کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4408652 1618852 2015 7 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
In silico model for predicting soil organic carbon normalized sorption coefficient (KOC) of organic chemicals
موضوعات مرتبط
علوم زیستی و بیوفناوری علوم محیط زیست شیمی زیست محیطی
پیش نمایش صفحه اول مقاله
In silico model for predicting soil organic carbon normalized sorption coefficient (KOC) of organic chemicals
چکیده انگلیسی
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 log KOC values were used to develop and validate a QSAR model for predicting KOC values. The model statistics parameters, adjusted determination coefficient (R2adj) of 0.854, the root mean square error (RMSE) of 0.472, the leave-one-out cross-validation squared correlation coefficient (Q2LOO) of 0.850, the external validation coefficient Q2ext 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 log KOC 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 CC, CC, OH, O, CHO, CO, CO(O), COOH, C6H5, NO2, NH2, NH, N, NN, NHC(O)NH, OC(O)NH2, C(O)NH2, X(F, Cl, Br, I), S, SH, S(O)2, OS(O)2, NHS(O)2, (SR)2PH(OR)2 and Si.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Chemosphere - Volume 119, January 2015, Pages 438-444
نویسندگان
, , , , , ,