Density Functional Theory (B3LYP/6-31G*) Study of Toxicity of Polychlorinated Dibenzofurans
Sabitu Babatunde Olasupo,
Adamu Uzairu,
Balarabe Sarki Sagagi
Issue:
Volume 5, Issue 2, March 2017
Pages:
14-24
Received:
25 February 2017
Accepted:
22 March 2017
Published:
13 April 2017
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 (R2) = 0.963, R2adj = 0.955, cross-validation correlation coefficient (Q2) = 0.889, external prediction ability (R2pred) = 0.8286, P-value of optimization at P95% < 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.
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...
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