Abstract
Quantitative Structure Toxicity Relationship (QSTR) study was applied to a dataset of 35 polychlorinated dibenzofurans (PCDFs) to investigate the relationship between toxicities of the compounds and their structures by employing Density Functional Theory (DFT) (B3LYP/6-31G*) method to compute their quantum molecular descriptors. The model was built using Genetic Function Algorithm (GFA) approach. The model (N= 24, Friedman LOF = 0.361, squared correlation coefficient (R<sup>2</sup>) = 0.963, R<sup>2</sup>adj = 0.955, cross-validation correlation coefficient (Q<sup>2</sup>) = 0.889, external prediction ability (R<sup>2</sup><sub>pred</sub>) = 0.8286, P-value of optimization at P<sub>95%</sub> < 0.05) of the best statistical significance was selected. The accuracy of the model was evaluated through Leave one out (LOOV) cross-validation, external validation using test set molecules, Y-randomization and applicability domain techniques. The results of the present study are expected to be useful to the environmental regulatory agencies locally and internationally in the area of environmental risk assessment of toxicity of Polychlorinated dibenzofurans (PCDFs) and other related Polychlorinated aromatic compounds/ pollutants that fall within the model’s applicability domain.
Highlights
One of the important aspect of modern toxicology research is the prediction of toxicity of environmental pollutants from their molecular structure in which a quantitative risk assessment becomes increasingly important in the modern society and is slowly incorporated into legislation of different countries
The aim of this study is to build a robust, reliable and rational Genetic Function Algorithm approximation (GFA) based Quantitative Structure Toxicity Relationship (QSTR) models to predict the toxicity of Polychlorinated dibenzofurans (PCDFs) by exploring the correlations between the experimental log (1/EC50) of the compounds and their calculated molecular descriptors
Data Collection A data set of Polychlorinated dibenzofurans (35 PCDFs) used for the QSTR analysis was selected from the literature [10]
Summary
One of the important aspect of modern toxicology research is the prediction of toxicity of environmental pollutants from their molecular structure in which a quantitative risk assessment becomes increasingly important in the modern society and is slowly incorporated into legislation of different countries. One of the important aspect of modern toxicology research is the prediction of toxicity of environmental pollutants from their molecular structure. Polychlorinated dibenzofurans (PCDFs) are polychlorinated aromatic compounds that represent a group of environmental contaminants known by their ubiquitous distribution, resistance to biological and chemical degradation, high toxicity and bioaccumulation [2]. They can have a significant impact on the health and well-being of human and animals [2]. Several persistent organic pollutants (e.g. PCDFs) are suspected to contribute to the increasing prevalence and risk of type 2 diabetes [4]
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