QSAR models for predicting toxicity of polychlorinated dibenzo-p-dioxins and dibenzofurans using quantum chemical descriptors

Bulletin of Environmental Contamination and Toxicology
Jianxiong DiaoYing Sun

Abstract

By partial least square regression, simple quantitative structure-activity relationship (QSAR) models were developed for the toxicity of polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs). Quantum chemical descriptors computed by semi-empirical PM3 method were used as predictor variables. Three optimal QSAR models are developed for 25 PCDDs, 35 PCDFs, 25 PCDDs and 35 PCDFs together, respectively. The cross-validated Q (cum) (2) values for the three QSAR models of 25 PCDDs, 35 PCDFs, 25 PCDDs and 35 PCDFs together are 0.816, 0.629 and 0.603, respectively, indicating good predictive capabilities for the biological toxicity of these PCDD/Fs. The present study suggests that quantum chemical descriptors of POPs indeed govern the binding affinity of these chemicals for aryl hydrocarbon receptors. Moreover, different models contain different molecular descriptors to define respective equation, which suggests that the relationship between molecular structure and the binding affinity of these chemicals for aryl hydrocarbon receptors is complex.

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Citations

Jun 4, 2013·SAR and QSAR in Environmental Research·M LarssonP L Andersson
Nov 22, 2013·Journal of Cheminformatics·Svetoslav H SlavovRichard D Beger
Apr 16, 2013·Ecotoxicology and Environmental Safety·Xiaolin LiHongxia Yu
Oct 8, 2014·Journal of Asian Natural Products Research·Jing-Li ChengGuo-Nian Zhu
Jan 9, 2018·SAR and QSAR in Environmental Research·A D Şahin, M T Saçan
Dec 9, 2020·Molecules : a Journal of Synthetic Chemistry and Natural Product Chemistry·Sopanant Datta, Taweetham Limpanuparb

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