Intrinsically disordered proteins: regulation and disease.

By M. Babu, R. van der Lee, N. S. de Groot, Jörg Gsponer. Current Opinion in Structural Biology, 2011

596 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/d12a36f0e97be3557aa4b38b50cbff67da51024d

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In Molecular Biology

Citations in the corpus

Computational Identification of MoRFs in Protein Sequences Using Hierarchical Application of Bayes Rule (2015, background): “…in regulatory processes and in signal transduction [3], as their structural flexibility grants MoRFs the ability to mold into a precise fit for a given binding surface and, thereby, achieve high interaction specificity, which is often desirable for protein interactions in signaling pathways [9].”
The s2D method: simultaneous sequence-based prediction of the statistical populations of ordered and disordered regions in proteins. (2015, background): “Detailed experimental characterization of structure and disorder in proteins remains a difficult and costly task, which is associated with the risk of obtaining inconclusive results especially when not employing a broad range of different techniques [7–12,14].”
Motif switches: decision-making in cell regulation. (2012, background): “As a result, to abrogate off-target effects, gene dosage of motif-containing proteins must be carefully controlled to ensure appropriate protein localisation and stoichiometry [4 ,18–20].”
MoRFchibi SYSTEM: software tools for the identification of MoRFs in protein sequences (2016, background): “Work in the last two decades has revealed that intrinsically disordered protein regions (IDRs) mediate many interactions as their structural flexibility enables them to ideally fit their target domain’s binding surfaces (1).”
Computational identification of MoRFs in protein sequences (2015, background): “Because of this functionality, their interactions need to be both specific and reversible (Babu et al., 2011; Mohan et al., 2006; Wong et al., 2013).”
Harnessing protein folding neural networks for peptide–protein docking (2021, methodology): “These advances were possible thanks to (1) the immense increase of sequenced proteins, allowing for the generation of highly informative Multiple Sequence Alignments (MSA), (2) the large amount of solved structures in the Protein Data Bank (PDB) that has been accumulated by low throughput and extens”