Virtual Screening of Plant-Derived Compounds Targeting Cancer: An in Silico Pharmacological Study

Abstract

Cancer remains one of the leading causes of mortality worldwide, necessitating the identification of novel, safe, and effective therapeutic agents. Plant-derived phytochemicals represent a promising source of bioactive compounds owing to their structural diversity and broad pharmacological potential. The present study employed an in silico drug discovery approach to identify potential anticancer phytochemicals through molecular docking, drug-likeness evaluation, and pharmacokinetic prediction. Seven phytochemicals, namely ursolic acid, betulinic acid, α-lapachone, xyloidone, patamostat, β-sitosterol, and quercitrin, were selected based on their reported anticancer activities and structural diversity. Three-dimensional ligand structures were retrieved from the PubChem database, while crystal structures of key cancer-associated proteins, including Epidermal Growth Factor Receptor (EGFR), Epidermal Growth Factor Receptor Tyrosine Kinase (EGFRK), Peroxisome Proliferator-Activated Receptor Gamma (PPARγ), and Myeloid Cell Leukemia-1 (MCL-1), were obtained from the Protein Data Bank. Molecular docking was performed using AutoDock Vina, followed by visualization of ligand–protein interactions using PyMOL. Drug-likeness was assessed according to Lipinski's Rule of Five, and pharmacokinetic properties were predicted using the SwissADME platform. Docking analysis demonstrated that several phytochemicals exhibited strong binding affinity toward the selected molecular targets, with ursolic acid and betulinic acid showing the most favorable interaction profiles across multiple proteins. Key hydrogen-bonding and hydrophobic interactions with active-site amino acid residues suggested stable ligand–protein complexes. Most selected compounds demonstrated acceptable drug-likeness characteristics and favorable ADME profiles, supporting their suitability as potential oral drug candidates. The integrated computational approach identified ursolic acid and betulinic acid as the most promising lead molecules for anticancer drug development. These findings provide a scientific basis for further molecular dynamics simulations and experimental validation through in vitro and in vivo studies to establish their therapeutic potential.