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    Quantitative structure-activity relationships for green algae growth inhibition by polymer particles.

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    Authors
    Nolte, Tom M
    Peijnenburg, Willie J G M
    Hendriks, A Jan
    van de Meent, Dik
    Type
    Article
    Language
    en
    
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    Title
    Quantitative structure-activity relationships for green algae growth inhibition by polymer particles.
    Published in
    Chemosphere 2017; 179:49-56
    Publiekssamenvatting
    After use and disposal of chemical products, many types of polymer particles end up in the aquatic environment with potential toxic effects to primary producers like green algae. In this study, we have developed Quantitative Structure-Activity Relationships (QSARs) for a set of highly structural diverse polymers which are capable to estimate green algae growth inhibition (EC50). The model (N = 43, R2 = 0.73, RMSE = 0.28) is a regression-based decision tree using one structural descriptor for each of three polymer classes separated based on charge. The QSAR is applicable to linear homo polymers as well as copolymers and does not require information on the size of the polymer particle or underlying core material. Highly branched polymers, non-nitrogen cationic polymers and polymeric surfactants are not included in the model and thus cannot be evaluated. The model works best for cationic and non-ionic polymers for which cellular adsorption, disruption of the cell wall and photosynthesis inhibition were the mechanisms of action. For anionic polymers, specific properties of the polymer and test characteristics need to be known for detailed assessment. The data and QSAR results for anionic polymers, when combined with molecular dynamics simulations indicated that nutrient depletion is likely the dominant mode of toxicity. Nutrient depletion in turn, is determined by the non-linear interplay between polymer charge density and backbone flexibility.
    DOI
    10.1016/j.chemosphere.2017.03.067
    PMID
    28363094
    URI
    http://hdl.handle.net/10029/621241
    ae974a485f413a2113503eed53cd6c53
    10.1016/j.chemosphere.2017.03.067
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