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|a Toth-Petroczy, Agnes
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|a Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
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|a Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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|a Palmedo, Peter Franklin
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|a Berger Leighton, Bonnie
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|a Ingraham, John
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|a Hopf, Thomas A.
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|a Sander, Chris
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|a Marks, Debora S.
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|a Palmedo, Peter Franklin
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|a Berger Leighton, Bonnie
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|a Structured States of Disordered Proteins from Genomic Sequences
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|b Elsevier,
|c 2018-05-17T17:03:23Z.
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|z Get fulltext
|u http://hdl.handle.net/1721.1/115426
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|a Protein 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 prediction
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|a National Institutes of Health (U.S.) (Grant R01GM081871)
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|a Article
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|t Cell
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