Evidence map›Paper›PMID 25594741›Full record

ArticleBioconjugate chemistry2015

Dual-purpose linker for alpha helix stabilization and imaging agent conjugation to glucagon-like peptide-1 receptor ligands.

Liang Zhang, Tejas Navaratna, Jianshan Liao, Greg M Thurber

Abstract read
In one paragraph

Article in Bioconjugate chemistry, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Directed Evolution Using Stabilized Bacterial Peptide Display.Journal of the American Chemical Society · 2020
    Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. 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

4 authors.

Liang ZhangDepartment of Chemical Engineering, ‡Department of Biomedical Engineering, University of Michigan , Ann Arbor, Michigan 48109, United States.
Tejas Navaratna
Jianshan Liao
Greg M Thurber

Funding

Whole Body Imaging of Beta Cell Mass in DiabetesK01DK093766 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI THURBER, GREG · 2011 to 2014
$641k
NIDDK NIH HHS 1K01DK093766NIDDK NIH HHS K01 DK093766
6 · The paper itself

Abstract

Peptides display many characteristics of efficient imaging agents such as rapid targeting, fast background clearance, and low non-specific cellular uptake. However, poor stability, low affinity, and loss of binding after labeling often preclude their use in vivo. Using glucagon-like peptide-1 receptor (GLP-1R) ligands exendin and GLP-1 as a model system, we designed a novel α-helix-stabilizing linker to simultaneously address these limitations. The stabilized and labeled peptides showed an increase in helicity, improved protease resistance, negligible loss or an improvement in binding affinity, and excellent in vivo targeting. The ease of incorporating azidohomoalanine in peptides and efficient reaction with the dialkyne linker enable this technique to potentially be used as a general method for labeling α helices. This strategy should be useful for imaging beta cells in diabetes research and in developing and testing other peptide targeting agents.

Indexed as

Amino Acid SequenceAnimalsExenatideGlucagon-Like Peptide 1Glucagon-Like Peptide-1 ReceptorHistological TechniquesInsulin-Secreting CellsLigandsMiceMice, Inbred C57BLMicroscopyModels, MolecularMolecular Sequence DataOptical ImagingPancreatic NeoplasmsPeptidesExenatideGlp1r protein, mouseGlucagon-Like Peptide 1Glucagon-Like Peptide-1 ReceptorLigandsPeptidesReceptors, GlucagonVenoms

Identifiers

PMID25594741
PMCPMC4933591

What OpenQuestion holds

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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.