Predicting aquatic toxicity of anionic hydrocarbon and perfluorinated surfactants using membrane-water partition coefficients from coarse-grained simulations

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 (<i>K</i><sub>mw</sub>/<i>D</i><sub>mw</sub>). Here, we further develop a computational route to <i>D</i><sub>mw</sub> 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 <i>D</i><sub>mw</sub> for molecules where no experimental values are available. This expanded set of simulated <i>D</i><sub>mw</sub> 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 <i>D</i><sub>mw</sub> 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 <i>D</i><sub>mw</sub> and derived QSARs is a promising approach for ecotoxicity screening of surfactants.

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Publication Details

Journal
Environmental Science Processes & Impacts
Published
2025-01-01
DOI
https://doi.org/10.1039/d4em00649f
Citations
1
Primary Topic
Environmental Chemistry and Analysis
Type
article
Field-Weighted Citation Impact
0.86

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article

Predicting aquatic toxicity of anionic hydrocarbon and perfluorinated surfactants using membrane-water partition coefficients from coarse-grained simulations

Elin L. Barrett, Mark A. Miller, Nicola Haywood, Geoff Hodges et al.
1 citations
Environmental Science Processes & Impacts
Environmental Chemistry and Analysis
0.86
article

Predicting aquatic toxicity of anionic hydrocarbon and perfluorinated surfactants using membrane-water partition coefficients from coarse-grained simulations

Elin L. Barrett, Mark A. Miller, Nicola Haywood, Geoff Hodges, Jayne Roberts, David Sheffield, Andrea Gredelj, E. Kearney
article en
1 citations

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 (<i>K</i><sub>mw</sub>/<i>D</i><sub>mw</sub>). Here, we further develop a computational route to <i>D</i><sub>mw</sub> 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 <i>D</i><sub>mw</sub> for molecules where no experimental values are available. This expanded set of simulated <i>D</i><sub>mw</sub> 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 <i>D</i><sub>mw</sub> 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 <i>D</i><sub>mw</sub> and derived QSARs is a promising approach for ecotoxicity screening of surfactants.

Environmental Science Processes & ImpactsVol. 27(4)
Norwegian Geotechnical Institute (NO), Unilever (United Kingdom) (GB), Durham University (GB)
Durham University, Norges Forskningsråd, Engineering and Physical Sciences Research Council
Clean water and sanitation
Openalex Percentile: Top 30%
Environmental Chemistry and Analysis
0.86
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