QSARs on the depuration rate constants of polycyclic aromatic hydrocarbons in Elliptio complanata

Using quantum chemical descriptors and partial least squares (PLS) regression, a quantitative structure-activity relationships (QSARs) model was developed to predict the depuration rate constants (k_d) of polycyclic aromatic hydrocarbons (PAHs) for mussels, Elliptio complanata (log k_d=-2.1406±0.6013DE-2.0767 × 10^-3 M_w-0.201 E_HOMO). With a high cumulative cross-validated regression coefficient value (Q_cum²) of 0.927 and low standard deviation (SD) of 0.065, the model obtained by the training set shows a good predictive ability, and it is validated to be robust by predicting the test set. Among 20 quantum chemical descriptors, the dielectric energy (DE), the molecular weight (M_w), and the highest occupied molecular orbital energy (E_HOMO) are the key descriptors governing the logk_d values in the model. Increase in the DE or decrease in the M_w values leads to the increase in logk_d, indicating the van der Waals interactions and steric hindrance effect on the depuration process. Decrease in the E_HOMO values results in increasing the logk_d values, implying important roles the molecular orbital energies may play in the biological depuration of PAHs in mussels.