High-performance liquid chromatography of chalcones: Quantitative structure-retention relationships using partial least-squares (PLS) modeling

Abstract

In this study, the multivariate partial least squares projections to latent structures (PLS) technique was used for modeling the RP-HPLC retention data of 17 chalcones, which were determined with methanol-water mobile phases of different compositions. The PLS model was based on molecular descriptors which can be calculated for any compound utilizing only the knowledge of its molecular structure. The PLS analysis resulted in a model with the following statistics: r = 0.976, Q = 0.933, s = 0.076, and F = 43.63. The adequacy of the developed model was assessed by means of cross-validation and also, by PLS modeling of the retention data of several chalcones reported by Walczak et al. [J. Chromatogr. 353, 123, (1986)], which were obtained using stationary phases of different polarity (-NH2, DIOL, -CN, ODS, C8). The structural interpretation of the developed PLS model was accomplished by means of comparative correlations between the nonempirical descriptors used in the model and the solvation parameters developed by Abraham. The results obtained in this work provides evidence for the great potential of the topological approach for the development of quantitative structure-retention relationship (QSRR) models.