Evidence map›Paper›PMID 19594871›Full record

ArticleBMC genomics2009

Protein disorder in the human diseasome: unfoldomics of human genetic diseases.

Uros Midic, Christopher J Oldfield, A Keith Dunker, Zoran Obradovic, Vladimir N Uversky

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 77 papers.

0numbers the graph read from it
0cells of the map it votes in
77citing papers in PubMed
5.1field-weighted citation impact, top 4% 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

77 citing papers in PubMed, 146 citations in OpenAlex.

  1. Review
  2. Article
  3. The Polymers of Life: Exploring Cellular Function Through Polymer Concepts.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Review
  4. Review
  5. Article
  6. Review
  7. Exploring Intrinsic Disorder in Human Synucleins and Associated Proteins.International journal of molecular sciences · 2024
    Article
  8. Article
  9. The Proteomic Analysis of Cancer-Related Alterations in the Human Unfoldome.International journal of molecular sciences · 2024
    Article
  10. Review
  11. Review
  12. Computational prediction of disordered binding regions.Computational and structural biotechnology journal · 2023
    Review
  13. Article
  14. Article
  15. Article
  16. Review
  17. Review
  18. Deep learning in prediction of intrinsic disorder in proteins.Computational and structural biotechnology journal · 2022
    Review
  19. Article
  20. Article

17 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

5 authors at 3 institutions in 2 countries.

Uros MidicCenter for Information Science and Technology, Temple University, Philadelphia, PA 19122, USA. uros@ist.temple.edu
Christopher J Oldfield
A Keith Dunker
Zoran Obradovic
Vladimir N Uversky
Indiana University – Purdue University Indianapolis · USTemple University · USIndiana University School of Medicine

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
NIGMS NIH HHS GM071714-01A2NIGMS NIH HHS R01 GM071714NLM NIH HHS R01 LM007688NLM NIH HHS R01 LM007688-01A1
6 · The paper itself

Abstract

backgroundIntrinsically disordered proteins lack stable structure under physiological conditions, yet carry out many crucial biological functions, especially functions associated with regulation, recognition, signaling and control. Recently, human genetic diseases and related genes were organized into a bipartite graph (Goh KI, Cusick ME, Valle D, Childs B, Vidal M, et al. (2007) The human disease network. Proc Natl Acad Sci U S A 104: 8685-8690). This diseasome network revealed several significant features such as the common genetic origin of many diseases. METHODS AND

findingsWe analyzed the abundance of intrinsic disorder in these diseasome network proteins by means of several prediction algorithms, and we analyzed the functional repertoires of these proteins based on prior studies relating disorder to function. Our analyses revealed that (i) Intrinsic disorder is common in proteins associated with many human genetic diseases; (ii) Different disease classes vary in the IDP contents of their associated proteins; (iii) Molecular recognition features, which are relatively short loosely structured protein regions within mostly disordered sequences and which gain structure upon binding to partners, are common in the diseasome, and their abundance correlates with the intrinsic disorder level; (iv) Some disease classes have a significant fraction of genes affected by alternative splicing, and the alternatively spliced regions in the corresponding proteins are predicted to be highly disordered; and (v) Correlations were found among the various diseasome graph-related properties and intrinsic disorder.

conclusionThese observations provide the basis for the construction of the human-genetic-disease-associated unfoldome.

Indexed as

Protein FoldingProteomicsAlgorithmsAlternative SplicingComputational BiologyDatabases, ProteinHumansProtein ConformationProteinsStructure-Activity RelationshipProteins

Identifiers

PMID19594871
PMCPMC2709255
OpenAlexW2000330915

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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.