Abstract
In this study, a comprehensive predictive topological modeling framework was employed to investigate the quantitative structure-property relationships (QSPR) of naturally occurring anticancer chalcones. A series of degree-based topological indices, including the first and second Zagreb indices, first and second redefined Zagreb indices, sum-connectivity index, symmetric division index, Randić index, and harmonic index, were computed to represent key molecular structural features. Statistical and regression analyses were performed to correlate these indices with experimentally reported physicochemical properties of chalcones. The study focuses on eight naturally derived anticancer Chalcones, namely, Isoliquiritigenin, Butein, Cardamonin, Sappanchalcone, Licochalcone A, Millepachine, Xanthohumol, and Curcumin-selected based on their structural diversity and well-documented pharmacological potential. Correlations between the computed indices and several physicochemical parameters, such as molecular complexity, molecular weight, molar refractivity, and polarizability, were examined. The study also includes a comprehensive statistical evaluation of the regression models to assess the predictive accuracy, robustness, and reliability of the proposed descriptors.