Evidence map›Paper›PMID 37117432›Full record

ReviewNature reviews. Chemistry2022

Studying protein structure and function by native separation-mass spectrometry.

Guusje van Schaick, Rob Haselberg, Govert W Somsen, Manfred Wuhrer, Elena Domínguez-Vega

Open access · hybridAbstract readReview
PubMed Publisher
In one paragraph

Review in Nature reviews. Chemistry, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
6.3field-weighted citation impact, top 2% 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

27 citing papers in PubMed, 57 citations in OpenAlex.

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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 2 institutions in 1 country.

Guusje van SchaickCenter for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, Netherlands.ORCID 0000-0001-8320-4460
Rob HaselbergDivision of Bioanalytical Chemistry, Amsterdam Institute of Molecular and Life Sciences, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.ORCID 0000-0003-1892-1724
Govert W SomsenDivision of Bioanalytical Chemistry, Amsterdam Institute of Molecular and Life Sciences, Vrije Universiteit Amsterdam, Amsterdam, Netherlands.ORCID 0000-0003-4200-2015
Manfred WuhrerCenter for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, Netherlands.ORCID 0000-0002-0814-4995
Elena Domínguez-VegaCenter for Proteomics and Metabolomics, Leiden University Medical Center, Leiden, Netherlands. E.Dominguez_Vega@lumc.nl.ORCID 0000-0002-6394-0783
Leiden University Medical Center · NLVrije Universiteit Amsterdam · NL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Alterations in protein structure may have profound effects on biological function. Analytical techniques that permit characterization of proteins while maintaining their conformational and functional state are crucial for studying changes in the higher order structure of proteins and for establishing structure-function relationships. Coupling of native protein separations with mass spectrometry is emerging rapidly as a powerful approach to study these aspects in a reliable, fast and straightforward way. This Review presents the available native separation modes for proteins, covers practical considerations on the hyphenation of these separations with mass spectrometry and highlights the involvement of affinity-based separations to simultaneously obtain structural and functional information of proteins. The impact of these approaches is emphasized by selected applications addressing biomedical and biopharmaceutical research questions.

Indexed as

Biological ProductsProteinsMass SpectrometryBiological ProductsProteins

Identifiers

PMID37117432
OpenAlexW4205939631

What OpenQuestion holds

Textmetadata
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.