title: Comparison of prediction methods for octanol-air partition coefficients of diverse organic compounds.
abstract: The octanol-air partition coefficient (KOA) is needed for assessing multimedia transport and bioaccumulability of organic chemicals in the environment. As experimental determination of KOA for various chemicals is costly and laborious, development of KOA estimation methods is necessary. We investigated three methods for KOA prediction, conventional quantitative structure-activity relationship (QSAR) models based on molecular structural descriptors, group contribution models based on atom-centered fragments, and a novel model that predicts KOA via solvation free energy from air to octanol phase (ΔGO(0)), with a collection of 939 experimental KOA values for 379 compounds at different temperatures (263.15-323.15 K) as validation or training sets. The developed models were evaluated with the OECD guidelines on QSAR models validation and applicability domain (AD) description. Results showed that although the ΔGO(0) model is theoretically sound and has a broad AD, the prediction accuracy of the model is the poorest. The QSAR models perform better than the group contribution models, and have similar predictability and accuracy with the conventional method that estimates KOA from the octanol-water partition coefficient and Henry's law constant. One QSAR model, which can predict KOA at different temperatures, was recommended for application as to assess the long-range transport potential of chemicals.
authors.affiliation: Key Laboratory of Industrial Ecology and Environmental Engineering (MOE), School of Environmental Science and Technology, Dalian University of Technology, Linggong Road 2, Dalian 116024, China.
authors.forename: Zhiqiang
authors.initials: Z
authors.lastname: Fu
authors.affiliation: Key Laboratory of Industrial Ecology and Environmental Engineering (MOE), School of Environmental Science and Technology, Dalian University of Technology, Linggong Road 2, Dalian 116024, China. Electronic address: jwchen@dlut.edu.cn.
authors.forename: Jingwen
authors.initials: J
authors.lastname: Chen
authors.affiliation: Key Laboratory of Industrial Ecology and Environmental Engineering (MOE), School of Environmental Science and Technology, Dalian University of Technology, Linggong Road 2, Dalian 116024, China.
authors.forename: Xuehua
authors.initials: X
authors.lastname: Li
authors.affiliation: Key Laboratory of Industrial Ecology and Environmental Engineering (MOE), School of Environmental Science and Technology, Dalian University of Technology, Linggong Road 2, Dalian 116024, China.
authors.forename: Ya'nan
authors.initials: Y
authors.lastname: Wang
authors.affiliation: Key Laboratory of Industrial Ecology and Environmental Engineering (MOE), School of Environmental Science and Technology, Dalian University of Technology, Linggong Road 2, Dalian 116024, China.
authors.forename: Haiying
authors.initials: H
authors.lastname: Yu
mesh_terms: D000388:Air / Q000032:analysis*; D000393:Air Pollutants / Q000032:analysis* / Q000737:chemistry; D008962:Models, Theoretical; D000442:Octanols / Q000032:analysis* / Q000737:chemistry; D011237:Predictive Value of Tests; D021281:Quantitative Structure-Activity Relationship; D013696:Temperature; D014867:Water / Q000737:chemistry
chemical_list: D000393:Air Pollutants; D000442:Octanols; D014867:Water
keywords: Application domain; Group contribution model; Octanol-air partition coefficients; Prediction method; Quantitative structure–activity relationship; Solvation model