Externally predictive single-descriptor based QSPRs for physico-chemical properties of polychlorinated-naphthalenes: Exploring relationships of logS(W), logK(OA), and logK(OW) with electron-correlation

Quantitative structure-property relationships (QSPRs), based only on a single-parameter, are proposed for the prediction of physico-chemical properties, namely, aqueous solubility (logSW), octanol-water partition coefficient (logKOW) and octanol-air partition coefficient (logKOA) of polychloronaphthalenes (PCNs) including all the 75 chloronaphthalene congeners. The QSPR models are developed using molecular descriptors computed through quantum mechanical methods including ab-initio as well as advanced semi-empirical methods. The predictivity of the developed models is tested through state-of-the-art external validation procedures employing an external prediction set of compounds. To analyse the role of instantaneous interactions between electrons (the electron-correlation), the models are also compared with those developed using only the electron-correlation contribution of the quantum chemical descriptor. The electron-correlation contribution towards the chemical hardness and the LUMO energy are observed to be the best predictors for octanol-water partition coefficient, whereas for the octanol-air partition coefficient, the total electronic energy and electron-correlation energy are found to be reliable descriptors, in fact, even better than the polarisability. For aqueous solubility of PCNs, the absolute electronegativity is observed to be the best predictor. This work suggests that the electron-correlation contribution of a quantum-chemical descriptor can be used as a reliable indicator for physico-chemical properties, particularly the partition coefficients.