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In silico site of metabolism prediction for human UGT-catalyzed reactions

文献类型：期刊论文

作者Peng, Jianlong1; Lu, Jing1; Shen, Qiancheng1; Zheng, Mingyue1; Luo, Xiaomin1; Zhu, Weiliang1; Jiang, Hualiang1,2; Chen, Kaixian1
刊名BIOINFORMATICS
出版日期2014-02-01
卷号30期号:3页码:398-405
ISSN号1367-4803
DOI10.1093/bioinformatics/btt681
文献子类Article
英文摘要Motivation: The human uridine diphosphate-glucuronosyltransferase enzyme family catalyzes the glucuronidation of the glycosyl group of a nucleotide sugar to an acceptor compound (substrate), which is the most common conjugation pathway that serves to protect the organism from the potential toxicity of xenobiotics. Moreover, it could affect the pharmacological profile of a drug. Therefore, it is important to identify the metabolically labile sites for glucuronidation. Results: In the present study, we developed four in silico models to predict sites of glucuronidation, for four major sites of metabolism functional groups, i.e. aliphatic hydroxyl, aromatic hydroxyl, carboxylic acid or amino nitrogen, respectively. According to the mechanism of glucuronidation, a series of 'local' and 'global' molecular descriptors characterizing the atomic reactivity, bonding strength and physicalchemical properties were calculated and selected with a genetic algorithm-based feature selection approach. The constructed support vector machine classification models show good prediction performance, with the balanced accuracy ranging from 0.88 to 0.96 on test set. For further validation, our models can successfully identify 84% of experimentally observed sites of metabolisms for an external test set containing 54 molecules.
WOS关键词URIDINE-DIPHOSPHATE-GLUCURONOSYLTRANSFERASE ; QUANTUM-CHEMICAL DESCRIPTORS ; SUPPORT VECTOR MACHINES ; UDP-GLUCURONOSYLTRANSFERASE ; SUBSTRATE SELECTIVITY ; DRUG GLUCURONIDATION ; PATTERN-RECOGNITION ; DESIGN ; CONJUGATION ; PARAMETERS
资助项目Hi-TECH Research and Development Program of China[2012AA020308] ; National ST Major Project[2012ZX09301-001-002] ; National Natural Science Foundation of China[21021063] ; National Natural Science Foundation of China[81001399] ; National Natural Science Foundation of China[81230076] ; National Natural Science Foundation of China[21210003]
WOS研究方向Biochemistry & Molecular Biology ; Biotechnology & Applied Microbiology ; Computer Science ; Mathematical & Computational Biology ; Mathematics
语种英语
WOS记录号WOS:000331271100014
出版者OXFORD UNIV PRESS
源URL[http://119.78.100.183/handle/2S10ELR8/277202]  
专题药物发现与设计中心
中科院受体结构与功能重点实验室
新药研究国家重点实验室
通讯作者Zheng, Mingyue
作者单位1.Chinese Acad Sci, Shanghai Inst Mat Med, Drug Discovery & Design Ctr, State Key Lab Drug Res, Shanghai 201203, Peoples R China;
2.E China Univ Sci & Technol, Sch Pharm, Shanghai 200237, Peoples R China
推荐引用方式
GB/T 7714		 Peng, Jianlong,Lu, Jing,Shen, Qiancheng,et al. In silico site of metabolism prediction for human UGT-catalyzed reactions[J]. BIOINFORMATICS,2014,30(3):398-405.
APA Peng, Jianlong.,Lu, Jing.,Shen, Qiancheng.,Zheng, Mingyue.,Luo, Xiaomin.,...&Chen, Kaixian.(2014).In silico site of metabolism prediction for human UGT-catalyzed reactions.BIOINFORMATICS,30(3),398-405.
MLA Peng, Jianlong,et al."In silico site of metabolism prediction for human UGT-catalyzed reactions".BIOINFORMATICS 30.3(2014):398-405.

入库方式： OAI收割

来源：上海药物研究所

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