The quantitative structure-activity relationship （QSAR） of 30 acylthiourea analogues was studied by using a three-dimensional holographic vector of atomic interaction field （3D-HoVAIF） to describe their chemical s...The quantitative structure-activity relationship （QSAR） of 30 acylthiourea analogues was studied by using a three-dimensional holographic vector of atomic interaction field （3D-HoVAIF） to describe their chemical structures. The descriptors obtained were screened by stepwise multiple regression （SMR） and a partial least-squares （PLS） regression model was built. The correlation coefficient r^2 of the established model and Leave-One-Out （LOO） Cross-Validation （CV） correlation coefficient q^2 are 0.624 and 0.409, respectively. The model has favorable stability and good prediction capability, and further QSAR analysis showed that hydrophobic interaction has the most important effect on the activity of acylthiourea analogue and 3D-HoVAIF was applicable to the molecular structural characterization and biologicalactivity prediction.展开更多
基金supported by the National High-tech Research Program (the "863" Program, No. 2006AA02Z312)Innovative Group Program for Graduates of Chongqing University, Science and Innovation Fund (No. 200711C1A0010260)
文摘The quantitative structure-activity relationship （QSAR） of 30 acylthiourea analogues was studied by using a three-dimensional holographic vector of atomic interaction field （3D-HoVAIF） to describe their chemical structures. The descriptors obtained were screened by stepwise multiple regression （SMR） and a partial least-squares （PLS） regression model was built. The correlation coefficient r^2 of the established model and Leave-One-Out （LOO） Cross-Validation （CV） correlation coefficient q^2 are 0.624 and 0.409, respectively. The model has favorable stability and good prediction capability, and further QSAR analysis showed that hydrophobic interaction has the most important effect on the activity of acylthiourea analogue and 3D-HoVAIF was applicable to the molecular structural characterization and biologicalactivity prediction.
