Abstract

To anticipate the physicochemical and biological properties of pharmacological compounds using mathematical descriptors, Quantitative Structure–Property Relationship (QSPR) analysis is essential. In this research, a QSPR analysis is performed on selected compounds associated with Alzheimer’s disease (AD) using degree-based topological indices derived from their molecular graphs. Various well-known topological indices, including the Wiener index, Zagreb indices, Randić index, ABC index, GA index, and associated descriptors, are computed. These indices are correlated with significant physicochemical characteristics, such as molecular weight, polar surface area, and molar refractivity, using linear and multiple regression models. The statistical performance of the models is evaluated using the correlation coefficient (R), the coefficient of determination (R²), and the standard error. The findings demonstrate that topological indices are effective molecular descriptors for predicting properties of Alzheimer’s drugs and provide insights into structure–property relationships.