QSAR and chemometric approaches for setting water quality objectives for dangerous chemicals

In order to evaluate environmentally safe levels of dangerous chemicals, there is the need for a set of toxicological data on organisms representative of the ecosystems, which is often unavailable or inadequate. In this article, a predictive approach was applied to a set of 125 chemicals (derived from the European priority list in compliance with Directive 76/464/EEC), for which water quality objectives were available. Toxicological data on organisms representative of the aquatic environment (algae, Daphnia, and fish) were taken from the literature or predicted by means of quantitative structure--activity relationships. This provided toxicological data on all three organisms for 97 of 125 chemicals and on at least two organisms (Daphnia and fish) for the whole data set. Principal Component Analysis was applied in order to perform an a priori classification of chemicals based on toxicity data. Then several classification models, based on traditional and nontraditional molecular descriptors, were applied. Classification models gave results in agreement with the a priori classification as well as with the original water quality objectives classification. The behavior of some outliers was explained. The approach described appears to be a useful tool for the preliminary classification of chemicals that are dangerous to the aquatic environment for which toxicological data are inadequate.