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多氯联苯定量结构-性质的关系 被引量:2

Study the relationships between molecular electronegativity-distance vector and partly physicochemical properties of polychlorinated biphenyls
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摘要 基于定量结构-性质相关(QSPR)研究多氯联苯化合物(PCBs)的性质具有重要意义。用分子负电性距离矢量(MEDV)表征209个PCBs的分子结构,同时用多元线性回归(MLR)技术和逐步回归结合留一法交叉检验筛选模型变量,建立多氯联苯类化合物的水溶性(LgS_w)、土壤吸附性(LgK_(oc))、色谱保留指数(RRI)、水溶液活度系数(LgY_w)、总分子表面积(TSA)与MEDV的QSPR模型,其线性相关系数(R)分别为0.9651,0.9692,0.9968,0.9111,0.9960。继用留一法和外部样本检验模型稳定性能,其相关系数(R_(CV),Q_(ext))分别为0.9611、0.9812;0.9572、0.9845;0.9941、0.9984;0.9980、0.9412;0.9953、0.9998。结果表明:所建QSPR模型均稳定性和预测能力良好。 Study on quantitative structure-property relationship(QSPR) of polychlorinated biphenyls(PCBs) would be helpful in researching for PCBs property.The molecular electronegativity-distance vector(MEDV) was used to describe the chemical structure of 209 polychlorinated biphenyls,with the help of multiple linear regression(MLR) technique and the stepwise multiple regression (SMR) method to filter variables,five QSPR models were established with high correlation coefficients,they are the relationship between MEDV and aqueous solubility(LgS_w),soil absorption(LgK_(oc)),gas-chromatographic retention indices(RRI),aqueous activity coefficient(LgY_w),total molecular surface area(TSA),respectively.And the linear correlation coefficients(R) are 0.965 1, 0.969 2,0.996 8,0.911 1,and 0.9960,respectively.In order totest the stability and predictability of the QSPR models,the cross validation with leave-one-out of procedure and the predictability for outer samples are carried out,the correlation coefficients(R_(CV) and Q_(ext)) are 0.961 1 and 0.981 2;0.957 2 and 0.984 5;0.997 0 and 0.998 4;0.998 0 and 0.941 2;0.995 3 and 0.999 8,respectively. The results show that the established QSPR models possess good stability and predictability.
机构地区 [ 陕西科技大学
出处 《计算机与应用化学》 CAS CSCD 北大核心 2010年第4期543-545,共3页 Computers and Applied Chemistry
基金 陕西省教育厅专项科研计划项目[08JK225] 陕西科技大学博士科研启动基金项目[BJ07-04]
关键词 多氯联苯 分子负电性距离矢量 定量结构-性质关系 polychlorinated biphenyl(PCBs) molecular electronegativity-distance vector(MEDV) quantitative structure-property relationship(QSPR)
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