Evidence map›Paper›PMID 17391014›Full record

ArticleJournal of proteome research2007

Functional anthology of intrinsic disorder. 1. Biological processes and functions of proteins with long disordered regions.

Hongbo Xie, Slobodan Vucetic, Lilia M Iakoucheva, Christopher J Oldfield, A Keith Dunker, Vladimir N Uversky, Zoran Obradovic

Abstract read
In one paragraph

Article in Journal of proteome research, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 259 papers.

0numbers the graph read from it
0cells of the map it votes in
259citing papers in PubMed
–field-weighted citation impact
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

259 citing papers in PubMed.

  1. Article
  2. Alphafuser: a parsimonious approach to predicting higher-order protein complexes.Acta crystallographica. Section D, Structural biology · 2026
    Article
  3. Review
  4. Article
  5. Prediction of Intrinsically Disordered Regions That Bind RNA with DisoRDPbind.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Evaluation of predictions of disordered binding regions in the CAID2 experiment.Computational and structural biotechnology journal · 2025
    Review
  13. Prediction of Disordered Linkers Using APOD.Methods in molecular biology (Clifton, N.J.) · 2025
    Article
  14. Article
  15. Review
  16. Exploring Intrinsic Disorder in Human Synucleins and Associated Proteins.International journal of molecular sciences · 2024
    Article
  17. Article
  18. Review
  19. Review
  20. Article

199 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

7 authors.

Hongbo XieCenter for Information Science and Technology, Temple University, Philadelphia, Pennsylvania 19122, USA.
Slobodan Vucetic
Lilia M Iakoucheva
Christopher J Oldfield
A Keith Dunker
Vladimir N Uversky
Zoran Obradovic

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 R01 GM071714NLM NIH HHS LM007688-0A1NLM NIH HHS R01 LM007688NLM NIH HHS R56 LM007688
6 · The paper itself

Abstract

Identifying relationships between function, amino acid sequence, and protein structure represents a major challenge. In this study, we propose a bioinformatics approach that identifies functional keywords in the Swiss-Prot database that correlate with intrinsic disorder. A statistical evaluation is employed to rank the significance of these correlations. Protein sequence data redundancy and the relationship between protein length and protein structure were taken into consideration to ensure the quality of the statistical inferences. Over 200,000 proteins from the Swiss-Prot database were analyzed using this approach. The predictions of intrinsic disorder were carried out using PONDR VL3E predictor of long disordered regions that achieves an accuracy of above 86%. Overall, out of the 710 Swiss-Prot functional keywords that were each associated with at least 20 proteins, 238 were found to be strongly positively correlated with predicted long intrinsically disordered regions, whereas 302 were strongly negatively correlated with such regions. The remaining 170 keywords were ambiguous without strong positive or negative correlation with the disorder predictions. These functions cover a large variety of biological activities and imply that disordered regions are characterized by a wide functional repertoire. Our results agree well with literature findings, as we were able to find at least one illustrative example of functional disorder or order shown experimentally for the vast majority of keywords showing the strongest positive or negative correlation with intrinsic disorder. This work opens a series of three papers, which enriches the current view of protein structure-function relationships, especially with regards to functionalities of intrinsically disordered proteins, and provides researchers with a novel tool that could be used to improve the understanding of the relationships between protein structure and function. The first paper of the series describes our statistical approach, outlines the major findings, and provides illustrative examples of biological processes and functions positively and negatively correlated with intrinsic disorder.

Indexed as

Protein ConformationProteinsSequence Analysis, ProteinAlgorithmsAnimalsComputational BiologyDatabases, ProteinHumansProteins

Identifiers

PMID17391014
PMCPMC2543138

What OpenQuestion holds

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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.