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Quantitative structure–activity relationship study on the inhibitors of fatty acid amide hydrolase
Author(s) -
Lu Peng,
Zhang Ruisheng,
Yuan Yongna,
Gong Zhiguo
Publication year - 2010
Publication title -
journal of chemometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.47
H-Index - 92
eISSN - 1099-128X
pISSN - 0886-9383
DOI - 10.1002/cem.1314
Subject(s) - fatty acid amide hydrolase , quantitative structure–activity relationship , support vector machine , chemistry , artificial intelligence , amide , fatty acid , computer science , hydrolase , pattern recognition (psychology) , stereochemistry , biochemistry , enzyme , receptor , cannabinoid receptor , agonist
A quantitative structure activity relationship (QSAR) analysis was performed on the $K_i $ values of a series of fatty acid amide hydrolase (FAAH) inhibitors. Six molecular descriptors selected by CODESSA software were used as inputs to perform heuristic method (HM) and support vector machine (SVM). The results obtained by SVM were compared with those obtained by the HM. The root mean square errors (RMSEs) for the training set given by HM and SVM were 0.555 and 0.404, respectively, which shows that the performance of the SVM model is better than that of the HM model. This paper provides a new and effective method for predicting the activity of FAAH inhibitors. Copyright © 2010 John Wiley & Sons, Ltd.