title: QSAR models for predicting octanol/water and organic carbon/water partition coefficients of polychlorinated biphenyls.
abstract: Quantitative structure-property relationship modelling can be a valuable alternative method to replace or reduce experimental testing. In particular, some endpoints such as octanol-water (KOW) and organic carbon-water (KOC) partition coefficients of polychlorinated biphenyls (PCBs) are easier to predict and various models have been already developed. In this paper, two different methods, which are multiple linear regression based on the descriptors generated using Dragon software and hologram quantitative structure-activity relationships, were employed to predict suspended particulate matter (SPM) derived log KOC and generator column, shake flask and slow stirring method derived log KOW values of 209 PCBs. The predictive ability of the derived models was validated using a test set. The performances of all these models were compared with EPI Suite™ software. The results indicated that the proposed models were robust and satisfactory, and could provide feasible and promising tools for the rapid assessment of the SPM derived log KOC and generator column, shake flask and slow stirring method derived log KOW values of PCBs.
authors.affiliation: a Key Laboratory of Natural Medicine and Immune Engineering of Henan Province , Henan University , Kaifeng , China.
authors.forename: S
authors.initials: S
authors.lastname: Yu
authors.affiliation: a Key Laboratory of Natural Medicine and Immune Engineering of Henan Province , Henan University , Kaifeng , China.
authors.forename: S
authors.initials: S
authors.lastname: Gao
authors.affiliation: a Key Laboratory of Natural Medicine and Immune Engineering of Henan Province , Henan University , Kaifeng , China.
authors.forename: Y
authors.initials: Y
authors.lastname: Gan
authors.affiliation: a Key Laboratory of Natural Medicine and Immune Engineering of Henan Province , Henan University , Kaifeng , China.
authors.forename: Y
authors.initials: Y
authors.lastname: Zhang
authors.affiliation: b Zhengjiang Fangyuan Test Group Co., Ltd , Zhejiang , China.
authors.forename: X
authors.initials: X
authors.lastname: Ruan
authors.affiliation: a Key Laboratory of Natural Medicine and Immune Engineering of Henan Province , Henan University , Kaifeng , China.
authors.forename: Y
authors.initials: Y
authors.lastname: Wang
authors.affiliation: a Key Laboratory of Natural Medicine and Immune Engineering of Henan Province , Henan University , Kaifeng , China.|c Pharmaceutical College of Henan University , Kaifeng , China.
authors.forename: L
authors.initials: L
authors.lastname: Yang
authors.affiliation: a Key Laboratory of Natural Medicine and Immune Engineering of Henan Province , Henan University , Kaifeng , China.
authors.forename: J
authors.initials: J
authors.lastname: Shi
mesh_terms: D004785:Environmental Pollutants / Q000737:chemistry*; D016014:Linear Models; D015999:Multivariate Analysis; D000442:Octanols / Q000737:chemistry*; D011078:Polychlorinated Biphenyls / Q000737:chemistry*; D021281:Quantitative Structure-Activity Relationship; D014867:Water / Q000737:chemistry*
chemical_list: D004785:Environmental Pollutants; D000442:Octanols; D014867:Water; D011078:Polychlorinated Biphenyls
keywords: Quantitative structure–property relationship; hologram quantitative structure–activity relationship; octanol–water partition coefficient; organic carbon–water partition coefficient; polychlorinated biphenyls