{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,28]],"date-time":"2026-01-28T22:45:35Z","timestamp":1769640335535,"version":"3.49.0"},"reference-count":7,"publisher":"Oxford University Press (OUP)","issue":"3","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016,2,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Summary: 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.<\/jats:p>\n               <jats:p>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.<\/jats:p>\n               <jats:p>We implemented FALCON@home using the Berkeley Open Infrastructure of Network Computing (BOINC) volunteer computing protocol. With computation power donated from over 20\u2009000 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@home-based 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.<\/jats:p>\n               <jats:p>Availability and implementation: FALCON@home is freely available at http:\/\/protein.ict.ac.cn\/FALCON\/.<\/jats:p>\n               <jats:p>Contact: \u00a0shuaicli@cityu.edu.hk, dbu@ict.ac.cn<\/jats:p>\n               <jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btv581","type":"journal-article","created":{"date-parts":[[2015,10,11]],"date-time":"2015-10-11T01:19:15Z","timestamp":1444526355000},"page":"462-464","source":"Crossref","is-referenced-by-count":33,"title":["FALCON@home: a high-throughput protein structure prediction server based on remote homologue recognition"],"prefix":"10.1093","volume":"32","author":[{"given":"Chao","family":"Wang","sequence":"first","affiliation":[{"name":"1 Key Lab of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China,"},{"name":"2 University of Chinese Academy of Sciences, Beijing, China,"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haicang","family":"Zhang","sequence":"additional","affiliation":[{"name":"1 Key Lab of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China,"},{"name":"2 University of Chinese Academy of Sciences, Beijing, China,"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wei-Mou","family":"Zheng","sequence":"additional","affiliation":[{"name":"3 Institute of Theoretical Physics, Chinese Academy of Sciences, Beijing, China,"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dong","family":"Xu","sequence":"additional","affiliation":[{"name":"4 Department of Computer Science and Christopher S. Bond Life Sciences Center, University of Missouri, MO 65211, USA,"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianwei","family":"Zhu","sequence":"additional","affiliation":[{"name":"1 Key Lab of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China,"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bing","family":"Wang","sequence":"additional","affiliation":[{"name":"1 Key Lab of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China,"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kang","family":"Ning","sequence":"additional","affiliation":[{"name":"5 College of Life Science, Huazhong University of Science and Technology, Wuhan, China and"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shiwei","family":"Sun","sequence":"additional","affiliation":[{"name":"1 Key Lab of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China,"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shuai Cheng","family":"Li","sequence":"additional","affiliation":[{"name":"6 Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dongbo","family":"Bu","sequence":"additional","affiliation":[{"name":"1 Key Lab of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China,"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2015,10,10]]},"reference":[{"key":"2023020110313239400_btv581-B1","doi-asserted-by":"crossref","first-page":"1925","DOI":"10.1110\/ps.036442.108","article-title":"Fragment-hmm: a new approach to protein structure prediction","volume":"17","author":"Li","year":"2008","journal-title":"Protein Sci."},{"key":"2023020110313239400_btv581-B2","doi-asserted-by":"crossref","first-page":"472","DOI":"10.1093\/bioinformatics\/btt709","article-title":"Combining evolutionary information extracted from frequency profiles with sequence-based kernels for protein remote homology detection","volume":"30","author":"Liu","year":"2014","journal-title":"Bioinformatics"},{"key":"2023020110313239400_btv581-B3","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1002\/prot.23175","article-title":"Raptorx: exploiting structure information for protein alignment by statistical inference","volume":"79","author":"Peng","year":"2011","journal-title":"Proteins Struct. 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