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The unfoldomics decade: an update on intrinsically disordered proteins

Overview of attention for article published in BMC Genomics, September 2008
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (82nd percentile)
  • High Attention Score compared to outputs of the same age and source (85th percentile)

Mentioned by

blogs
1 blog
q&a
1 Q&A thread

Citations

dimensions_citation
472 Dimensions

Readers on

mendeley
537 Mendeley
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11 CiteULike
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Title
The unfoldomics decade: an update on intrinsically disordered proteins
Published in
BMC Genomics, September 2008
DOI 10.1186/1471-2164-9-s2-s1
Pubmed ID
Authors

A Keith Dunker, Christopher J Oldfield, Jingwei Meng, Pedro Romero, Jack Y Yang, Jessica Walton Chen, Vladimir Vacic, Zoran Obradovic, Vladimir N Uversky

Abstract

Our first predictor of protein disorder was published just over a decade ago in the Proceedings of the IEEE International Conference on Neural Networks (Romero P, Obradovic Z, Kissinger C, Villafranca JE, Dunker AK (1997) Identifying disordered regions in proteins from amino acid sequence. Proceedings of the IEEE International Conference on Neural Networks, 1: 90-95). By now more than twenty other laboratory groups have joined the efforts to improve the prediction of protein disorder. While the various prediction methodologies used for protein intrinsic disorder resemble those methodologies used for secondary structure prediction, the two types of structures are entirely different. For example, the two structural classes have very different dynamic properties, with the irregular secondary structure class being much less mobile than the disorder class. The prediction of secondary structure has been useful. On the other hand, the prediction of intrinsic disorder has been revolutionary, leading to major modifications of the more than 100 year-old views relating protein structure and function. Experimentalists have been providing evidence over many decades that some proteins lack fixed structure or are disordered (or unfolded) under physiological conditions. In addition, experimentalists are also showing that, for many proteins, their functions depend on the unstructured rather than structured state; such results are in marked contrast to the greater than hundred year old views such as the lock and key hypothesis. Despite extensive data on many important examples, including disease-associated proteins, the importance of disorder for protein function has been largely ignored. Indeed, to our knowledge, current biochemistry books don't present even one acknowledged example of a disorder-dependent function, even though some reports of disorder-dependent functions are more than 50 years old. The results from genome-wide predictions of intrinsic disorder and the results from other bioinformatics studies of intrinsic disorder are demanding attention for these proteins. Disorder prediction has been important for showing that the relatively few experimentally characterized examples are members of a very large collection of related disordered proteins that are wide-spread over all three domains of life. Many significant biological functions are now known to depend directly on, or are importantly associated with, the unfolded or partially folded state. Here our goal is to review the key discoveries and to weave these discoveries together to support novel approaches for understanding sequence-function relationships. Intrinsically disordered protein is common across the three domains of life, but especially common among the eukaryotic proteomes. Signaling sequences and sites of posttranslational modifications are frequently, or very likely most often, located within regions of intrinsic disorder. Disorder-to-order transitions are coupled with the adoption of different structures with different partners. Also, the flexibility of intrinsic disorder helps different disordered regions to bind to a common binding site on a common partner. Such capacity for binding diversity plays important roles in both protein-protein interaction networks and likely also in gene regulation networks. Such disorder-based signaling is further modulated in multicellular eukaryotes by alternative splicing, for which such splicing events map to regions of disorder much more often than to regions of structure. Associating alternative splicing with disorder rather than structure alleviates theoretical and experimentally observed problems associated with the folding of different length, isomeric amino acid sequences. The combination of disorder and alternative splicing is proposed to provide a mechanism for easily "trying out" different signaling pathways, thereby providing the mechanism for generating signaling diversity and enabling the evolution of cell differentiation and multicellularity. Finally, several recent small molecules of interest as potential drugs have been shown to act by blocking protein-protein interactions based on intrinsic disorder of one of the partners. Study of these examples has led to a new approach for drug discovery, and bioinformatics analysis of the human proteome suggests that various disease-associated proteins are very rich in such disorder-based drug discovery targets.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 537 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 14 3%
United Kingdom 7 1%
Germany 4 <1%
Poland 2 <1%
France 2 <1%
Canada 2 <1%
Belgium 2 <1%
Argentina 2 <1%
India 1 <1%
Other 9 2%
Unknown 492 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 156 29%
Researcher 112 21%
Student > Master 61 11%
Student > Bachelor 38 7%
Professor 27 5%
Other 88 16%
Unknown 55 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 226 42%
Biochemistry, Genetics and Molecular Biology 130 24%
Chemistry 45 8%
Physics and Astronomy 20 4%
Computer Science 11 2%
Other 39 7%
Unknown 66 12%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 11 January 2012.
All research outputs
#4,571,315
of 25,374,917 outputs
Outputs from BMC Genomics
#1,709
of 11,244 outputs
Outputs of similar age
#15,682
of 90,485 outputs
Outputs of similar age from BMC Genomics
#7
of 48 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,244 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done well, scoring higher than 84% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 90,485 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 82% of its contemporaries.
We're also able to compare this research output to 48 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 85% of its contemporaries.