Year: 2025
Type: article
Abstract: Doxorubicin remains a cornerstone in cancer chemotherapy; however, its clinical utility is hindered by doselimiting toxicities and drug resistance. In this study, novel hybrid derivatives of doxorubicin were computationally designed and evaluated for their anticancer potential using in silico methods. Ligands were constructed using ChemSketch and assessed for physicochemical properties (Molinspiration), pharmacokinetic profiles (SwissADME), and biological activities (PASS). Toxicity was predicted via GUSAR, while molecular docking was performed using AutoDock Vina with key cancer-related protein targets. Docking results indicated favorable binding affinities, particularly with 5zad and 4zqf, suggesting enhanced therapeutic interactions. Visualization of ligand-protein interactions was conducted using Biovia Discovery Studio. This study demonstrates the potential of doxorubicin hybrids as promising leads for further development in anticancer therapy. Further in vitro and in vivo validation is warranted.
Authors: S.Apoorva S.Apoorva, B.Veeresh B.Veeresh, Areeba Fatima Areeba Fatima, Ameena Qavi Ameena Qavi, Nabeel Karigar Nabeel Karigar
Language: English
Subfield: Computational Theory and Mathematics
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4412915202