Statistical approach to chemicals classification

Principal component analysis was employed to test its applicability for classifying potential environmental contaminants by modes of action with respect to various targets. Discrimination of baseline from specific toxicants is necessary to allow the rational QSAR prediction from either log Pow or other descriptors, thus selecting the appropriate endpoints and models. Taking pesticides from different classes with known effects as an example, a reduction of the relevant toxicity parameters was achieved by combining data sets. Based on the principal components QSARs reflecting the underlying common processes were derived. The predominance of lipophilicity-dependent baseline toxicity is indicated for various classes of compounds with respect to most endpoints, whereas the pattern of excess toxicity revealed to be specific for each target. Multivariate statistics proved to be a useful tool to recognize compounds of analogous mode of action, as required for consecutive QSAR application.