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In Silico Modeling Method for Computational Aquatic Toxicology of Endocrine Disruptors: A Software-Based Approach Using QSAR Toolbox
Published on: August 28, 2019
Toxicity prediction of dioxins and dioxins-like compounds based on the molecular fragments variable connectivity
Qiang Chen1, Jingmin Sun, Jing Liu
1College of Atmospheric Sciences, Lanzhou University, 222 Tianshui South Road, Lanzhou, People's Republic of China. chenqqh@163.com
Abstract:
The toxicity of 95 doxins and dioxin-like compounds was investigated by quantitative structure-activity relationship (QSAR) with the molecular fragments variable connectivity index (mfVCI). For each of the four homologues, the models have good fitting (R² > 0.80) and predictive (Q²EXT > 0.80) ability. The models developed from more than one homologues are also satisfactory with R² > 0.80 and Q²EXT > 0.77. The molecular fragments weights have the ability to diagnose the contribution of the molecular fragments to the toxicity of the compounds. The mfVCI may play an important role in the development of molecular descriptors in further QSAR research.
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