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Updated: Sep 19, 2025

In Silico Modeling Method for Computational Aquatic Toxicology of Endocrine Disruptors: A Software-Based Approach Using QSAR Toolbox
Published on: August 28, 2019
QSAR Model Development for the Environmental Risk Limits and High-Risk List Identification of Phenylurea Herbicides
Jiajia Wei1,2, Liang Duan1,2, Jiangnan Zhao1,2
1Hubei Key Laboratory of Petroleum Geochemistry and Environment (Yangtze University), Wuhan 430100, China.
None:
Due to the extensive residues of phenylurea herbicides (PUHs) in the environment, it is important for the ecological risk assessment of PUHs to determine their environmental risk limits and identify the high-risk PUHs. This study derived the environmental risk limit (HC5) of PUHs based on the species sensitivity distribution method and obtained the molecular descriptors using the ORCA and Dragon software. Based on the derived HC5 and the molecular descriptors, quantitative structure-activity relationship (QSAR) models were developed to predict the HC5 values using multiple linear regression (MLR) and machine learning (ML) methods. Then, the ecological risk assessment was carried out based on the monitored environmental concentration and the predicted HC5, and a list of high-risk PUHs was proposed. The results indicated that the derived HC5 concentrations of 36 PUHs vary greatly, ranging from 0.0000084963 to 5.1512 mg/L. The performance of both the developed QSAR models by the MLR and RF methods met the OECD requirements. Comparatively, the RF model showed a better predictive performance, with a higher correlation coefficient between the experimental HC5 and predicted HC5 (R2 = 0.90) than the MLR model (R2 = 0.86). The developed QASR models also provided insights into the influence of the molecular descriptors on toxicity that the spatial structural descriptors, electronic descriptors, and hydrophobicity descriptors are key descriptors affecting the toxicity of PUHs. The high-risk PUH list from the ecological risk assessment demonstrated that the risk quotient of 10 PUHs (diuron, rimsulfuron, thifensulfuron-methyl, metsulfuron-methyl, metsulfuron, isoproturon, pyrazosulfuron, bensulfuron, tribenuron-methyl, and tebuthiuron) ranged from 4.39 to 2977.68, which are high-risk PUHs that should be given more attention. The obtained results can provide important basis for the ecological risk assessment of PUHs.
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