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dc.contributor.authorToth-Petroczy, Agnes
dc.contributor.authorIngraham, John
dc.contributor.authorHopf, Thomas A.
dc.contributor.authorSander, Chris
dc.contributor.authorMarks, Debora S.
dc.contributor.authorPalmedo, Peter Franklin
dc.contributor.authorBerger Leighton, Bonnie
dc.date.accessioned2018-05-17T17:03:23Z
dc.date.available2018-05-17T17:03:23Z
dc.date.issued2016-09
dc.date.submitted2016-07
dc.identifier.issn0092-8674
dc.identifier.issn1097-4172
dc.identifier.urihttp://hdl.handle.net/1721.1/115426
dc.description.abstractProtein flexibility ranges from simple hinge movements to functional disorder. Around half of all human proteins contain apparently disordered regions with little 3D or functional information, and many of these proteins are associated with disease. Building on the evolutionary couplings approach previously successful in predicting 3D states of ordered proteins and RNA, we developed a method to predict the potential for ordered states for all apparently disordered proteins with sufficiently rich evolutionary information. The approach is highly accurate (79%) for residue interactions as tested in more than 60 known disordered regions captured in a bound or specific condition. Assessing the potential for structure of more than 1,000 apparently disordered regions of human proteins reveals a continuum of structural order with at least 50% with clear propensity for three-or two-dimensional states. Co-evolutionary constraints reveal hitherto unseen structures of functional importance in apparently disordered proteins. Keywords: Evolutionary couplings disorder; conformational flexibility; statistical physics; maximum entropy; EVfold; bioinformatics; computational biology; structure predictionen_US
dc.description.sponsorshipNational Institutes of Health (U.S.) (Grant R01GM081871)en_US
dc.publisherElsevieren_US
dc.relation.isversionofhttp://dx.doi.org/10.1016/J.CELL.2016.09.010en_US
dc.rightsCreative Commons Attribution-NonCommercial-NoDerivs Licenseen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/en_US
dc.sourcePMCen_US
dc.titleStructured States of Disordered Proteins from Genomic Sequencesen_US
dc.typeArticleen_US
dc.identifier.citationToth-Petroczy, Agnes et al. “Structured States of Disordered Proteins from Genomic Sequences.” Cell 167, 1 (September 2016): 158–170 © 2016 Elsevier Incen_US
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratoryen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.contributor.mitauthorPalmedo, Peter Franklin
dc.contributor.mitauthorBerger Leighton, Bonnie
dc.relation.journalCellen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2018-05-16T15:29:26Z
dspace.orderedauthorsToth-Petroczy, Agnes; Palmedo, Perry; Ingraham, John; Hopf, Thomas A.; Berger, Bonnie; Sander, Chris; Marks, Debora S.en_US
dspace.embargo.termsNen_US
dc.identifier.orcidhttps://orcid.org/0000-0002-2724-7228
mit.licensePUBLISHER_CCen_US


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