A quantitative structure-property relationship analysis of soot-water partition coefficients for persistent organic pollutants
- 作者：Hui-Ying Xua ; xuhy65@163.com ; Jian-Wei Zoub ; Jian-Qing Mina ; Wei Wangc
- 关键词：Soot&ndash ; water partition coefficients ; Molecular electrostatic potential ; Quantitative structure&ndash ; property/activity relationship (QSPR/QSAR) ; Persistent organic pollutants
- 刊名：Ecotoxicology and Environmental Safety
- 出版年：2012
- 期刊代码：77_01476513
- 类别：env
- 出版时间：1 June, 2012
- 卷：80
- 期：Complete
- 页码：1-5
- 文件大小：249 K
摘要
Geometrical optimization and electrostatic potential calculations have been performed at the HF/6-31G鈦?/sup> level of theory for investigated persistent organic pollutants (POPs). A number of statistically based parameters have been obtained. Relationship between soot-water partition coefficients (log KSC) of POPs and the structural descriptors has been established by the multiple linear regression method. The result shows that the quantities derived from electrostatic potential and Vs,max, together with molecular surface area (AS) and the energy of the highest occupied molecular orbital (EHOMO) can be well used to express the quantitative relationship between structure and log KSC (QSPR) of POPs. Predictive capability of the model has been demonstrated by leave-one-out cross-validation with the cross-validated correlation coefficient of 0.9797. Furthermore, the predictive power of this model was further examined for the external test set with the correlation coefficient of 0.9811 between observed and predicted log KSC, validating the robustness and good predictive ability of our model. Furthermore, in order to further investigate the applicability of these parameters derived from electrostatic potential in prediction of soot-water partition coefficient for organic pollutants, eleven polycyclic aromatic hydrocarbons (PAHs), eleven polychlorinated biphenyls (PCBs) and nine phenyl urea herbicides (PUHs) from other source have also been studied. The QSPR models established may provide a new powerful method for predicting soot-water partition coefficients (log KSC) of organic pollutants.