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Updated: Jan 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
Evaluation of Endocrine Disruptome and VirtualToxLab for Predicting Per- and Polyfluoroalkyl Substances Binding to
Nina Franko1, Manca Vetrih1, Marija Sollner Dolenc1
1Department of Pharmaceutical Chemistry, Faculty of Pharmacy, University of Ljubljana, SI-1000 Ljubljana, Slovenia.
Abstract:
This study investigated whether the Endocrine Disruptome and VirtualToxLab in silico platforms are suitable for predicting the endocrine disrupting effects of per- and polyfluoroalkyl substances (PFASs)-in particular, for interactions with oestrogen receptors (ERs) and androgen receptor (AR). Compounds included in the U.S. Environmental Protection Agency's PFAS working list were analysed with both models, and the results were compared with the available in vitro data regarding their modulation of nuclear receptors. Based on the identified prediction parameters, such as sensitivity, specificity, accuracy, and Mathews' correlation coefficient, VirtualToxLab was found to be a reliable model for predicting the reactivity of PFASs with AR, while a positive consensus approach of both platforms provided reliable predictions of the PFAS reactivity with ERα and ERβ. This study provides the evidence that Endocrine Disruptome and VirtualToxLab can be used as a tier 1 screening tool for assessment of the endocrine disrupting effect of PFASs. Furthermore, it demonstrates that the likelihood of endocrine disrupting properties increases with the lipophilicity of PFASs and identifies the understudied PFHpS, PFNS, PFDS, 9-Cl, NMeFOSAA, NEtFOSAA, 4:2 FTS, 6:2 FTS, 8:2 FTS, 6:2 monoPAP, 8:2 monoPAP, and 5:3 acid as potential ligands of AR and/or ERs.

