First‐Principles Structure–Activity Relationship Insights Into Phenolic Scaffolds: QSAR Modeling and Drug‐Likeness Screening

Abstract Phenolic compounds represent a structurally diverse class of bioactive secondary metabolites renowned for their therapeutic potential, particularly due to their antioxidant, anti‐inflammatory, and anticancer properties. The correlation between their molecular structure and biological efficacy, however, remains an area of active investigation. This study presents an integrated computational investigation of 49 phenolic derivatives combining density functional theory (DFT)‐based global reactivity descriptors determination, quantitative structure–activity relationship (QSAR) modeling, and ADMET (i.e., absorption, distribution, metabolism, excretion, and toxicity) profiling. Using B3LYP/6‐311++G** calculations, electronic descriptors are systematically analyzed across a structurally diverse dataset. The results reveal distinct substituent‐dependent trends: electron‐donating groups enhance HOMO energies, decrease energy gaps, and increase softness, favoring antioxidant and redox activity, whereas electron‐withdrawing groups increase hardness and electrophilicity, correlating with metabolic stability and potential enzyme inhibition. Complementary QSAR models achieved high predictive performance and identified LogP, electrophilicity, and hydration energy as key toxicity predictors. ADMET analysis highlighted 4‐ethoxyphenol, 2‐fluorophenol, and 4‐cyanophenol as promising drug‐like scaffolds with high gastrointestinal absorption, favorable blood–brain barrier permeability, and minimal predicted toxicity. Overall, this study provides structure–activity insights for phenolic scaffolds by bridging electronic structure with pharmacokinetic behavior and prioritizing candidates for future drug design and experimental validation.