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Updated: Aug 18, 2026

In Silico Modeling Method for Computational Aquatic Toxicology of Endocrine Disruptors: A Software-Based Approach Using QSAR Toolbox
Published on: August 28, 2019
Predictability and prediction of lowest observed adverse effect levels in a structurally heterogeneous set of
J V de Julián-Ortiz1, R García-Domenech, J Gálvez
1Red de Investigación de Centros de Enfermedades Tropicales, Facultad de Farmacia, Universidad de Valencia, Burjasot, Spain.
Abstract:
A database of chronic lowest observed adverse effect levels (LOAELs) for 234 compounds, previously compiled from different sources (Toxicology Letters79, 131-143 (1995)), was modelled using graph theoretical descriptors. This study reveals that data are not homogeneous. Only those data originating from the U.S. Environmental Protection Agency (EPA) reports could be well modelled by multilinear regression (MLR) and linear discriminant analysis (LDA). In contrast, data available from the specific procedures of the National Toxicology Program (NTP) database introduced noise and did not render good models either alone, or in combination with the EPA data.
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