KMS Of Academy of mathematics and systems sciences, CAS
| Structure alignment-based classification of RNA-binding pockets reveals regional RNA recognition motifs on protein surfaces | |
Liu, Zhi-Ping1; Liu, Shutang1; Chen, Ruitang2; Huang, Xiaopeng3,4,5; Wu, Ling-Yun3,4,5
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| 2017-01-11 | |
| Source Publication | BMC BIOINFORMATICS
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| ISSN | 1471-2105 |
| Volume | 18Pages:13 |
| Abstract | Background: Many critical biological processes are strongly related to protein-RNA interactions. Revealing the protein structure motifs for RNA-binding will provide valuable information for deciphering protein-RNA recognition mechanisms and benefit complementary structural design in bioengineering. RNA-binding events often take place at pockets on protein surfaces. The structural classification of local binding pockets determines the major patterns of RNA recognition. Results: In this work, we provide a novel framework for systematically identifying the structure motifs of protein-RNA binding sites in the form of pockets on regional protein surfaces via a structure alignment-based method. We first construct a similarity network of RNA-binding pockets based on a non-sequential-order structure alignment method for local structure alignment. By using network community decomposition, the RNA-binding pockets on protein surfaces are clustered into groups with structural similarity. With a multiple structure alignment strategy, the consensus RNA-binding pockets in each group are identified. The crucial recognition patterns, as well as the protein-RNA binding motifs, are then identified and analyzed. Conclusions: Large-scale RNA-binding pockets on protein surfaces are grouped by measuring their structural similarities. This similarity network-based framework provides a convenient method for modeling the structural relationships of functional pockets. The local structural patterns identified serve as structure motifs for the recognition with RNA on protein surfaces. |
| Keyword | RNA-binding pocket Local structure classification Structural alignment Network clustering Structure motif |
| DOI | 10.1186/s12859-016-1410-1 |
| Language | 英语 |
| Funding Project | Strategic Priority Research Program of the Chinese Academy of Sciences[XDB13040600] ; National Center for Mathematics and Interdisciplinary Sciences, Chinese Academy of Sciences ; National Natural Science Foundation of China (NSFC)[61533011] ; National Natural Science Foundation of China (NSFC)[61572287] ; National Natural Science Foundation of China (NSFC)[31100949] ; National Natural Science Foundation of China (NSFC)[11131009] ; National Natural Science Foundation of China (NSFC)[11631014] ; National Natural Science Foundation of China (NSFC)[91330114] ; Shandong Provincial Natural Science Foundation of China[ZR2015FQ001] ; Fundamental Research Funds of Shandong University[2014 TB006] ; Fundamental Research Funds of Shandong University[2015QY001] ; Fundamental Research Funds of Shandong University[2016JC007] ; Scientific Research Foundation for Returned Overseas Chinese Scholars, Ministry of Education of China |
| WOS Research Area | Biochemistry & Molecular Biology ; Biotechnology & Applied Microbiology ; Mathematical & Computational Biology |
| WOS Subject | Biochemical Research Methods ; Biotechnology & Applied Microbiology ; Mathematical & Computational Biology |
| WOS ID | WOS:000392170800003 |
| Publisher | BIOMED CENTRAL LTD |
| Citation statistics | |
| Document Type | 期刊论文 |
| Identifier | http://ir.amss.ac.cn/handle/2S8OKBNM/363 |
| Collection | 应用数学研究所 |
| Corresponding Author | Wu, Ling-Yun |
| Affiliation | 1.Shandong Univ, Sch Control Sci & Engn, Dept Biomed Engn, Jinan 250061, Shandong, Peoples R China 2.Stanford Univ, Dept Comp Sci, Stanford, CA 94305 USA 3.Chinese Acad Sci, Acad Math & Syst Sci, Inst Appl Math, Beijing 100190, Peoples R China 4.Chinese Acad Sci, Natl Ctr Math & Interdisciplinary Sci, Beijing 100190, Peoples R China 5.Univ Chinese Acad Sci, Beijing 100049, Peoples R China |
| Recommended Citation GB/T 7714 | Liu, Zhi-Ping,Liu, Shutang,Chen, Ruitang,et al. Structure alignment-based classification of RNA-binding pockets reveals regional RNA recognition motifs on protein surfaces[J]. BMC BIOINFORMATICS,2017,18:13. |
| APA | Liu, Zhi-Ping,Liu, Shutang,Chen, Ruitang,Huang, Xiaopeng,&Wu, Ling-Yun.(2017).Structure alignment-based classification of RNA-binding pockets reveals regional RNA recognition motifs on protein surfaces.BMC BIOINFORMATICS,18,13. |
| MLA | Liu, Zhi-Ping,et al."Structure alignment-based classification of RNA-binding pockets reveals regional RNA recognition motifs on protein surfaces".BMC BIOINFORMATICS 18(2017):13. |
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