Citation: Ling-Yun MO, Bai-Kang YUAN, Jie ZHU, Li-Tang QIN, Jun-Feng DAI. QSAR Models for Predicting Additive and Synergistic Toxicities of Binary Pesticide Mixtures on Scenedesmus Obliquus[J]. Chinese Journal of Structural Chemistry, ;2022, 41(3): 220316. doi: 10.14102/j.cnki.0254-5861.2011-3306 shu

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

Ling-Yun MO ^{a, b, c} ,
Bai-Kang YUAN ^a ,
Jie ZHU ^a ,
Li-Tang QIN ^{a, b,,} ,
Jun-Feng DAI ^{a, d,,}

a.
College of Environmental Science and Engineering, Guilin University of Technology, Guilin 541004, China
b.
Guangxi Key Laboratory of Environmental Pollution Control Theory and Technology, Guilin University of Technology, Guilin, Guangxi 541004, China
c.
Technical Innovation Center of Mine Geological Environmental Restoration Engineering in Southern Karst Area, MNR, Nanning 530023, China
d.
Guangxi Collaborative Innovation Center for Water Pollution Control and Water Safety in Karst Area, Guilin University of Technology, Guilin 541004, China

Corresponding author: Li-Tang QIN, qinsar@163.com Jun-Feng DAI, whudjf@163.com
Received Date: 9 July 2021
Accepted Date: 13 October 2021

Fund Project: the National Key Research and Development Program of China 2019YFC0507502Guangxi Science and Technology Major Special Project Guike-AA2016004Natural Science Foundation of Guangxi Province 2018GXNSFAA281156Guilin Scientific Research and Technology Development Program 20180107-5Guilin Scientific Research and Technology Development Program 20180101-1

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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 (R² and Q² > 0.85) and externally (Q_F1², Q_F2², and Q_F3² > 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.
- pesticide,
- QSAR,
- toxicity prediction,
- binary mixture,
- algae
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