Binding affinities (AhR) of polychlorinated biphenyls (PCBs), dibenzo-p-dioxins (PCDDs) and dibenzofurans (PCDFs) study combining DFT and QSAR results

Quantitative Structure-Activity Relationship (QSAR) study was applied to the prediction of the binding interactions between PCBs, PCDDs, PCDFs, and AhR. The concentration of the test chemicals reducing specific binding of (3H) 50% pEC50 of 65 compounds were modeled using the parameters from quantum-chemical calculations at density functional theory level (B3LYP/6-31G (d,p)) were applied. It was expected that the main contribution to the degradation rate was given by the total energy ET. Principal Component Analysis (PCA) method, the Multiple Linear Regression method (MLR), Partial Multiple Non Linear Regression method (MNLR) and the Artificial Neural Network (ANN), showed a correlation coefficient more than 0,9. The prediction results were in excellent agreement with the experimental values; It is expected to be beneficial to predict the activity of other compounds in the same groups.