In Silico Molecular Docking of Aminoglycosides as Topoisomerase 1 Inhibitors: A Computational approach

Abstract

Cancer remains a leading cause of mortality worldwide, necessitating the discovery of novel therapeutic agents to combat this disease. The present study focuses on identifying drug-like molecules with anticancer properties through an in silico approach, targeting the human topoisomerase I-DNA complex (PDB ID: 1A35), a critical enzyme in DNA replication and repair. The primary objectives were to evaluate the binding affinity and drug-likeness of selected ligands, including antibiotics (gentamicin and amikacin) and chemotherapeutic agents (irinotecan and topotecan), using computational tools. The protein structure was prepared and energy-minimized, while ligands were sketched using ChemDraw Ultra 8.0, converted to 3D forms, and energy-minimized using Chem3D Pro 8.0. Molecular docking was performed using AutoDock Vina PyRx, and interactions were visualized with Biovia Discovery Studio 2024 Client. The results revealed binding energies of -6.2 and -6.7 kcal/mol for amikacin and gentamicin, respectively, and -8.4 and -7.6 kcal/mol for irinotecan and topotecan, respectively, indicating strong interactions with the target protein. These findings underscore the potential of these compounds as promising candidates for anticancer drug development, particularly due to their favorable binding affinities and adherence to Lipinski’s Rule of Five. This study highlights the significance of computational approaches in accelerating drug discovery and provides a foundation for further experimental validation of these molecules as potential anticancer agents.