Relationships Between Aquatic Toxicity, Chemical Hydrophobicity, and Mode of Action: Log Kow Revisited.

Arch Environ Contam Toxicol

Office of Research and Development, U.S. EPA, U.S. EPA, 1 Sabine Island Drive, Gulf Breeze, FL, USA.

Published: November 2022

AI Article Synopsis

  • The study reassessed how different modes of action (MOA) affect the relationship between chemical hydrophobicity and aquatic toxicity, using a large database of 617 organic chemicals.
  • It found that quantitative structure-activity relationships (QSARs) based on specific MOAs significantly improve the accuracy of predicting lethal concentrations (LC50) for specific chemicals, compared to broader MOA classifications.
  • Additionally, both mass-based and mole-based toxicity data proved suitable for developing QSAR models, showing no clear trend for which produced better accuracy.

Article Abstract

Relationships between toxicity and chemical hydrophobicity have been known for nearly 100 years in mammals and fish, typically using the log of the octanol:water partition coefficient (Kow). The current study reassessed the influence of mode of action (MOA) on acute aquatic toxicity-log Kow relationships using a comprehensive database of 617 organic chemicals with curated and standardized acute toxicity data that did not exceed solubility limits, their consensus log Kow values, and weight of evidence-based MOA classifications (including 6 broad and 26 specific MOAs). A total of 166 significant (p < 0.05) log Kow-toxicity models were developed across six taxa groups that included QSARs for 5 of the broad and 13 of the specific MOAs. In this study, we demonstrate that QSARs based on MOAs can significantly increase LC50 prediction accuracy for specific acting chemicals. Prediction accuracy increases when QSARs are built based on highly specific MOAs, rather than broad MOA classifications. Additionally, we demonstrate that building QSAR models with chemicals in specific MOA groupings, rather than broader MOA groups leads to significantly better estimates. We also evaluated the differences between models developed from mass-based (µg/L) and mole-based (µmol/L) toxicity data and demonstrate that both are suitable for QSAR development with no clear trend in greater model accuracy. Overall, the results reveal that, despite high variance in all taxa and MOA groups, specific MOA-based models can improve the accuracy of aquatic toxicity predictions over more general groupings.Please check and confirm that the authors and their respective affiliations have been correctly identified and amend if necessary.The affiliations are correct.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11375592PMC
http://dx.doi.org/10.1007/s00244-022-00944-5DOI Listing

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