ABSTRACT
Quantitative structure– chromatographic retention relationships (QSRRs) depend on the chromatographic retention of the analyte including the chemical structure and physicochemical properties of stationary and mobile phases in liquid chromatography. In order to analyze the QSRR, two sets of data are collected: a set of parameters describing the retention of the analyte series and a set of structural parameters of separated molecules. QSRR has its origins in thin-layer chromatography (TLC). It is a powerful theoretical tool for the description and prediction of molecular systems in chromatographic research. In the QSRR approach, the relationship between chromatographic parameters and some molecular descriptors can be examined by the linear modeling methods, such as linear regression (LR), multiple linear regression (MLR), principal component regression, and partial least squares (PLS) regression. In the other QSRR model, retention depends on the specific descriptors obtained using molecular modeling. The QSRR approach can also be applied to present the retention models on noncommercial self-prepared stationary phases.
