Investigation into the phenomena affecting the retention behavior of basic analytes in chaotropic chromatography: Joint effects of the most relevant chromatographic factors and analytes' molecular properties.

Abstract The aim of this study was to systematically investigate the phenomena affecting the retention behavior of structurally diverse basic drugs in ion-interaction chromatographic systems with chaotropic additives. To this end, the influence of three factors was studied: pH value of the aqueous phase, concentration of sodium hexafluorophosphate, and content of acetonitrile in the mobile phase. Mobile phase pH was found to affect the thermodynamic equilibria in the studied system beyond its effects on the analytes’ ionization state. Specifically, increasing pH from 2 to 4 led to longer retention times, even with analytes which remain completely protonated. An explanation for this phenomenon was sought by studying the adsorption behavior of acetonitrile and chaotropic additive onto stationary phase. It was shown that the magnitude of the developed surface potential, which significantly affects retention – increases with pH, and that this can be attributed to the larger surface excess of acetonitrile. To study how analytes’ structural properties influence their retention, quantitative structure–retention modeling was performed next. A support vector machine regression model was developed, relating mobile phase constituents and structural descriptors with retention data. While the ETA_EtaP_B_RC and XlogP can be considered as molecular descriptors which describe factors affecting retention in any RP-HPLC system, TDB9p and RDF45p are molecular descriptors which account for spatial arrangement of polarizable atoms and they can clearly relate to analytes’ behavior on the stationary phase surface, where the electrostatic potential develops. Complementarity of analytes’ structure with that of the electric double layer can be seen as a key factor influencing their retention behavior. Structural diversity of analytes and good predictive capabilities over a range of experimental conditions make the established model a useful tool in predicting retention behavior in the studied chromatographic system.