Structured states of disordered proteins from genomic sequences

By Agnes Toth-Petroczy, Perry Palmedo, John Ingraham, Thomas A. Hopf, Bonnie Berger, Christopher Sander, Debora Marks. 2016

132 citations recorded by the source corpus.

SUMMARY 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 over 60 known disordered regions captured in a bound or specific condition. Assessing the potential for structure of over 1000 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 structure of functional importance in apparently disordered proteins.

Subfields: Molecular Biology

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Citations in the corpus

Enhancing Evolutionary Couplings with Deep Convolutional Neural Networks (2017, methodology): “Importantly, some of the false contacts identified by DeepContact are true homodimer contacts and others may be true in another conformation, particularly given the small distances between the residues of many of the false contacts (Figures 3A and 4B) (Hopf et al., 2012; Morcos et al., 2011; Toth-Pe”
Large-scale structure prediction by improved contact predictions and model quality assessment (2017, background): “It has been shown that accurate protein structures can be obtained for soluble proteins (Marks et al., 2011), membrane proteins (Nugent and Jones, 2012; Hopf et al., 2012; Hayat et al., 2015) and even disordered proteins (Toth-Petroczy et al., 2016).”
The challenge of modeling protein assemblies: the CASP12‐CAPRI experiment (2018, result): “Progress in this endeavor will likely come from charting conformational changes in families or related proteins(50) and exploiting information on co-evolution.(51,52) The latter approach is already making important headways in predicting the structures of protein monomers, as witnessed by results ob”
Origins of coevolution between residues distant in protein 3D structures (2017, background): “There has been considerable recent success in using direct couplings to infer residue–residue contacts for protein structure prediction (6–9), protein–protein complex prediction (10–12), identification of specific interaction partners among two sets of paralogous proteins (13), resolution of ambigui”