应用一种反映分子局部微环境描述子——原子电性相互作用矢量(vector of atomic electronegative interaction,AEIV)和原子杂化状态指数(atomic hybridation state index,AHSI)对喹啉类化合物的13种分子中的129个^(13)C-NMR谱建模模拟,...应用一种反映分子局部微环境描述子——原子电性相互作用矢量(vector of atomic electronegative interaction,AEIV)和原子杂化状态指数(atomic hybridation state index,AHSI)对喹啉类化合物的13种分子中的129个^(13)C-NMR谱建模模拟,应用多元线性回归方法得到定量结构波谱关系模型的复相关系数(R_(MM1))为0.988,标准偏差(SD_(MM1))为5.317.采用留一法交互检验结果R_(CV1)为0.987,SD_(CV1)为5.630.随机抽出两部分分子进行检验,得到的相关系数R_(MM2)为0.993,R_(MM3)为0.987.结果表明,使用AEIV和AHSI所建模型具有相当的预测能力和稳定性.展开更多
构建了基于分子三维结构计算的原子电负性距离矢量(atomic electronegative space distance vector,AESDV),用以描述各芳香醚类化合物分子中不同等价碳原子的化学微环境,并结合原子自身杂化状态指数(AHSI),建立了^(13)C核磁共振定量结...构建了基于分子三维结构计算的原子电负性距离矢量(atomic electronegative space distance vector,AESDV),用以描述各芳香醚类化合物分子中不同等价碳原子的化学微环境,并结合原子自身杂化状态指数(AHSI),建立了^(13)C核磁共振定量结构波谱关系的多元线性回归模型,复相关系数(R)为0.964,标准误差(SD)为8.673.经留一法交互检验的复相关系数(R_(CV))为0.948,标准误差(SD_(CV))为10.362.随机抽出样本进行外部检验,得到测试集的复相关系数(R_(test1)及R_(test2))分别为0.979和0.939,标准误差(SD_(test1)及SD_(test2))分别为6.400和10.162.研究结果表明,使用该方法所建模型具有良好的预测能力和稳定性.展开更多
用原子电性距离矢量(atom ic electronegativity d istance vector,AEDV)和原子杂化状态指数(atom ic hybrid i-zation state index,AHSI)对13个雄甾烯酮化合物中247个碳原子进行了结构表征,并与其核磁共振碳谱(13CNMR)建立了多元线性...用原子电性距离矢量(atom ic electronegativity d istance vector,AEDV)和原子杂化状态指数(atom ic hybrid i-zation state index,AHSI)对13个雄甾烯酮化合物中247个碳原子进行了结构表征,并与其核磁共振碳谱(13CNMR)建立了多元线性定量构谱相关(QSSR)模型;运用逐步回归结合统计检测,对模型变量进行了筛选,建模计算值、留一法(leave-one-out,LOO)交互校验(cross-validation,CV)预测值和留分法(leave-molecu le-out,LMO)交互校验预测值的复相关系数(R)分别为0.989 6,0.989 1和0.989 4。结果表明:AEDV,AHSI与13CNMR谱化学位移显著相关。展开更多
Atomic electronegativity interaction vector (AEIV) and atomic hybridization state index (AHSI) were used for establishing the quantitative structure-spectroscopy relationship(QSSR) model of 13C NMR chemical shifts of ...Atomic electronegativity interaction vector (AEIV) and atomic hybridization state index (AHSI) were used for establishing the quantitative structure-spectroscopy relationship(QSSR) model of 13C NMR chemical shifts of isodon diterpenoid compounds.Multiple linear regression (MLR) and computational neural network (CNN) were used to create the models,and the estimation stability and generalization ability of the models were strictly analyzed by both internal and external validations.The established MLR and CNN models were correlated with experimental values and the correlation coefficients of model estimation,leave-one-out (LOO)cross-validation (CV),and predicted values of external samples were Rcum=0.9724,RCV=0.9723,Qext=0.9738 (MLR);Rcum=0.9957,Qext=0.9956 (CNN),respectively.The results indicated that CNN gave significantly better prediction of 13C NMR chemical shifts for isodon diterpenoids than MLR.Satisfactory results showed that AEIV and AHSI were obviously good for modeling 13C NMR chemical shifts of isodon diterpenoid compounds.展开更多
文摘应用一种反映分子局部微环境描述子——原子电性相互作用矢量(vector of atomic electronegative interaction,AEIV)和原子杂化状态指数(atomic hybridation state index,AHSI)对喹啉类化合物的13种分子中的129个^(13)C-NMR谱建模模拟,应用多元线性回归方法得到定量结构波谱关系模型的复相关系数(R_(MM1))为0.988,标准偏差(SD_(MM1))为5.317.采用留一法交互检验结果R_(CV1)为0.987,SD_(CV1)为5.630.随机抽出两部分分子进行检验,得到的相关系数R_(MM2)为0.993,R_(MM3)为0.987.结果表明,使用AEIV和AHSI所建模型具有相当的预测能力和稳定性.
基金Youth Foundation of Education Bureau,Sichuan Province(13ZB0003)Natural Science Foundation of Education Bureau,Sichuan Province(15ZB0272)
文摘构建了基于分子三维结构计算的原子电负性距离矢量(atomic electronegative space distance vector,AESDV),用以描述各芳香醚类化合物分子中不同等价碳原子的化学微环境,并结合原子自身杂化状态指数(AHSI),建立了^(13)C核磁共振定量结构波谱关系的多元线性回归模型,复相关系数(R)为0.964,标准误差(SD)为8.673.经留一法交互检验的复相关系数(R_(CV))为0.948,标准误差(SD_(CV))为10.362.随机抽出样本进行外部检验,得到测试集的复相关系数(R_(test1)及R_(test2))分别为0.979和0.939,标准误差(SD_(test1)及SD_(test2))分别为6.400和10.162.研究结果表明,使用该方法所建模型具有良好的预测能力和稳定性.
文摘用原子电性距离矢量(atom ic electronegativity d istance vector,AEDV)和原子杂化状态指数(atom ic hybrid i-zation state index,AHSI)对13个雄甾烯酮化合物中247个碳原子进行了结构表征,并与其核磁共振碳谱(13CNMR)建立了多元线性定量构谱相关(QSSR)模型;运用逐步回归结合统计检测,对模型变量进行了筛选,建模计算值、留一法(leave-one-out,LOO)交互校验(cross-validation,CV)预测值和留分法(leave-molecu le-out,LMO)交互校验预测值的复相关系数(R)分别为0.989 6,0.989 1和0.989 4。结果表明:AEDV,AHSI与13CNMR谱化学位移显著相关。
文摘Atomic electronegativity interaction vector (AEIV) and atomic hybridization state index (AHSI) were used for establishing the quantitative structure-spectroscopy relationship(QSSR) model of 13C NMR chemical shifts of isodon diterpenoid compounds.Multiple linear regression (MLR) and computational neural network (CNN) were used to create the models,and the estimation stability and generalization ability of the models were strictly analyzed by both internal and external validations.The established MLR and CNN models were correlated with experimental values and the correlation coefficients of model estimation,leave-one-out (LOO)cross-validation (CV),and predicted values of external samples were Rcum=0.9724,RCV=0.9723,Qext=0.9738 (MLR);Rcum=0.9957,Qext=0.9956 (CNN),respectively.The results indicated that CNN gave significantly better prediction of 13C NMR chemical shifts for isodon diterpenoids than MLR.Satisfactory results showed that AEIV and AHSI were obviously good for modeling 13C NMR chemical shifts of isodon diterpenoid compounds.
