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ITP OpenIR  > 理论物理所2016年知识产出  > 期刊论文
题名: FALCON@home: a high-throughput protein structure prediction server based on remote homologue recognition
作者: Wang, C ;  Zhang, HC ;  Zheng, WM ;  Xu, D ;  Zhu, JW ;  Wang, B ;  Ning, K ;  Sun, SW ;  Li, SC ;  Bu, DB
刊名: BIOINFORMATICS
出版日期: 2016
卷号: 32, 期号:3, 页码:462-464
学科分类: Biochemistry & Molecular Biology; Biotechnology & Applied Microbiology; Computer Science; Mathematical & Computational Biology; Mathematics
DOI: http://dx.doi.org/10.1093/bioinformatics/btv581
通讯作者: Bu, DB (reprint author), Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing, Peoples R China. ;  Li, SC (reprint author), City Univ Hong Kong, Dept Comp Sci, Kowloon, Hong Kong, Peoples R China.
文章类型: Article
英文摘要: The protein structure prediction approaches can be categorized into template-based modeling (including homology modeling and threading) and free modeling. However, the existing threading tools perform poorly on remote homologous proteins. Thus, improving fold recognition for remote homologous proteins remains a challenge. Besides, the proteome-wide structure prediction poses another challenge of increasing prediction throughput. In this study, we presented FALCON@home as a protein structure prediction server focusing on remote homologue identification. The design of FALCON@home is based on the observation that a structural template, especially for remote homologous proteins, consists of conserved regions interweaved with highly variable regions. The highly variable regions lead to vague alignments in threading approaches. Thus, FALCON@home first extracts conserved regions from each template and then aligns a query protein with conserved regions only rather than the full-length template directly. This helps avoid the vague alignments rooted in highly variable regions, improving remote homologue identification. We implemented FALCON@home using the Berkeley Open Infrastructure of Network Computing (BOINC) volunteer computing protocol. With computation power donated from over 20 000 volunteer CPUs, FALCON@home shows a throughput as high as processing of over 1000 proteins per day. In the Critical Assessment of protein Structure Prediction (CASP11), the FALCON@homebased prediction was ranked the 12th in the template-based modeling category. As an application, the structures of 880 mouse mitochondria proteins were predicted, which revealed the significant correlation between protein half-lives and protein structural factors.
类目[WOS]: Biochemical Research Methods ;  Biotechnology & Applied Microbiology ;  Computer Science, Interdisciplinary Applications ;  Mathematical & Computational Biology ;  Statistics & Probability
关键词[WOS]: INFORMATION
收录类别: SCI
项目资助者: National Basic Research Program of China [2012CB316502] ;  National Nature Science Foundation of China [11175224, 11121403, 31270834, 61272318, 30870572, 61303161] ;  National Institutes of Health of USA [R21/R33-GM078601, R01-GM100701] ;  European Commission [306819]
语种: 英语
Citation statistics: 
内容类型: 期刊论文
URI标识: http://ir.itp.ac.cn/handle/311006/21788
Appears in Collections:理论物理所2016年知识产出_期刊论文

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Recommended Citation:
Wang, C,Zhang, HC,Zheng, WM,et al. FALCON@home: a high-throughput protein structure prediction server based on remote homologue recognition[J]. BIOINFORMATICS,2016,32(3):462-464.
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