Two novel topological electro-negativity indices based on distance matrix,named YC and WC indices,were proposed to be used for modeling properties of multiple bond organic compounds by equilibrium electro-negativity o...Two novel topological electro-negativity indices based on distance matrix,named YC and WC indices,were proposed to be used for modeling properties of multiple bond organic compounds by equilibrium electro-negativity of atom and relative bond length of molecule.A quantitative structural property relationship(QSPR) model for estimating flash point of 92 compounds was developed based on the newly introduced topological electro-negativity indices YC and WC and path number parameter P3.The model correlation coefficient and standard error for training set in multiple linear regression were 0.9923 and 5.28,respectively.The average absolute error of flash point was only 3.86 K between experimental and calculated values,and the relative error was 1.46%.Furthermore,the model was strictly tested by both internal and external validations.The predicted values were in good agreement with experimental values for leave-one-out(LOO),and the training set and validation set.The results show that this QSPR model is of good stability and powerful prediction ability.展开更多
A quantitative structure-spectrum relationship (QSSR) model was developed to simulate 13C nuclear magnetic resonance (NMR) spectra of carbinol carbon atoms for 55 alcohols. The proposed model,using multiple linear reg...A quantitative structure-spectrum relationship (QSSR) model was developed to simulate 13C nuclear magnetic resonance (NMR) spectra of carbinol carbon atoms for 55 alcohols. The proposed model,using multiple linear regression,contained four descriptors solely extracted from the molecular structure of compounds. The statistical results of the final model show that R2= 0.982 4 and S=0.869 8 (where R is the correlation coefficient and S is the standard deviation). To test its predictive ability,the model was further used to predict the 13C NMR spectra of the carbinol carbon atoms of other nine compounds which were not included in the developed model. The average relative errors are 0.94% and 1.70%,respectively,for the training set and the predictive set. The model is statistically significant and shows good stability for data variation as tested by the leave-one-out (LOO) cross-validation. The comparison with other approaches also reveals good performance of this method.展开更多
文摘Two novel topological electro-negativity indices based on distance matrix,named YC and WC indices,were proposed to be used for modeling properties of multiple bond organic compounds by equilibrium electro-negativity of atom and relative bond length of molecule.A quantitative structural property relationship(QSPR) model for estimating flash point of 92 compounds was developed based on the newly introduced topological electro-negativity indices YC and WC and path number parameter P3.The model correlation coefficient and standard error for training set in multiple linear regression were 0.9923 and 5.28,respectively.The average absolute error of flash point was only 3.86 K between experimental and calculated values,and the relative error was 1.46%.Furthermore,the model was strictly tested by both internal and external validations.The predicted values were in good agreement with experimental values for leave-one-out(LOO),and the training set and validation set.The results show that this QSPR model is of good stability and powerful prediction ability.
基金Projects(20775010, 21075011) supported by the National Natural Science Foundation of ChinaProject(2008AA05Z405) supported by the National High-tech Research and Development Program of China+2 种基金Project(09JJ3016) supported by the Natural Science Foundation of Hunan Province, ChinaProject(09C066) supported by the Scientific Research Fund of Hunan Provincial Education Department, ChinaProject(2010CL01) supported by the Foundation of Hunan Provincial Key Laboratory of Materials Protection for Electric Power and Transportation, China
文摘A quantitative structure-spectrum relationship (QSSR) model was developed to simulate 13C nuclear magnetic resonance (NMR) spectra of carbinol carbon atoms for 55 alcohols. The proposed model,using multiple linear regression,contained four descriptors solely extracted from the molecular structure of compounds. The statistical results of the final model show that R2= 0.982 4 and S=0.869 8 (where R is the correlation coefficient and S is the standard deviation). To test its predictive ability,the model was further used to predict the 13C NMR spectra of the carbinol carbon atoms of other nine compounds which were not included in the developed model. The average relative errors are 0.94% and 1.70%,respectively,for the training set and the predictive set. The model is statistically significant and shows good stability for data variation as tested by the leave-one-out (LOO) cross-validation. The comparison with other approaches also reveals good performance of this method.
