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Updated: Apr 17, 2026

In Silico Modeling Method for Computational Aquatic Toxicology of Endocrine Disruptors: A Software-Based Approach Using QSAR Toolbox
Published on: August 28, 2019
QSAR models for bioconcentration: is the increase in the complexity justified by more accurate predictions?
Francesca Grisoni1, Viviana Consonni1, Sara Villa2
1Milano Chemometrics and QSAR Research Group, Milano, Italy; Dept. of Earth and Environmental Sciences, University of Milano-Bicocca, P.za della Scienza 1, 20126 Milano, Italy.
Abstract:
This study compares nine QSAR models for the prediction of BCF on fish: four KOW based models (Veith, Mackay, Bintein and TGD equations) and five complex models (EPI Suite BCFBAF, VEGA CAESAR, VEGA Meylan, VEGA Read-across and VEGA consensus). The aim is to test if increasing complexity leads to predictions that are more accurate than those based only on KOW are. To this end, experimental BCF data for 1056 compounds, along with experimental and predicted KOW values, were collected and used for the comparison. A particular focus has been placed on compounds for which metabolism, elimination and specific interactions with tissues can be hypothesized. VEGA Read-across improved global predictions with respect to the KOW based models and resulted to be a good approach to take into account metabolism and interactions with tissues. For the other complex models, several drawbacks were highlighted. Finally, for different classes of compounds (i.e. Perfluorinated Compounds, Organophosphorous Compounds, Synthetic Pyrethroids and Polychlorinated Biphenyls) results confirmed the mechanistic interpretation of the processes involved in their bioconcentration.
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