Journal
JOURNAL OF CHEMICAL INFORMATION AND COMPUTER SCIENCES
Volume 43, Issue 4, Pages 1240-1247Publisher
AMER CHEMICAL SOC
DOI: 10.1021/ci0340660
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A Quantitative Structure-Property Relationship (QSPR) model is developed to calculate the solute polarity parameter p of a set of 233 compounds of a very different chemical nature. The proposed model, derived from multiple linear regression, contains four descriptors calculated from the molecular structure and the well-known hydrophobicity parameter log P-o/w. According to the statistics obtained with the prediction set, the model has a very good prediction capacity (R-2 = 0.954, F = 889, n = 45, and SD = 0.27). The study shows that log P-o/w and hydrogen bond acidity of the solutes are the most relevant descriptors to predict p values. This p parameter is embodied in a general equation to predict retention in reversed-phase liquid chromatography (RP-HPLC). It describes analyte retention exclusively on the basis of mobile phase/analyte/stationary phase polar interactions. Equations and procedures to determine polarity of both chromatographic phases had been successfully developed previously. Therefore, the proposed QSPR model for p estimation becomes a very useful toot in RP-HPLC optimization of procedures and methods in the everyday analytical work.
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