In Chemosphere
Benzotriazole ultraviolet stabilizers (BUVSs), as light stabilizers, have attracted widespread attention because of their easy migration in the environment and their acute toxicity and biological toxicity effects, such as immunotoxicity and hepatotoxicity. Accordingly, the treatment and remediation mechanisms of high-performance, environmentally friendly, and low human health risk BUVS substitutes were analyzed. Firstly, the weights and the comprehensive effect (CE) values of migration and toxicity of BUVSs were determined by Topsis assisted by the coefficient of variation (CV) method. From this, a three-dimensional quantitative structure activity relationship (3D-QSAR) model based on the CE values of the 13 BUVSs was constructed. Secondly, EPI software was used to predict the functionality and environmental friendliness of BUVS substitutes, and a partial least squares regression machine learning (ML-PLSR) model was used to analyze the mechanism. Then, ADMET (absorption, distribution, metabolism, excretion, toxicity), TOPKAT, and exposure dose models were used to evaluate the ecological and human health risks of BUVSs and their substitutes. Finally, the key charge information affecting the UV-326 substitutes was deduced by time dependent density functional theory (TDDFT). Using UV-326 as an example, 15 UV-326 substitutes with reduced CE values were designed (reductions of 2.61%-23.18%). Compared with ML-PLSR models of acute toxicity, immunotoxicity, and hepatotoxicity, it was found that the decrease of DM and Qyy values and the increase of Qzz value could further decrease the toxicity of the UV-326 substitutes. Ecological and human health risk assessment showed that the exposure risks of the six UV-326 substitutes were within acceptable limits. TDDFT showed that the change of electron distribution and electron excitation type were the key factors affecting the performance of the UV-326 substitutes, and a charge transfer excitation type was more conducive to obtaining high-performance, environmentally friendly UV-326 substitutes. This study aims to alleviate the toxic damage to the ecological environment and human health caused by BUVS exposure.
Xue Jiaqi, Chen Xinyi, Zhao Yuanyuan, Li Yu
2023-Jan-03
Benzotriazole, Coefficient of variation method, Environmental friendliness, Machine learning, Pearson correlation coefficient method, ultraviolet Absorbent
