pKa Prediction for Acidic Phosphorus-Containing Compounds Using Multiple Linear Regression with Computational Descriptors

Ninety-six acidic phosphorus-containing molecules with pK(a) 1.88 to 6.26 were collected and divided into training and test sets by random sampling. Structural parameters were obtained by density functional theory calculation of the molecules. The relationship between the experimental pK(a) values and structural parameters was obtained by multiple linear regression fitting for the training set, and tested with the test set; the R-2 values were 0.974 and 0.966 for the training and test sets, respectively. This regression equation, which quantitatively describes the influence of structural parameters on pK(a), and can be used to predict pK(a) values of similar structures, is significant for the design of new acidic phosphorus-containing extractants. (C) 2016 Wiley Periodicals, Inc.