Prediction of octanol-air partition coefficients for PCBs at different ambient temperatures based on the solvation free energy and the dimer ratio

Abstract

h i g h l i g h t sA predictive model for log K OA of PCBs was developed based on △G OA . The optimal combination of theoretical method and basis-set was HF/MIDI!6D. The model was improved after taking the dimer formation into account. Log K OA values of PCBs at different ambient temperatures were predicted.

Modelling the octanol-air partition coefficient of aromatic pollutants based on the solvation free energy and the dimer effect

“…Among them, the Solvation Model Density (SMD) model (Marenich et al, 2009) is one of the most precise continuum solvation models due to its consideration of the first solvation shell. In our previous study, it was found that ΔG OA values of polychlorinated biphenyls (PCBs) calculated by the SMD model based on the HF/MiDi!6D level were in accordance with the experimental values (Li et al, 2020). However, it is not known if it can be generalized to other organic pollutants.…”

“…Given the higher lipophilicity, the presence of more aggregates is expected to raise the apparent K OA values relative to the theoretically predictive values based on monomers only. As for dimers and polymers, it has been showed that taking dimers into account without polymers could effectively improve the prediction of K OA of PCBs already (Li et al, 2020). Therefore, it is desirable to consider the effect of dimers when K OA values of these aromatic pollutants are estimated, which could not only improve the prediction of K OA , but also simplify the calculation and analyses.…”

Reliable Prediction of the Octanol–Air Partition Ratio

“…Many of these QSARs are focused on predicting the K OA of a specific subset of closely related Accepted Article chemicals (e.g. PCDDs (Chen et al 2002;Zeng et al 2013); PBDEs (Chen et al 2003a;Xu et al 2007;Liu et al 2013); PCNs (Chen et al 2003b); PCBs (Chen et al 2003c;Chen et al 2016;Yuan et al 2016;Li et al 2020); PAHs (Ferreira 2001)) and are therefore too limited in their applicability domain for most purposes.…”

“…QSARs are commonly used in the pharmaceutical industry and in environmental science and chemistry to predict a property of a chemical based on its structure. Many of these QSARs are focused on predicting the K OA of a specific subset of closely related chemicals, for example, polychlorinated dibenzo‐ p ‐dioxins (PCDDs; Chen et al, 2002 ; Zeng et al, 2013 ), polybrominated diphenyl ethers (PBDEs; Chen et al, 2003a ; Liu et al, 2013 ; Xu et al, 2007 ), polychlorinated naphthalenes (PCNs; Chen et al, 2003b ), polychlorinated biphenyls (PCBs; Chen et al, 2003c ; Chen et al, 2016 ; Li et al, 2020 ; Yuan et al, 2016 ), and polycyclic aromatic hydrocarbons (PAHs; Ferreira, 2001 ); thus they are too limited in their applicability domain for most purposes.…”

Monte Carlo based QSGFEAR: prediction of Gibb's free energy of activation at different temperatures using SMILES based descriptors

“…20 Rigorous validation and a well-defined applicability domain are the critical components for the future success of a QSPR/QSAR model, regardless of model structure or fitting technique. 21,22 QSPR/QSAR modelling plays a significant role in predicting various physicochemical properties 23 that is evident from the numerous reports available in the literature such as pK a , 24 aqueous solubility, 25 melting point, 26,27 flammability limit, 28 soil sorption coefficient, 29 refractive indices, 30,31 adsorption coefficient, 32 octanol-air partition coefficients, 33 Henry's law constant, 34 dielectric constant, 35 critical temperature, decomposition temperature, 36,37 thermal conductivity, 38 viscosity, enthalpy of vaporisation, 39 Gibbs free energy of solvation 40 and sublimation, 41 enthalpy of formation, 42 heat capacity (C) at variable temperatures 43 and many others. Gibb's free energy of activation (DG ‡ ) is an important physicochemical property for dynamic systems and QSPR/QSAR provides an accurate, robust and reliable mathematical equation to predict its values.…”