Evidence map›Paper›PMID 20186334›Full record

ArticlePloS one2010

A computational approach for deciphering the organization of glycosaminoglycans.

Jean L Spencer, Joel A Bernanke, Jo Ann Buczek-Thomas, Matthew A Nugent

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.1field-weighted citation impact, top 26% 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

11 citing papers in PubMed, 24 citations in OpenAlex.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Docking server for the identification of heparin binding sites on proteins.Journal of chemical information and modeling · 2014
    Article
  7. Heparan sulfate-protein binding specificity.Biochemistry. Biokhimiia · 2013
    Review
  8. Glycosaminoglycan glycomics using mass spectrometry.Molecular & cellular proteomics : MCP · 2013
    Review
  9. Article
  10. Proteoglycan sequence.Molecular bioSystems · 2012
    Review
  11. Review
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

4 authors at 1 institution in 1 country.

Jean L SpencerDepartment of Biochemistry, Boston University School of Medicine, Boston, Massachusetts, United States of America. spencerj@bu.edu
Joel A Bernanke
Jo Ann Buczek-Thomas
Matthew A Nugent
Boston University · US

Funding

Growth Factors in Vascular BiologyR01HL056200 · NHLBI · BOSTON UNIVERSITY MEDICAL CAMPUS · PI NUGENT, MATTHEW A · 1997 to 2008
$2.7M
Elastase Injury of Pulmonary Extracellular MatrixR01HL088572 · NHLBI · BOSTON UNIVERSITY MEDICAL CAMPUS · PI NUGENT, MATTHEW A · 2008 to 2012
$2.0M
NHLBI NIH HHS HL088672NHLBI NIH HHS HL56200NHLBI NIH HHS R01 HL056200NHLBI NIH HHS R01 HL088572
6 · The paper itself

Abstract

backgroundIncreasing evidence has revealed important roles for complex glycans as mediators of normal and pathological processes. Glycosaminoglycans are a class of glycans that bind and regulate the function of a wide array of proteins at the cell-extracellular matrix interface. The specific sequence and chemical organization of these polymers likely define function; however, identification of the structure-function relationships of glycosaminoglycans has been met with challenges associated with the unique level of complexity and the nontemplate-driven biosynthesis of these biopolymers. METHODOLOGY/PRINCIPAL

findingsTo address these challenges, we have devised a computational approach to predict fine structure and patterns of domain organization of the specific glycosaminoglycan, heparan sulfate (HS). Using chemical composition data obtained after complete and partial digestion of mixtures of HS chains with specific degradative enzymes, the computational analysis produces populations of theoretical HS chains with structures that meet both biosynthesis and enzyme degradation rules. The model performs these operations through a modular format consisting of input/output sections and three routines called chainmaker, chainbreaker, and chainsorter. We applied this methodology to analyze HS preparations isolated from pulmonary fibroblasts and epithelial cells. Significant differences in the general organization of these two HS preparations were observed, with HS from epithelial cells having a greater frequency of highly sulfated domains. Epithelial HS also showed a higher density of specific HS domains that have been associated with inhibition of neutrophil elastase. Experimental analysis of elastase inhibition was consistent with the model predictions and demonstrated that HS from epithelial cells had greater inhibitory activity than HS from fibroblasts. CONCLUSIONS/SIGNIFICANCE: This model establishes the conceptual framework for a new class of computational tools to use to assess patterns of domain organization within glycosaminoglycans. These tools will provide a means to consider high-level chain organization in deciphering the structure-function relationships of polysaccharides in biology.

Indexed as

Models, ChemicalSoftwareAlgorithmsAnimalsBinding SitesCell LineCells, CulturedDisaccharidesEpithelial CellsFibroblastsFourier AnalysisGlycosaminoglycansHeparan SulfateHeparin LyaseHexuronic AcidsMolecular StructureDisaccharidesGlycosaminoglycansHeparan SulfateHeparin LyaseHexuronic Acids

Identifiers

PMID20186334
PMCPMC2826411
OpenAlexW2001311229

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.