Evidence map›Paper›PMID 18831774›Full record

ArticleBMC genomics2008

The unfoldomics decade: an update on intrinsically disordered proteins.

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

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 235 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
235citing papers in PubMed, 2 pooled it
21.0field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

235 citing papers in PubMed, 2 syntheses or guidelines pooled it, 663 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Review
  4. Rapid Fragment Screening byAngewandte Chemie (International ed. in English) · 2026
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  12. Chameleonic Nature of Aβ: Implications for Alzheimer's and Other Amyloid Diseases.BioEssays : news and reviews in molecular, cellular and developmental biology · 2025
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  14. Prediction of Intrinsic Disorder Functions with DEPICTER2.Methods in molecular biology (Clifton, N.J.) · 2025
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  15. Review
  16. Review
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  18. RettDb: the Rett syndrome omics database to navigate the Rett syndrome genomic landscape.Database : the journal of biological databases and curation · 2024
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  20. The Proteomic Analysis of Cancer-Related Alterations in the Human Unfoldome.International journal of molecular sciences · 2024
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175 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 4 institutions in 2 countries.

A Keith DunkerCenter for Computational Biology and Bioinformatics, Indiana University Schools of Medicine and Informatics, Indianapolis, IN 46202, USA. kedunker@iupui.edu
Christopher J Oldfield
Jingwei Meng
Pedro Romero
Jack Y Yang
Jessica Walton Chen
Vladimir Vacic
Zoran Obradovic
Vladimir N Uversky
Indiana University – Purdue University Indianapolis · USIndiana University School of MedicineInstitute for Biological Instrumentation · RUTemple University · US

Funding

Bioinformatics linkage of protein disorder and functionR01LM007688 · NLM · INDIANA UNIV-PURDUE UNIV AT INDIANAPOLIS · PI DUNKER, ALAN KEITH · 2003 to 2006
$1.3M
Mining the Structural Genomics Initiative for DisorderR01GM071714 · NIGMS · INDIANA UNIV-PURDUE UNIV AT INDIANAPOLIS · PI DUNKER, ALAN KEITH · 2006 to 2009
$1.1M
Bioinformatics linkage of protein disorder and functionR56LM007688 · NLM · INDIANA UNIVERSITY INDIANAPOLIS · PI DUNKER, ALAN KEITH · 2008 to 2008
$442k
NIGMS NIH HHS GM071714-01A2NIGMS NIH HHS R01 GM071714NLM NIH HHS R01 LM007688NLM NIH HHS R01 LM007688-01A1NLM NIH HHS R56 LM007688
6 · The paper itself

Abstract

backgroundOur 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.

resultsDisorder 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.

conclusionIntrinsically 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.

Indexed as

Computational BiologyProtein FoldingAlgorithmsAlternative SplicingAmino Acid SequenceBinding SitesDrug DesignHumansProtein ConformationProteinsSequence Analysis, ProteinStructure-Activity RelationshipProteins

Identifiers

PMID18831774
PMCPMC2559873
OpenAlexW1991906934

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.