In order to investigate the relationship between structure and the activity of cinnamyl-isobutylamuine,the ab initio calculation was undertaken and the information of their electronic sturctures was obtained.It is fou...In order to investigate the relationship between structure and the activity of cinnamyl-isobutylamuine,the ab initio calculation was undertaken and the information of their electronic sturctures was obtained.It is found that the anticonvulsant activities of these kinds of compounds have a linear relationship with energy and composition of LUMO and LUMO(+3).When the drug molecule interacts with the acceptor,there may be occurrence of electron transfer between the drug molecule and the acceptor to form the electron-transferred-complex.The active sites of the drug molecule are at the carbony and ethylene bond.展开更多
In this paper, the comparison of orthogonal descriptors and Leaps and Bounds regression analysis is performed. The results obtained by using orthogonal descriptors are better than that obtained by using Leaps and Boun...In this paper, the comparison of orthogonal descriptors and Leaps and Bounds regression analysis is performed. The results obtained by using orthogonal descriptors are better than that obtained by using Leaps and Bounds regression for the data set of nitrobenzenes used in this study. Leaps and Bounds regression can be used effectively for selection of variables in quantitative structure activity/property relationship(QSAR/QSPR) studies. Consequently, orthogonalisation of descriptors is also a good method for variable selection for studies on QSAR/QSPR.展开更多
The purpose of this study was to develop a quantitative structure–property relationship(QSPR) model based on the enhanced replacement method(ERM) and support vector machine(SVM) to predict the blood-to-brain barrier ...The purpose of this study was to develop a quantitative structure–property relationship(QSPR) model based on the enhanced replacement method(ERM) and support vector machine(SVM) to predict the blood-to-brain barrier partitioning behavior(log BB) of various drugs and organic compounds. Different molecular descriptors were calculated using a dragon package to represent the molecular structures of the compounds studied. The enhanced replacement method(ERM) was used to select the variables and construct the SVM model. The correlation coefficient, R^2, between experimental results and predicted log BB was 0.878 and 0.986, respectively. The results obtained demonstrated that, for all compounds, the log BB values estimated by SVM agreed with the experimental data, demonstrating that SVM is an effective method for model development, and can be used as a powerful chemometric tool in QSPR studies.展开更多
文摘In order to investigate the relationship between structure and the activity of cinnamyl-isobutylamuine,the ab initio calculation was undertaken and the information of their electronic sturctures was obtained.It is found that the anticonvulsant activities of these kinds of compounds have a linear relationship with energy and composition of LUMO and LUMO(+3).When the drug molecule interacts with the acceptor,there may be occurrence of electron transfer between the drug molecule and the acceptor to form the electron-transferred-complex.The active sites of the drug molecule are at the carbony and ethylene bond.
文摘In this paper, the comparison of orthogonal descriptors and Leaps and Bounds regression analysis is performed. The results obtained by using orthogonal descriptors are better than that obtained by using Leaps and Bounds regression for the data set of nitrobenzenes used in this study. Leaps and Bounds regression can be used effectively for selection of variables in quantitative structure activity/property relationship(QSAR/QSPR) studies. Consequently, orthogonalisation of descriptors is also a good method for variable selection for studies on QSAR/QSPR.
文摘The purpose of this study was to develop a quantitative structure–property relationship(QSPR) model based on the enhanced replacement method(ERM) and support vector machine(SVM) to predict the blood-to-brain barrier partitioning behavior(log BB) of various drugs and organic compounds. Different molecular descriptors were calculated using a dragon package to represent the molecular structures of the compounds studied. The enhanced replacement method(ERM) was used to select the variables and construct the SVM model. The correlation coefficient, R^2, between experimental results and predicted log BB was 0.878 and 0.986, respectively. The results obtained demonstrated that, for all compounds, the log BB values estimated by SVM agreed with the experimental data, demonstrating that SVM is an effective method for model development, and can be used as a powerful chemometric tool in QSPR studies.
