Structured States of Disordered Proteins from Genomic Sequences
Name
nihms816623.pdf
Size
1.18 MB
Format
Adobe PDF
Checksum (MD5)
9b67aff16d39641aa9008279177a4134
Author(s)
Toth-Petroczy, Agnes
Ingraham, John
Hopf, Thomas A.
Sander, Chris
Marks, Debora S.
Palmedo, Peter Franklin
Berger Leighton, Bonnie
Date Issued
September 2016
Journal
Cell
Publisher
Elsevier
Citation
Toth-Petroczy, Agnes et al. “Structured States of Disordered Proteins from Genomic Sequences.” Cell 167, 1 (September 2016): 158–170 © 2016 Elsevier Inc
Version
Author's final manuscript
Abstract
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
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Terms of Use
Creative Commons Attribution-NonCommercial-NoDerivs License
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1016/J.CELL.2016.09.010
