Quantitative structure–activity relationships for prediction of the toxicity of hydroxylated and quinoid PCB metabolites

Quantitative structure–activity relationship (QSAR) models were developed for the in vitro potencies to downregulate gap junctional intercellular communication (GJIC) of hydroxylated polychlorinated biphenyls (OH-PCBs) and PCB quinines using partial least squares (PLS) regression. Quantum chemical descriptors computed by the semiempirical AM1, PM3 and MNDO methods were used as predictor variables. The cross-validated \(Q^{2}_{{{\text{cum}}}} \) values for the three optimal QSAR models are 0.784, 0.789 and 0.755, respectively, indicating good predictive capabilities for the acute inhibition of GJIC (IC50) of oxygenated PCB derivatives. The slightly higher \(Q^{2}_{{{\text{cum}}}} \) value of the model using computed molecular descriptors from the PM3 Hamiltonian suggested a slightly better predictive power than the models developed using AM1 or MNDO. However, given these dispersion parameters in these three optimal models, there would not be a significant difference between the \(Q^{2}_{{{\text{cum}}}} \) values. Results from this study showed that the logarithmic scale of IC50 is affected by different molecular structural descriptors.