A new approach to QSAR modelling of acute toxicity†

Abstract

A new QSAR approach based on a Quantitative Neighbourhoods of Atoms description of molecular structures and self-consistent regression was developed. Its prediction accuracy, advantages and limitations were analysed from three sets of published experimental data on acute toxicity: 56 phenylsulfonyl carboxylates for Vibrio fischeri; 65 aromatic compounds for the alga Chlorella vulgaris and 200 phenols for the ciliated protozoan Tetrahymena pyriformis. According to our findings, the proposed approach provides a good correlation and prediction accuracy (r 2 = 0.908 and Q 2 = 0.866) for the set of 56 phenylsulfonyl carboxylates and the 65 aromatic compounds tested on C. vulgaris (r 2 = 0.885, Q 2 = 0.849). For the 200 phenols tested on T. pyriformis, the prediction accuracy was r 2 = 0.685 and Q 2 = 0.651. This is at least as good as the best results obtained with the other QSAR methods originally used on the same data sets. †Presented at the 12th International Workshop on Quantitative Structure-Activity Relationships in Environmental Toxicology (QSAR2006), 8–12 May 2006, Lyon, France.