Prediction of n-octanol-water partition coefficient for polychlorinated biphenyls from theoretical molecular descriptors

Abstract

A quantitative structure-property relationship (QSPR) study was performed to develop models that relate the structures of 133 polychlorinated biphenyls to their n-octanol-water partition coefficients (log Kow). Molecular descriptors were derived solely from 3D structures of the molecules. The genetic algorithm-partial least squares (GA-PLS) method was applied as a variable selection tool. The partial least square (PLS) method was used to select the best descriptors and the selected descriptors were used as input neurons in neural network model.