Integrated Virtual Screening of Anthraquinone Derivatives for Anticancer Drug Discovery

Anthraquinone derivatives are naturally derived compounds with well-documented anticancer potential. However, their therapeutic potential remains underexplored due to limited structure–activity optimization and lack of target-specific screening. This study aimed to systematically prioritize potent anthraquinone-based anticancer hits targeting three clinically significant cancer-related proteins, namely p53 (Y220C mutant), ERK2 (MAPK1) and ER[Formula: see text] (ESR1), using an integrated virtual screening strategy. A large library derived from 24 anthraquinone scaffolds was subjected to a parallel ligand- and structure-based computational screening workflow. This included quantitative structure–activity relationship (QSAR), pharmacophore, shape similarity and docking screening. A consensus scoring approach was employed by converting individual screening scores to [Formula: see text]-scores and averaging them across methods to rank hits. The consensus approach demonstrated improved discrimination between active and inactive compounds, with receiver operating characteristic and area under the curve (ROC–AUC) values of 0.98 for ER[Formula: see text], 0.96 for ERK2 and 0.91 for p53. Top-ranking hits showed favorable docking scores and poses comparable to known ligands. Diverse anthraquinone subclasses, such as chrysophanol, aloe-emodin and physcion, featured prominently among the prioritized candidates, enriched with key functional groups like hydroxyl, amine and carboxyl moieties. Post-simulation evaluations confirmed that the top-ranked hits maintained stable dynamics and structural compatibility, supporting their promise as potential lead candidates. Their conformational consistency with co-crystallized ligands further substantiated the reliability of the screening approach. In conclusion, this novel integrative virtual screening framework effectively identified chemically diverse anthraquinone-based candidates with the potential of exhibiting high affinity against ER[Formula: see text], ERK2 and p53 (Y220C mutant).