Classifying class I and class II compounds by hydrophobicity and hydrogen bonding descriptors

The successful development of quantitative structure-activity relationships (QSARs) and the prediction of toxicity based on QSARs depend on the correct classification of the mechanism of toxic action of chemical compounds. The toxicity mechanism of a compound can be determined by a few existing methods, such as studying the chemical structure of the compound for certain substructures and assigning a mechanism accordingly. However, these methods are less reliable for compounds with complex structures and are usually complicated. A novel descriptor-based method employing a multivariate statistical technique--discriminant analysis--was developed in this study for the classification of class I and class II compounds. The discriminating variables used in discriminant analysis were the hydrophobicity descriptor log(K(ow)) and the hydrogen bonding descriptors E(LUMO), E(HOMO), Q(+), and Q(-). Because only numerical values of these descriptors are required for this method, which can be calculated, no additional experimental work was required for the toxicity mechanism classification of new compounds. A nonlinear discriminant function was generated that could not be expressed explicitly. Assessing the predicting ability of the discriminant function by the cross-validation method showed that a low total error rate, 4.2% was achieved.