Toxicity of binary mixtures of pesticides and pharmaceuticals toward Vibrio fischeri: Assessment by quantitative structure-activity relationships

Pollutants in real aquatic systems commonly occur as chemical mixtures. Yet, the corresponding risk assessment is still mostly based on information on single-pollutant toxicity, accepting the assumption that pollutant mixtures exhibit additive toxicity effect which is often not the case. Therefore, it is still better to use the experimental approach. Unfortunately, experimental determination of toxicity for each mixture is practically unfeasible. In this study, quantitative structure-activity relationship (QSAR) models for the prediction of toxicity of binary mixtures towards bioluminescent bacteria Vibrio fischeri were developed at three toxicity levels (EC10, EC30 and EC50). For model development, experimentally determined toxicity values of 14 pollutants (pharmaceuticals and pesticides) were correlated with their structural features, applying multiple linear regression together with genetic algorithm. Statistical analysis, internal validation and external validation of the models were carried out. The toxicity is accurately predicted by all three models. EC30 and EC50 values are mostly influenced by geometrical distances between nitrogen and sulfur atoms. Furthermore, the simultaneous presence of oxygen and chlorine atoms in mixture can induce the increase in toxicity. At lower effect levels (EC10), nitrogen atom bonded to different groups has the highest impact on mixture toxicity. Thus, the analysis of the descriptors involved in the developed models can give insight into toxic mechanisms of the binary systems. (C) 2020 Published by Elsevier Ltd.

Automated summary

The study focuses on developing QSAR models to predict the toxicity of binary mixtures towards bioluminescent bacteria Vibrio fischeri. The models successfully predict toxicity and identify factors influencing toxicity levels. The analysis of descriptors in the models provides insight into toxic mechanisms of binary systems.