title: In silico model for predicting soil organic carbon normalized sorption coefficient (K(OC)) of organic chemicals.
abstract: As a kind of in silico method, the methodology of quantitative structure-activity relationship (QSAR) has been shown to be an efficient way to predict soil organic carbon normalized sorption coefficients (KOC) values. In the present study, a total of 824 logKOC values were used to develop and validate a QSAR model for predicting KOC values. The model statistics parameters, adjusted determination coefficient (R(2)adj) of 0.854, the root mean square error (RMSE) of 0.472, the leave-one-out cross-validation squared correlation coefficient (Q(2)LOO) of 0.850, the external validation coefficient Q(2)ext of 0.761 and the RMSEext of 0.558 were obtained, which indicate satisfactory goodness of fit, robustness and predictive ability. The squared Moriguchi octanol-water partition coefficient (MLOGP2) explained 66.5% of the logKOC variance. The applicability domain of the current model has been extended to emerging pollutants like polybrominated diphenyl ethers, perfluorochemicals and heterocyclic toxins. The developed model can be used to predict the compounds with various functional groups including C=C, -C≡C-, -OH, -O-, -CHO, C=O, -C=O(O), -COOH, -C6H5, -NO2, -NH2, -NH-, N-, -N-N-, -NH-C(O)-NH-, -O-C(O)-NH2, -C(O)-NH2, -X(F, Cl, Br, I), -S-, -SH, -S(O)2-, -OS(O)2-, -NH-S(O)2-, (SR)2PH(OR)2 and Si.
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
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: 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: Xianhai
authors.initials: X
authors.lastname: Yang
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: Felichesmi
authors.initials: F
authors.lastname: Lyakurwa
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: lixuehua@dlut.edu.cn.
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: Xianliang
authors.initials: X
authors.lastname: Qiao
mesh_terms: D000327:Adsorption; D002244:Carbon / Q000032:analysis*; D003198:Computer Simulation; D004784:Environmental Monitoring / Q000379:methods*; D021281:Quantitative Structure-Activity Relationship; D012987:Soil / Q000737:chemistry*; D012989:Soil Pollutants / Q000032:analysis*
chemical_list: D012987:Soil; D012989:Soil Pollutants; D002244:Carbon
keywords: Multiple linear regression (MLR); Predictive ability; Quantitative structure–activity relationship (QSAR); Soil organic carbon normalized sorption coefficient (K(OC))