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Updated: May 20, 2025

In Silico Modeling Method for Computational Aquatic Toxicology of Endocrine Disruptors: A Software-Based Approach Using QSAR Toolbox
Published on: August 28, 2019
Predicting aquatic toxicity of anionic hydrocarbon and perfluorinated surfactants using membrane-water partition
Andrea Gredelj1,2, Jayne Roberts1, Eoin M Kearney3
1Safety, Environmental and Regulatory Science (SERS), Unilever, Colworth Park, Sharnbrook MK44 1LQ, UK. Jayne.Roberts@unilever.com.
Abstract:
Anionic surfactants are widely used in commercial and industrial applications. For assessment of their environmental fate and effects, it is highly desirable to quantify the membrane-water partition/distribution coefficient (Kmw/Dmw). Here, we further develop a computational route to Dmw for anionic surfactants based on coarse-grained molecular dynamics simulations, validating it against new and existing experimental measurements. Having parameterised molecular fragments for the coarse-grained models, the simulations are used to predict Dmw for molecules where no experimental values are available. This expanded set of simulated Dmw values is then used to derive QSARs for acute toxicity of mono-constituent anionic surfactants in daphnids and fish, allowing for extrapolation to similar compounds without experimental Dmw values. For this study, we have selected hydrocarbon-based (HC) surfactants because of their widespread use, and perfluorinated (FC) surfactants as a challenging case study. Separate daphnid and fish QSARs demonstrate good fits, robustness and predictivity, and highlight differing toxicity relationships for HC and FC surfactants in daphnids. Overall, the combined use of simulated Dmw and derived QSARs is a promising approach for ecotoxicity screening of surfactants.
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