Evidence map›Paper›PMID 26477253›Full record

ArticleMethods in enzymology2015

Peptide-Membrane Interactions by Spin-Labeling EPR.

Tatyana I Smirnova, Alex I Smirnov

Open access · greenAbstract read
In one paragraph

Article in Methods in enzymology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
0.8field-weighted citation impact, top 8% 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

9 citing papers in PubMed, 20 citations in OpenAlex.

  1. Review
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  9. The two sides of a lipid-protein story.Biophysical reviews · 2016
    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

2 authors at 1 institution in 1 country.

Tatyana I SmirnovaDepartment of Chemistry, North Carolina State University, Raleigh, North Carolina, USA. Electronic address: tismirno@ncsu.edu.
Alex I SmirnovDepartment of Chemistry, North Carolina State University, Raleigh, North Carolina, USA.
North Carolina State University · US

Funding

Time-domain/ELDOR EPR SpectrometerS10RR023614 · NCRR · NORTH CAROLINA STATE UNIVERSITY RALEIGH · PI SMIRNOV, ALEX I. · 2009 to 2009
$500k
NCRR NIH HHS RR023614NCRR NIH HHS S10 RR023614
6 · The paper itself

Abstract

Site-directed spin labeling (SDSL) in combination with electron paramagnetic resonance (EPR) spectroscopy is a well-established method that has recently grown in popularity as an experimental technique, with multiple applications in protein and peptide science. The growth is driven by development of labeling strategies, as well as by considerable technical advances in the field, that are paralleled by an increased availability of EPR instrumentation. While the method requires an introduction of a paramagnetic probe at a well-defined position in a peptide sequence, it has been shown to be minimally destructive to the peptide structure and energetics of the peptide-membrane interactions. In this chapter, we describe basic approaches for using SDSL EPR spectroscopy to study interactions between small peptides and biological membranes or membrane mimetic systems. We focus on experimental approaches to quantify peptide-membrane binding, topology of bound peptides, and characterize peptide aggregation. Sample preparation protocols including spin-labeling methods and preparation of membrane mimetic systems are also described.

Indexed as

AnimalsBinding SitesCell MembraneElectron Spin Resonance SpectroscopyHumansLipid BilayersPeptidesProtein AggregatesSpin LabelsThermodynamicsLipid BilayersPeptidesProtein AggregatesSpin LabelsAccessibility EPR experimentsBinding isothermsMembrane mimeticsPeptide aggregationPeptide binding

Identifiers

PMID26477253
PMCPMC5008870
OpenAlexW1944086851

What OpenQuestion holds

Textmetadata
LicenceTDM
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.