MOAtox: A comprehensive mode of action and acute aquatic toxicity database for predictive model development

Area of Science:

• Environmental Toxicology
• Computational Chemistry
• Ecotoxicology

Background:

• Mode of action (MOA) is crucial for predicting chemical toxicity, offering an alternative to traditional class-based modeling.
• Development of predictive toxicity models is hindered by a lack of high-quality MOA and toxicity databases.

Purpose of the Study:

• To develop a standardized dataset of MOA assignments and associated aquatic toxicity values for 1213 diverse chemicals.
• To facilitate the creation of quantitative structure-activity relationship (QSAR) and other predictive toxicology models.

Main Methods:

• Assigned MOAs using consensus classifications, QSAR predictions, and expert judgment for 1213 chemicals.
• Compiled a toxicity database of 674 acute values for fish and invertebrates, linked to MOAs.
• Generated species-specific acute toxicity values for key aquatic species, estimating where necessary using Web-ICE.

Main Results:

• A dataset of 1213 chemicals with assigned MOAs (6 broad, 31 specific) was created.
• A linked toxicity database of 674 acute values for fish and invertebrates was developed.
• Standardized, high-confidence toxicity data for rainbow trout, fathead minnow, bluegill, and Daphnia magna were compiled.

Conclusions:

• The developed dataset provides a valuable resource for advancing predictive aquatic toxicology.
• This standardized data supports the development of more accurate QSAR and MOA-based toxicity models.
• The findings enhance chemical risk assessment by improving the prediction of environmental hazards.