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

Chemosphere 2017 39 citations ? Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count. Score: 30 ? 0–100 AI score estimating relevance to the microplastics field. Papers below 30 are filtered from public browse.

Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Tom M. Nolte, Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Tom M. Nolte, Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg A. Jan Hendriks, Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg A. Jan Hendriks, Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Dik van de Meent, Dik van de Meent, A. Jan Hendriks, A. Jan Hendriks, Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg Willie J.G.M. Peijnenburg

Summary

Researchers built mathematical models to predict how toxic different polymer particles are to green algae, finding that the electric charge and structural properties of a polymer determine how much it inhibits algal growth. The models revealed that positively charged polymers harm algae by disrupting their cell walls, while negatively charged ones act mainly by depleting nutrients — a distinction important for assessing the environmental risks of microplastics and polymer-based products.

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, R<sup>2</sup> = 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.

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