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Identification of compound-protein interactions through the analysis of gene ontology, KEGG enrichment for proteins and molecular fragments of compounds

文献类型：期刊论文

作者Chen, Lei2; Zhang, Yu-Hang1; Zheng, Mingyue3; Huang, Tao1; Cai, Yu-Dong4
刊名MOLECULAR GENETICS AND GENOMICS
出版日期2016-12
卷号291期号:6页码:2065-2079
关键词Compound-protein interaction Gene ontology enrichment KEGG enrichment Minimum redundancy maximum relevance Incremental feature selection
ISSN号1617-4615
DOI10.1007/s00438-016-1240-x
文献子类Article
英文摘要Compound-protein interactions play important roles in every cell via the recognition and regulation of specific functional proteins. The correct identification of compound-protein interactions can lead to a good comprehension of this complicated system and provide useful input for the investigation of various attributes of compounds and proteins. In this study, we attempted to understand this system by extracting properties from both proteins and compounds, in which proteins were represented by gene ontology and KEGG pathway enrichment scores and compounds were represented by molecular fragments. Advanced feature selection methods, including minimum redundancy maximum relevance, incremental feature selection, and the basic machine learning algorithm random forest, were used to analyze these properties and extract core factors for the determination of actual compound-protein interactions. Compound-protein interactions reported in The Binding Databases were used as positive samples. To improve the reliability of the results, the analytic procedure was executed five times using different negative samples. Simultaneously, five optimal prediction methods based on a random forest and yielding maximum MCCs of approximately 77.55 % were constructed and may be useful tools for the prediction of compound-protein interactions. This work provides new clues to understanding the system of compound-protein interactions by analyzing extracted core features. Our results indicate that compound-protein interactions are related to biological processes involving immune, developmental and hormone-associated pathways.
WOS关键词AMINO-ACID-COMPOSITION ; DISORDER ARGININOSUCCINIC ACIDURIA ; SUPPORT VECTOR MACHINE ; FEATURE-SELECTION ; RANDOM FORESTS ; INTERACTION PREDICTION ; INTERACTION NETWORKS ; MINIMUM REDUNDANCY ; MAXIMUM RELEVANCE ; DNA METHYLATION
资助项目National Natural Science Foundation of China[31371335] ; National Natural Science Foundation of China[61303099] ; Shanghai Sailing Program[00000000] ; Youth Innovation Promotion Association of Chinese Academy of Sciences (CAS)[2016245]
WOS研究方向Biochemistry & Molecular Biology ; Genetics & Heredity
语种英语
WOS记录号WOS:000387134600005
出版者SPRINGER HEIDELBERG
源URL[http://119.78.100.183/handle/2S10ELR8/275790]  
专题药物发现与设计中心
通讯作者Chen, Lei; Cai, Yu-Dong
作者单位1.Chinese Acad Sci, Shanghai Inst Biol Sci, Inst Hlth Sci, Shanghai 200031, Peoples R China;
2.Shanghai Maritime Univ, Coll Informat Engn, Shanghai 201306, Peoples R China;
3.Shanghai Inst Mat Med, Drug Discovery & Design Ctr, Shanghai 201203, Peoples R China;
4.Shanghai Univ, Sch Life Sci, Shanghai 200444, Peoples R China
推荐引用方式
GB/T 7714		 Chen, Lei,Zhang, Yu-Hang,Zheng, Mingyue,et al. Identification of compound-protein interactions through the analysis of gene ontology, KEGG enrichment for proteins and molecular fragments of compounds[J]. MOLECULAR GENETICS AND GENOMICS,2016,291(6):2065-2079.
APA Chen, Lei,Zhang, Yu-Hang,Zheng, Mingyue,Huang, Tao,&Cai, Yu-Dong.(2016).Identification of compound-protein interactions through the analysis of gene ontology, KEGG enrichment for proteins and molecular fragments of compounds.MOLECULAR GENETICS AND GENOMICS,291(6),2065-2079.
MLA Chen, Lei,et al."Identification of compound-protein interactions through the analysis of gene ontology, KEGG enrichment for proteins and molecular fragments of compounds".MOLECULAR GENETICS AND GENOMICS 291.6(2016):2065-2079.

入库方式： OAI收割

来源：上海药物研究所

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