FALCON@home: a high-throughput protein structure prediction server based on remote homologue recognition
文献类型：期刊论文
| 作者 | Xu, D; Wang, C; Zhang, HC; Zheng, WM ; Wang, B; Ning, K; Sun, SW; Li, SC; Bu, DB; Bu, DB (reprint author), Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing, Peoples R China.
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| 刊名 | BIOINFORMATICS
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| 出版日期 | 2016 |
| 卷号 | 32期号:3页码:462-464 |
| DOI | http://dx.doi.org/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. |
| 学科主题 | Biochemistry & Molecular Biology ; Biotechnology & Applied Microbiology ; Computer Science ; Mathematical & Computational Biology ; Mathematics |
| 语种 | 英语 |
| 源URL | [http://ir.itp.ac.cn/handle/311006/21788]  |
| 专题 | 理论物理研究所_理论物理所1978-2010年知识产出 |
| 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. |
| 推荐引用方式 GB/T 7714 | Xu, D,Wang, C,Zhang, HC,et al. FALCON@home: a high-throughput protein structure prediction server based on remote homologue recognition[J]. BIOINFORMATICS,2016,32(3):462-464. |
| APA | Xu, D.,Wang, C.,Zhang, HC.,Zheng, WM.,Wang, B.,...&Zhu, JW.(2016).FALCON@home: a high-throughput protein structure prediction server based on remote homologue recognition.BIOINFORMATICS,32(3),462-464. |
| MLA | Xu, D,et al."FALCON@home: a high-throughput protein structure prediction server based on remote homologue recognition".BIOINFORMATICS 32.3(2016):462-464. |
入库方式： OAI收割
来源：理论物理研究所
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