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Prediction of the sorption of organic compounds into soil organic matter from molecular structure

机译:从分子结构预测有机化合物对土壤有机质的吸附

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摘要

A new model to estimate the soil-water partition coefficient of non-ionic organic compounds normalized to soil organic carbon, K-oc, from the two-dimensional molecular structure is presented. Literature data of log Koc for 571 organic chemicals were fitted to 29 parameters with a squared correlation coefficient r(2) of 0.852 and a standard error of 0.469 log units. The application domain includes the atom types C, H, N, O, P, S, F, Cl, and Br in various important compound classes. The multilinear model contains the variables molecular weight, bond connectivity, molecular E-state, an indicator for nonpolar and weakly polar compounds, and 24 fragment corrections representing polar groups. The prediction capability is evaluated through an initial two-step development using an 80%:20% split of the data into training and prediction, cross-validation, permutation, and application to three external data sets. The discussion includes separate analyses for subsets of H-bond donors and acceptors as well as for nonpolar and weakly polar compounds. Comparison with existing models including linear solvation energy relationships illustrates the superiority of the new model.
机译:提出了一种从二维分子结构估算归一化为土壤有机碳的非离子有机化合物的土壤水分配系数的新模型。将571种有机化学品的log Koc文献数据拟合到29个参数,相关系数r(2)的平方为0.852,标准误为0.469 log单位。应用领域包括各种重要化合物类别中的原子类型C,H,N,O,P,S,F,Cl和Br。多线性模型包含变量分子量,键连接性,分子E状态,非极性和弱极性化合物的指示剂以及代表极性基团的24个片段校正。通过将数据分为培训和预测,交叉验证,置换以及应用于三个外部数据集的80%:20%的初始两步开发来评估预测能力。讨论包括对氢键供体和受体的子集以及非极性和弱极性化合物的单独分析。与现有模型(包括线性溶剂化能量关系)的比较说明了新模型的优越性。

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