Title :
QSAR Model of Hydroxy- or Methoxy-substituted Benzaldoximes and Benzaldehyde-o-alkyloximes as Tyrosinase Inhibitors
Author :
Luo, Huajun ; Wang, Junzhi ; Zou, Kun
Author_Institution :
Hubei Key Lab. of Natural Products R&D, China Three Gorges Univ., Yichang, China
Abstract :
Quantitative structure-activity relationship (QSAR) study on the tyrosinase inhibition activities of hydroxy- or methoxy-substituted benzaldoximes and benzaldehyde-O-alkyloximes was performed using support vector machines (SVM) method. The predictive power of the models was verified with the leave one out cross validation test and independent test methods. The cross validation squared correlation coefficient value for optimal SVM model was 0.6880. Compared with stepwise multiple linear regression and back propagation artificial neural network models, the SVM model was the most powerful with a square of predictive correlation coefficient of 0.6117 for the test set.
Keywords :
QSAR; bioinformatics; inhibitors; organic compounds; support vector machines; QSAR model; benzaldehyde-O-alkyloximes; correlation coefficient value; cross validation test; hydroxy-substituted benzaldoximes; independent test methods; methoxy-substituted benzaldoximes; quantitative structure-activity relationship; support vector machines; tyrosinase inhibitors; Compounds; Correlation; Kernel; Mathematical model; Predictive models; Support vector machines; Training; QSAR; benzaldehyde-O-ethyloximes; benzaldoximes; model; support vector machines; tyrosinase inhibitor;
Conference_Titel :
Information Engineering (ICIE), 2010 WASE International Conference on
Conference_Location :
Beidaihe, Hebei
Print_ISBN :
978-1-4244-7506-3
Electronic_ISBN :
978-1-4244-7507-0
DOI :
10.1109/ICIE.2010.27