Solvation-weighted connectivity indices for GC retention prediction of polycyclic aromatic sulphur heterocycles

Predicting the gas chromatographic retention indices (RIs) of sulphur-containing polycyclic aromatic hydrocarbons (S-PAHs) is challenging due to positional isomerism, which introduces subtle structural variations that are not well captured by conventional physicochemical descriptors or simple partitioning models. In this study, a quantitative structure–retention relationship (QSRR) model was developed to accurately predict the RIs of S-PAHs using three molecular descriptors calculated with AlvaDesc software. Among the evaluated variables, solvation-weighted connectivity indices (X3sol, X4sol, and X5sol) emerged as the most influential descriptors governing chromatographic behaviour and selectivity. The model was built using a training set of 35 compounds and externally validated with an independent test set of 13 compounds. It demonstrated excellent predictive performance, with an adjusted coefficient of determination (R2adj.) of approximately 0.99 for both datasets. Residual analysis confirmed the robustness of the model, showing deviations mostly within ±5 RI units and no systematic error. Overall, solvation-weighted connectivity indices effectively capture subtle topological differences among positional isomers, providing a robust, interpretable, and reliable framework for predicting and understanding the retention behaviour of S-PAHs.