FALCON@home: a high-throughput protein structure prediction server based on remote homologue recognition | |
Wang, Chao1,5; Zhang, Haicang1,5; Zheng, Wei-Mou3; Xu, Dong2,4; Zhu, Jianwei1; Wang, Bing1; Ning, Kang7; Sun, Shiwei1; Li, Shuai Cheng6; Bu, Dongbo1 | |
刊名 | BIOINFORMATICS
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2016-02-01 | |
卷号 | 32期号:3页码:462-464 |
ISSN号 | 1367-4803 |
DOI | 10.1093/bioinformatics/btv581 |
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. |
资助项目 | National Basic Research Program of China[2012CB316502] ; National Nature Science Foundation of China[11175224] ; National Nature Science Foundation of China[11121403] ; National Nature Science Foundation of China[31270834] ; National Nature Science Foundation of China[61272318] ; National Nature Science Foundation of China[30870572] ; National Nature Science Foundation of China[61303161] ; National Institutes of Health of USA[R21/R33-GM078601] ; National Institutes of Health of USA[R01-GM100701] ; European Commission[306819] |
WOS研究方向 | Biochemistry & Molecular Biology ; Biotechnology & Applied Microbiology ; Computer Science ; Mathematical & Computational Biology ; Mathematics |
语种 | 英语 |
出版者 | OXFORD UNIV PRESS |
WOS记录号 | WOS:000370203000023 |
内容类型 | 期刊论文 |
源URL | [http://119.78.100.204/handle/2XEOYT63/8718] ![]() |
专题 | 中国科学院计算技术研究所期刊论文_英文 |
通讯作者 | Li, Shuai Cheng; Bu, Dongbo |
作者单位 | 1.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing, Peoples R China 2.Univ Missouri, Christopher S Bond Life Sci Ctr, Columbia, MO 65211 USA 3.Chinese Acad Sci, Inst Theoret Phys, Beijing 100080, Peoples R China 4.Univ Missouri, Dept Comp Sci, Columbia, MO 65211 USA 5.Univ Chinese Acad Sci, Beijing, Peoples R China 6.City Univ Hong Kong, Dept Comp Sci, Kowloon, Hong Kong, Peoples R China 7.Huazhong Univ Sci & Technol, Coll Life Sci, Wuhan 430074, Peoples R China |
推荐引用方式 GB/T 7714 | Wang, Chao,Zhang, Haicang,Zheng, Wei-Mou,et al. FALCON@home: a high-throughput protein structure prediction server based on remote homologue recognition[J]. BIOINFORMATICS,2016,32(3):462-464. |
APA | Wang, Chao.,Zhang, Haicang.,Zheng, Wei-Mou.,Xu, Dong.,Zhu, Jianwei.,...&Bu, Dongbo.(2016).FALCON@home: a high-throughput protein structure prediction server based on remote homologue recognition.BIOINFORMATICS,32(3),462-464. |
MLA | Wang, Chao,et al."FALCON@home: a high-throughput protein structure prediction server based on remote homologue recognition".BIOINFORMATICS 32.3(2016):462-464. |
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