Quantitative Structure–Activity Relationship (QSAR) Modeling of EC₅₀ of Aquatic Toxicities for Daphnia magna

Abstract

The experimental EC₅₀ toxicities toward Daphnia magna for a series of 130 benzoic acids, benzaldehydes, phenylsulfonyl acetates, cycloalkane-carboxylates, benzanilides, and other esters were studied using the Best multilinear regression algorithm (BMLR) implemented in CODESSA. A modified quantitative structure–activity relationships (QSAR) procedure was applied guaranteeing the stability and reproducibility of the results. Separating the initial data set into training and test subsets generated three independent models with an average R² of .735. A five-descriptor general model including all 130 compounds, constructed using the descriptors found effective for the independent subsets, was characterized by the following statistical parameters: R² = .712; R²_cv = .676; F = 61.331; s² = 0.6. The removal of two extreme outliers improved significantly the statistical parameters: R² = .759; R²_cv = .728; F = 77.032; s² = 0.499. The sensitivity of the general model to chance correlations was estimated by applying a scrambling procedure involving 20 randomizations of the original property values. The resulting R² = .192 demonstrated the high robustness of the model proposed. The descriptors appearing in the obtained models are related to the biochemical nature of the adverse effects. An additional study of the EC₅₀/LC₅₀ relationship for a series of 28 compounds (part of our general data set) revealed that these endpoints correlated with R² = .98.

Acknowledgements

We thank the Keenan Professorship Fund for partial support of this work.