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Updated: May 16, 2025

In Silico Modeling Method for Computational Aquatic Toxicology of Endocrine Disruptors: A Software-Based Approach Using QSAR Toolbox
Published on: August 28, 2019
Exploring the reactivity of high-valent copper species with emerging contaminants using predictive QSAR modelling
Tao Zhao1, Minghao Xu1, Xuerui Yang1
1State Environmental Protection Key Lab of Environmental Risk Assessment and Control on Chemical Processes, School of Resources and Environmental Engineering, East China University of Science and Technology, Shanghai, People's Republic of China.
Abstract:
High-valent metal species (HVMS) exhibited exceptional oxidative capabilities and selectivity in advanced oxidation processes (AOPs), making them promising oxidants for environmental remediation. However, their inherent instability has hindered kinetic assessments and limited further applications. This study developed a quantitative structure-activity relationship (QSAR) model for predicting the pseudo-first order rate constants (kobs) of high-valent copper species Cu(III) with typical emerging contaminants (ECs). The optimal model was logkobs = 0.002×PSA - 10.1465 × q(C-)X - 4.5896 × ELUMO - 2.0116. R2adj (0.822), Q2LOO (0.784), and Q2ext (0.951) shown the model's robust and great predictive ability. Polar surface area (PSA), Hirshfeld charge on carbon atoms (q(C-)X), and the energy of the lowest unoccupied molecular orbital (ELUMO) synergistically controlled the reactivity of Cu(III). A larger PSA was conducive to the diffusion of ECs in aquatic environments. Additionally, Density functional theory (DFT) calculations revealed that a smaller q(C-)X could increase the nucleophilic sites of ECs, thereby enhancing the electrophilic reaction of Cu(III). And a lower ELUMO was beneficial for adjusting the energy gap (EGAP) to enhance the reactivity of ECs. This study filled the gap in the prediction of kobs for Cu(III) and provided a reliable reference for the selective treatment of different ECs by HVMS.
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