Evidence map›Paper›PMID 36291578›Full record

ReviewBiomolecules2022

Integration of Nanometer-Range Label-to-Label Distances and Their Distributions into Modelling Approaches.

Gunnar Jeschke

Abstract readReview
In one paragraph

Review in Biomolecules, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. FAMP: A Software Framework for FRET-Based Integrative Modeling of RNA.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. Protein ensemble modeling and analysis with MMMx.Protein science : a publication of the Protein Society · 2024
    Article
  7. 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

1 author.

Gunnar JeschkeDepartment of Chemistry and Applied Biosciences, ETH Zürich, Vladimir-Prelog-Weg 2, CH-8093 Zürich, Switzerland.ORCID 0000-0001-6853-8585

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Labelling techniques such as electron paramagnetic resonance spectroscopy and single-molecule fluorescence resonance energy transfer, allow access to distances in the range of tens of angstroms, corresponding to the size of proteins and small to medium-sized protein complexes. Such measurements do not require long-range ordering and are therefore applicable to systems with partial disorder. Data from spin-label-based measurements can be processed into distance distributions that provide information about the extent of such disorder. Using such information in modelling presents several challenges, including a small number of restraints, the influence of the label itself on the measured distance and distribution width, and balancing the fitting quality of the long-range restraints with the fitting quality of other restraint subsets. Starting with general considerations about integrative and hybrid structural modelling, this review provides an overview of recent approaches to these problems and identifies where further progress is needed.

Indexed as

ProteinsElectron Spin Resonance SpectroscopyModels, MolecularSpin LabelsProteinsSpin Labelsdouble electron electron resonanceensemble modelEPR spectroscopyFRETintrinsic disordermolecular force fieldssite-directed spin labellingstructural biology

Identifiers

PMID36291578
PMCPMC9599366

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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.