binding constant Kb (M−1), and the total cluster count are provided. The findings yielded by this in silico methodology for exploring the spectrum of action, establishing quantitative “structure-activity” relationships, and forecasting molecular mechanisms may prove to be of applied value for targeted drug development.