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dc.contributor.authorZhou, Yaoqi
dc.contributor.authorDuan, Yong
dc.contributor.authorYang, Yuedong
dc.contributor.authorFaraggi, Eshel
dc.contributor.authorLei, Hongxing
dc.date.accessioned2017-08-25T12:32:18Z
dc.date.available2017-08-25T12:32:18Z
dc.date.issued2011
dc.date.modified2014-03-30T22:07:00Z
dc.identifier.issn1432-881X
dc.identifier.doi10.1007/s00214-010-0799-2
dc.identifier.urihttp://hdl.handle.net/10072/57419
dc.description.abstractPredicting the structure of a protein from its amino acid sequence is a long-standing unsolved problem in computational biology. Its solution would be of both fundamental and practical importance as the gap between the number of known sequences and the number of experimentally solved structures widens rapidly. Currently, the most successful approaches are based on fragment/ template reassembly. Lacking progress in template-free structure prediction calls for novel ideas and approaches. This article reviews trends in the development of physical and specific knowledge-based energy functions as well as sampling techniques for fragment-free structure prediction. Recent physical- and knowledge-based studies demonstrated that it is possible to sample and predict highly accurate protein structures without borrowing native fragments from known protein structures. These emerging approaches with fully flexible sampling have the potential to move the field forward.
dc.description.peerreviewedYes
dc.description.publicationstatusYes
dc.format.extent348060 bytes
dc.format.mimetypeapplication/pdf
dc.languageEnglish
dc.publisherSpringer
dc.publisher.placeGermany
dc.relation.ispartofstudentpublicationN
dc.relation.ispartofpagefrom3
dc.relation.ispartofpageto16
dc.relation.ispartofissue1
dc.relation.ispartofjournalTheoretical Chemistry Accounts
dc.relation.ispartofvolume128
dc.rights.retentionY
dc.subject.fieldofresearchBioinformatics
dc.subject.fieldofresearchTheoretical and Computational Chemistry
dc.subject.fieldofresearchcode060102
dc.subject.fieldofresearchcode0307
dc.titleTrends in template/fragment-free protein structure prediction
dc.typeJournal article
dc.type.descriptionC1 - Articles
dc.type.codeC - Journal Articles
gro.rights.copyright© The Author(s) 2011. This is a Springer Open Choice license agreement which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
gro.date.issued2011
gro.hasfulltextFull Text
gro.griffith.authorZhou, Yaoqi
gro.griffith.authorYang, Yuedong


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