用量子化学MOPAC-AM1法计算21种多环芳烃(PAHs)的SEDs(steric and electronic descriptors)参数,然后用多元线性回归法建立预测多环芳烃的沸点(BP)和辛醇/水分配系数(logK_(ow))等的QSPR模型,预测BP的模型含3个变量[前线轨道能量差(E_(l...用量子化学MOPAC-AM1法计算21种多环芳烃(PAHs)的SEDs(steric and electronic descriptors)参数,然后用多元线性回归法建立预测多环芳烃的沸点(BP)和辛醇/水分配系数(logK_(ow))等的QSPR模型,预测BP的模型含3个变量[前线轨道能量差(E_(lumo)-E_(homo))、分子总电子能(EE)和分子总连接性(TCon)],预测logK_(ow)的模型含3个变量[偶极矩(D)、分子总能量(TE)和分子总连接性(TCon)]。所建2个模型的相关系数的平方(R^2)分别为0.997 6和0.9861,交叉验证系数(R_(LOO)~2)分别为0.9820和0.9575,说明模型均具有很好的预测能力和较强的稳健性,同时也证明SEDs参数适用于多环芳烃类化合物的QSPR研究。展开更多
New descriptors were constructed and structures of some oxygen-containing organic compounds were parameterized. The multiple linear regression（MLR） and partial least squares regression（PLS） methods were employed t...New descriptors were constructed and structures of some oxygen-containing organic compounds were parameterized. The multiple linear regression（MLR） and partial least squares regression（PLS） methods were employed to build two relationship models between the structures and octanol/water partition coefficients（LogP） of the compounds. The modeling correlation coefficients（R） were 0.976 and 0.922, and the ＂leave one out＂ cross validation correlation coefficients（R（CV）） were 0.973 and 0.909, respectively. The results showed that the structural descriptors could well characterize the molecular structures of the compounds; the stability and predictive power of the models were good.展开更多
文摘用量子化学MOPAC-AM1法计算21种多环芳烃(PAHs)的SEDs(steric and electronic descriptors)参数,然后用多元线性回归法建立预测多环芳烃的沸点(BP)和辛醇/水分配系数(logK_(ow))等的QSPR模型,预测BP的模型含3个变量[前线轨道能量差(E_(lumo)-E_(homo))、分子总电子能(EE)和分子总连接性(TCon)],预测logK_(ow)的模型含3个变量[偶极矩(D)、分子总能量(TE)和分子总连接性(TCon)]。所建2个模型的相关系数的平方(R^2)分别为0.997 6和0.9861,交叉验证系数(R_(LOO)~2)分别为0.9820和0.9575,说明模型均具有很好的预测能力和较强的稳健性,同时也证明SEDs参数适用于多环芳烃类化合物的QSPR研究。
基金supported by the Youth Foundation of Education Bureau,Sichuan Province(13ZB0003)
文摘New descriptors were constructed and structures of some oxygen-containing organic compounds were parameterized. The multiple linear regression（MLR） and partial least squares regression（PLS） methods were employed to build two relationship models between the structures and octanol/water partition coefficients（LogP） of the compounds. The modeling correlation coefficients（R） were 0.976 and 0.922, and the ＂leave one out＂ cross validation correlation coefficients（R（CV）） were 0.973 and 0.909, respectively. The results showed that the structural descriptors could well characterize the molecular structures of the compounds; the stability and predictive power of the models were good.
