title: A quantitative structure-property relationship analysis of soot-water partition coefficients for persistent organic pollutants.
abstract: Geometrical optimization and electrostatic potential calculations have been performed at the HF/6-31G level of theory for investigated persistent organic pollutants (POPs). A number of statistically based parameters have been obtained. Relationship between soot-water partition coefficients (logK(SC)) 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 V(s)(-)¯ and V(s,max), together with molecular surface area (A(S)) and the energy of the highest occupied molecular orbital (E(HOMO)) can be well used to express the quantitative relationship between structure and logK(SC) (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 logK(SC), 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 (logK(SC)) of organic pollutants.
authors.affiliation: College of Biology & Environment Engineering, Zhejiang Shuren University, Hangzhou 310015, China. xuhy65@163.com
authors.forename: Hui-Ying
authors.initials: HY
authors.lastname: Xu
authors.forename: Jian-Wei
authors.initials: JW
authors.lastname: Zou
authors.forename: Jian-Qing
authors.initials: JQ
authors.lastname: Min
authors.forename: Wei
authors.initials: W
authors.lastname: Wang
mesh_terms: D015386:Hazardous Substances / Q000032:analysis*; D016014:Linear Models; D008956:Models, Chemical; D011078:Polychlorinated Biphenyls / Q000032:analysis / Q000737:chemistry; D011084:Polycyclic Aromatic Hydrocarbons / Q000032:analysis / Q000737:chemistry; D021281:Quantitative Structure-Activity Relationship; D053260:Soot / Q000737:chemistry*; D055672:Static Electricity; D014867:Water / Q000737:chemistry*
chemical_list: D015386:Hazardous Substances; D011084:Polycyclic Aromatic Hydrocarbons; D053260:Soot; D014867:Water; D011078:Polychlorinated Biphenyls