Evidence map›Paper›PMID 21614187›Full record

ArticleInternational journal of molecular sciences2010

Computational prediction of O-linked glycosylation sites that preferentially map on intrinsically disordered regions of extracellular proteins.

Ikuko Nishikawa, Yukiko Nakajima, Masahiro Ito, Satoshi Fukuchi, Keiichi Homma, Ken Nishikawa

Abstract read
In one paragraph

Article in International journal of molecular sciences, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers.

0numbers the graph read from it
0cells of the map it votes in
40citing 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

40 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Article
  6. Review
  7. Article
  8. Article
  9. Advances in chemical probing of proteinChemical Society reviews · 2021
    Review
  10. Review
  11. Precision Mapping of O-LinkedJournal of the American Chemical Society · 2020
    Article
  12. Article
  13. Article
  14. Frontiers in genetics · 2020
    Review
  15. Exploitation of glycosylation in enveloped virus pathobiology.Biochimica et biophysica acta. General subjects · 2019
    Review
  16. Article
  17. Review
  18. Article
  19. Review
  20. Article
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

6 authors.

Ikuko NishikawaCollege of Information Science and Engineering, Ritsumeikan University/Noji-higashi 1-1-1, Kusatsu, Shiga 525-8577, Japan; E-Mail: nakajima.yukiko@gmail.com.
Yukiko Nakajima
Masahiro Ito
Satoshi Fukuchi
Keiichi Homma
Ken Nishikawa

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

O-glycosylation of mammalian proteins is one of the important posttranslational modifications. We applied a support vector machine (SVM) to predict whether Ser or Thr is glycosylated, in order to elucidate the O-glycosylation mechanism. O-glycosylated sites were often found clustered along the sequence, whereas other sites were located sporadically. Therefore, we developed two types of SVMs for predicting clustered and isolated sites separately. We found that the amino acid composition was effective for predicting the clustered type, whereas the site-specific algorithm was effective for the isolated type. The highest prediction accuracy for the clustered type was 74%, while that for the isolated type was 79%. The existence frequency of amino acids around the O-glycosylation sites was different in the two types: namely, Pro, Val and Ala had high existence probabilities at each specific position relative to a glycosylation site, especially for the isolated type. Independent component analyses for the amino acid sequences around O-glycosylation sites showed the position-specific existences of the identified amino acids as independent components. The O-glycosylation sites were preferentially located within intrinsically disordered regions of extracellular proteins: particularly, more than 90% of the clustered O-GalNAc glycosylation sites were observed in intrinsically disordered regions. This feature could be the key for understanding the non-conservation property of O-glycosylation, and its role in functional diversity and structural stability.

Indexed as

Computer SimulationNeural Networks, ComputerGlycosylationProtein ConformationProteinsSequence Analysis, ProteinProteinsclustered and isolated glycosylation sitesextracellular proteinintrinsically disorderedmucin-typenon-conservation propertyposttranslational modificationprotein O-glycosylationsupport vector machine

Identifiers

PMID21614187
PMCPMC3100847

What OpenQuestion holds

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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.