QUANTITATIVE STRUCTURE-TOXICITY RELATIONSHIP (QSTR) STUDY OF POLYCHLORINATED DIBENZOFURANS USING QUANTUM CHEMICAL DESCRIPTORS
AbstractOne of the important aspects of modern toxicology research is the prediction of toxicity of environmental pollutants from their molecular structure A 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. The molecular descriptors were obtained by Density Functional Theory (DFT) (B3LYP/6-31G*) level of calculation. The QSTR model was built using Genetic Function Algorithm (GFA) method. The model with the best statistical significance (N = 24, Friedman LOF = 0.361, R2 = 0.963, R2adj. = 0.955 R2cv = 0.889, R2pred= 0.8286, P95% ˂ 0.05) 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 prediction results are expected to be useful in predicting and identify structural features responsible for the toxicity of the chemicals and other congeneric compounds that fall within the model’s applicability domain.
Article Information
2
175-186
838
581
English
IJLSR
S. B. Olasupo * , A. Uzairu and B. Sagagi
Department of Chemistry, Kano University of Science and Technology, Wudil Kano, Nigeria
olasabit@yahoo.com
20 August 2016
15 November 2016
11 December 2016
10.13040/IJPSR.0975-8232.IJLSR.2(12).175-86
31 December 2016
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