Classification of 5-HT1A receptor agonists and antagonists using GA-SVM method

doi:10.1038/aps.2011.112

CORC > 上海药物研究所 > 中国科学院上海药物研究所 > 药物发现与设计中心

	Classification of 5-HT1A receptor agonists and antagonists using GA-SVM method
	Zhu, Xue-lian; Cai, Hai-yan; Xu, Zhi-jian; Wang, Yong; Wang, He-yao; Zhang, Ao; Zhu, Wei-liang
刊名	ACTA PHARMACOLOGICA SINICA
	2011-11
卷号	32 期号:11 页码:1424-1430
关键词	5-HT1A receptor support vector machine genetic algorithm agonist antagonists
ISSN号	1671-4083
DOI	10.1038/aps.2011.112
文献子类	Article
英文摘要	Aim: To construct a reliable computational model for the classification of agonists and antagonists of 5-HT1A receptor. Methods: Support vector machine (SVM), a well-known machine learning method, was employed to build a prediction model, and genetic algorithm (GA) was used to select the most relevant descriptors and to optimize two important parameters, C and r of the SVM model. The overall dataset used in this study comprised 284 ligands of the 5-HT1A receptor with diverse structures reported in the literatures. Results: A SVM model was successfully developed that could be used to predict the probability of a ligand being an agonist or antagonist of the 5-HT1A receptor. The predictive accuracy for training and test sets was 0.942 and 0.865, respectively. For compounds with probability estimate higher than 0.7, the predictive accuracy of the model for training and test sets was 0.954 and 0.927, respectively. To further validate our model, the receiver operating characteristic (ROC) curve was plotted, and the Area-Under-the-ROC-Curve (AUC) value was calculated to be 0.883 for training set and 0.906 for test set. Conclusion: A reliable SVM model was successfully developed that could effectively distinguish agonists and antagonists among the ligands of the 5-HT1A receptor. To our knowledge, this is the first effort for the classification of 5-HT1A receptor agonists and antagonists based on a diverse dataset. This method may be used to classify the ligands of other members of the GPCR family.
资助项目	National Natural Science Foundation of China[20721003] ; MOST[2010DFB73280] ; Shanghai Committee of Science and Technology[09540703900] ; ACS[KSCX2-YW-R-208]
WOS关键词	VIVO PHARMACOLOGICAL EVALUATION ; SEROTONIN TRANSPORTER AFFINITY ; IN-VITRO ; DUAL 5-HT1A ; REUPTAKE INHIBITORS ; LIGANDS ; POTENT ; DERIVATIVES ; DISCOVERY ; ANALOGS
WOS研究方向	Chemistry ; Pharmacology & Pharmacy
语种	英语
CSCD记录号	CSCD:4364876
出版者	ACTA PHARMACOLOGICA SINICA
WOS记录号	WOS:000296739400017
内容类型	期刊论文
源URL	[http://119.78.100.183/handle/2S10ELR8/278358]
专题	药物发现与设计中心
通讯作者	Zhu, Wei-liang
作者单位	Chinese Acad Sci, Shanghai Inst Mat Med, Shanghai 201203, Peoples R China
推荐引用方式 GB/T 7714	Zhu, Xue-lian,Cai, Hai-yan,Xu, Zhi-jian,et al. Classification of 5-HT1A receptor agonists and antagonists using GA-SVM method[J]. ACTA PHARMACOLOGICA SINICA,2011,32(11):1424-1430.
APA	Zhu, Xue-lian.,Cai, Hai-yan.,Xu, Zhi-jian.,Wang, Yong.,Wang, He-yao.,...&Zhu, Wei-liang.(2011).Classification of 5-HT1A receptor agonists and antagonists using GA-SVM method.ACTA PHARMACOLOGICA SINICA,32(11),1424-1430.
MLA	Zhu, Xue-lian,et al."Classification of 5-HT1A receptor agonists and antagonists using GA-SVM method".ACTA PHARMACOLOGICA SINICA 32.11(2011):1424-1430.