QUANTITATIVE STRUCTURE-TOXICITY RELATIONSHIP (QSTR) STUDY OF POLYCHLORINATED DIBENZOFURANS USING QUANTUM CHEMICAL DESCRIPTORSAbstract
One 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.
S. B. Olasupo * , A. Uzairu and B. Sagagi
Department of Chemistry, Kano University of Science and Technology, Wudil Kano, Nigeria
20 August 2016
15 November 2016
11 December 2016
31 December 2016