Determination of Abraham solute parameters from molecular structure.

Abstract

The Abraham solute parameters are well-known factors for the quantitative description of solute/solvent interactions. A quantitative structure-property relationship (QSPR) is reported for the E, S, A, and B parameters of a large set of 457 solutes, of very different chemical nature. The proposed models, derived from multilinear regression analysis (MLRA) and computational neural networks (CNN), contain five descriptors calculated solely from the molecular structure of compounds. Good correlations were obtained for the four parameters studied, and the corresponding values of R(2) and standard deviations are better or similar than those derived from other theoretical bases. All models were validated by external prediction sets. The proposed QSPR models, both by MLRA and CNN, contain analogous descriptors encoding similar information, that agree with the accepted physicochemical meaning of the Abraham parameters; however, some descriptors which encode information that is not associated with this physicochemical meaning are also included in the QSPR models.