Classification of Intrinsically Disordered Regions and Proteins

By R. van der Lee, Marija Buljan, Benjamin Lang, Robert J. Weatheritt, G. Daughdrill, A. Keith Dunker, Mónika Fuxreiter, Julian Gough, J. Gsponer, David T. Jones and 8 more. 2014

1,960 citations recorded by the source corpus.

1.1. Uncharacterized Protein Segments Are a Source of Functional Novelty Over the past decade, we have observed a massive increase in the amount of information describing protein sequences from a variety of organisms.1,2 While this may reflect the diversity in sequence space, and possibly also in function space,3 a large proportion of the sequences lacks any useful function annotation.4,5 Often these sequences are annotated as putative or hypothetical proteins, and for the majority their functions still remain unknown.6,7 Suggestions about potential protein function, primarily molecular function, often come from computational analysis of their sequences. For instance, homology detection allows for the transfer of information from well-characterized protein segments to those with similar sequences that lack annotation of molecular function.8−10 Other aspects of function, such as the biological processes proteins participate in, may come from genetic- and disease-association studies, expression and interaction network data, and comparative genomics approaches that investigate genomic context.11−17 Characterization of unannotated and uncharacterized protein segments is expected to lead to the discovery of novel functions as well as provide important insights into existing biological processes. In addition, it is likely to shed new light on molecular mechanisms of diseases that are not yet fully understood. Thus, uncharacterized protein segments are likely to be a large source of functional novelty relevant for discovering new biology.

Subfields: Molecular Biology

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Citations in the corpus

IUPred2A: context-dependent prediction of protein disorder as a function of redox state and protein binding (2018, background): “Such regions are best characterized as ensembles of highly fluctuating conformations in isolation but their detailed properties are delicately tailored for their specific function (2).”
DisProt 7.0: a major update of the database of disordered proteins (2016, neutral): “Although they cannot be crystallized and thus cannot be directly characterized by X-ray crystallography, there are a variety of techniques that can report on their highly dynamic structural state at low- or even high spatial and temporal resolution (3).”
The s2D method: simultaneous sequence-based prediction of the statistical populations of ordered and disordered regions in proteins. (2015, background): “Many IDPs, however, perform their function by transiently populating relatively structured states [7,12,38].”
AlphaFold2: A Role for Disordered Protein/Region Prediction? (2022, background): “Since the time that problem was posed by Perutz and Kendrew, a new class of proteins, intrinsically disordered proteins, has been discovered and IDPs have become the focus of much study [10,11,13,14,60,61].”
FuzDB: database of fuzzy complexes, a tool to develop stochastic structure-function relationships for protein complexes and higher-order assemblies (2016, background): “The multiplicity of structures and their plasticity bias these proteins for interactions with many different partners, either simultaneously or in spatially/temporally separated fashion (3).”
MobiDB 2.0: an improved database of intrinsically disordered and mobile proteins (2014, background): “Proteins with long disorder regions are more frequent in higher Eukaryotes and known to have specific functions (3,5) as well as being associated with human diseases such as cancer (31).”
The impact of AlphaFold2 one year on (2022, positive): “By comparison with proteins for which experimental structures are already available in the PDB, it is clear that most of the AlphaFold2 models generated are of very high quality, with good side-chain placement and very low root-mean-square deviations (r.m.s.d.).”
Principles of protein structural ensemble determination. (2017, background): “It has been suggested that these proteins make up about one-third of the human proteome [10,12] and that their dynamic nature facilitates multiple interactions, making them particularly important in regulation and signalling processes [10,13].”
Disorder Prediction Methods, Their Applicability to Different Protein Targets and Their Usefulness for Guiding Experimental Studies (2015, background): “SAXS works by measuring the scatter of X-rays caused by the protein within solution, thereby providing details on the shape and dimensions of the structure [23].”