Quantitative Structure-Activity Relationship Approaches for Exploring the Anticancer Potential of Flavonoids

Flavonoids are structurally diverse polyphenolic compounds widely distributed in fruits, vegetables, grains, and beverages, with considerable potential as anticancer agents. Their pleiotropic activities involve modulation of key cancer hallmarks, including oxidative stress, cell-cycle progression, apoptosis, autophagy, angiogenesis, invasion, and metastasis. These effects are mediated through multiple signaling pathways, including PI3K/Akt, MAPK, NF-κB, and STAT3. Understanding the relationship between flavonoid structure and biological activity is therefore essential for rational optimization of flavonoid-based therapeutics. Structure-activity relationship (SAR) and quantitative structure-activity relationship (QSAR) approaches provide systematic frameworks for correlating structural and physicochemical features, including hydroxylation, glycosylation, prenylation, electronic distribution, steric properties, and lipophilicity, with anticancer activity and target interactions. This review summarizes advances in flavonoid identification and characterization and critically examines computational approaches used to investigate their anticancer potential, including molecular docking, linear and nonlinear QSAR modeling, molecular similarity analysis, topological descriptors, semiempirical calculations, density functional theory, molecular dynamics simulations, and Free-Wilson analysis. Particular emphasis is placed on integrating computational predictions with experimental validation and addressing challenges related to pharmacokinetics, bioavailability, selectivity, and translation. Collectively, SAR/QSAR-guided strategies offer valuable tools for elucidating structure-activity relationships and accelerating the rational discovery and optimization of flavonoid-based anticancer candidates.