Prediction of vapour pressures for halogenated diphenyl ether congeners from molecular descriptors

Polychlorinated diphenyl ethers (PCDE) and polybrominated diphenyl ethers (PBDE) have both been identified as environmental contaminants. The physical properties are important in determining the distribution and fate of organic contaminants in the environment. The purpose of the present investigation was to characterise halogenated diphenyl ethers using computationally derived descriptors, and to develop calibration models for the vapour pressure from published experimental data.

Experimental data for vapour pressures were obtained from the literature. The chemical structure of each PCDE and PBDE congener was optimised prior to descriptor generation. The data analysis was performed using principal component analysis (PCA) and partial least squares regression (PLSR). The calibration models were validated with external test sets.

All congeners of PCDEs and PBDEs were characterised by 795 molecular descriptors and two principal components could account for about two thirds of the variance within each group. Bilinear calibration models were developed that could explain 99.4% of the variance in the external validation test sets. Vapour pressures were subsequently predicted for all congeners that were adequately described by these calibration models. The type and number of halogen atoms in the molecule were the main factors influencing the vapour pressures of halogen substituted diphenyl ethers, but the variations in substitution pattern was also shown to be a significant factor.

The molecular descriptor patterns of halogenated aromatic compounds such as diphenyl ethers can be described and interpreted using principal component analysis (PCA). The major sources of variation in the descriptor spaces for PCDEs and PBDEs are the same as those contributing to the differences in vapour pressure, similar to what has previously been reported for the PCBs. The bilinear calibration models for vapour pressure presented here, has a standard error of prediction that is lower than what is reported as the experimental uncertainty or observed as deviations between experimental investigations. The estimated prediction errors are expected to be within the reported boundaries when the models are applied to new objects within the same molecular descriptor space, and model predictions can hence extend the current database of experimental values.

The results from this investigation and others show that the establishment of quantitative structure-property relationships (QSPR) is a viable approach to estimate physical properties for halogenated diphenyl ethers. It is easy to foresee an increased need for using QSPR estimation methods in the future, for evaluation of the environmental fate for organic pollutants. Despite method developments and automation, it is unlikely that laboratory determinations can cope with the pace that new pollutants are identified.