QSAR Models for Predicting Additive and Synergistic Toxicities of Binary Pesticide Mixtures on Scenedesmus Obliquus?

Pesticides released into the environment may pose potential risks to the ecological system and human health. However, existing toxicity data on pesticide mixtures still lack, especially regarding the toxic interactions of their mixtures. This study aimed to determine the toxic interactions of binary mixtures of pesticides on Scenedesmus Obliquus (S. obliquus) and to build quantitative structure-activity relationship models (QASR) for predicting the mixture toxicities. By applying direct equipartition ray method to design binary mixtures of five pesticides (linuron, dimethoate, dichlorvos, trichlorfon and metribuzin), the toxicity of a single pesticide and its mixture was tested by microplate toxicity analysis on S. obliquus. The QASR models were built for combined toxicity of binary mixtures of pesticides at the half-maximal effective concentration (EC50), 30% maximal effective concentration (EC30) and 10% maximal effective concentration (EC10). The results showed that the single toxicity follows: metribuzin > linuron > dichlorvos > trichlorfon > dimethoate. The mixtures of linuron and trichlorfon, dichlorvos and metribuzin, dimethoate and metribuzin induced synergetic effects, while the remaining binary mixtures exhibited additive. The developed QSAR models were internally validated using the leave-one-out cross-validation (LOO), leave-many-out cross-validation (LMO), bootstrapping, and y-randomization test, and externally validated by the test sets. All three QSAR models satisfied well with the experimental values for all mixture toxicities, and presented high internally (R-2 and Q(2) > 0.85) and externally (Q(2)F1, Q(2)F2, and Q(2)F3 > 0.80) predictive powers. The developed QSAR models could accurately predict the toxicity values of EC50, EC30 and EC10 and were superior to the concentration addition model's results (CA). Compared to the additive effect, the QSAR model could more accurately predict the binary mixture toxicities of pesticides with synergistic effects.

Automated summary

This study aimed to investigate the toxic interactions of pesticide mixtures and develop quantitative structure-activity relationship models for predicting their toxicities. The results showed that some pesticide mixtures exhibited synergistic effects. The developed models accurately predicted the toxicities of the mixtures and outperformed the traditional concentration addition model.