Evidence map›Paper›PMID 27626458›Full record

ArticleThe journal of physical chemistry letters2016

Reconciling Intermediates in Mechanical Unfolding Experiments with Two-State Protein Folding in Bulk.

David de Sancho, Robert B Best

Abstract read
In one paragraph

Article in The journal of physical chemistry letters, 2016. 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. Strain learning in protein-based mechanical metamaterials.Proceedings of the National Academy of Sciences of the United States of America · 2024
    Article
  2. Article
  3. Review
  4. Article
  5. Article
  6. Proteins Breaking Bad: A Free Energy Perspective.The journal of physical chemistry letters · 2017
    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

2 authors.

David de SanchoCIC nanoGUNE , 20018 Donostia-San Sebastián, Spain.
Robert B BestLaboratory of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health , Bethesda, Maryland 20892-0520, United States.

Funding

Understanding protein folding, evolution and function via molecular simulationZIADK075104 · NIDDK · NATIONAL INSTITUTE OF DIABETES AND DIGESTIVE AND KIDNEY DISEASES · PI BEST, ROBERT · 2013 to 2025
$13.7M
Intramural NIH HHS Z99 DK999999
6 · The paper itself

Abstract

Most experimentally well-characterized single domain proteins of less than 100 residues have been found to be two-state folders. That is, only two distinct populations can explain both equilibrium and kinetic measurements. Results from single molecule force spectroscopy, where a protein is unfolded by applying a mechanical pulling force to its ends, have largely confirmed this description for proteins found to be two-state in ensemble experiments. Recently, however, stable intermediates have been reported in mechanical unfolding experiments on a cold-shock protein previously found to be a prototypical two-state folder. Here, we tackle this discrepancy using free energy landscapes and Markov state models derived from coarse-grained molecular simulations. We show that protein folding intermediates can be selectively stabilized by the pulling force and that the populations of these intermediates vary in a force-dependent manner. Our model qualitatively captures the experimental results and suggests a possible origin of the apparent discrepancy.

Indexed as

Bacterial ProteinsCold Shock Proteins and PeptidesKineticsMarkov ChainsMicroscopy, Atomic ForceProtein FoldingProteinsProtein UnfoldingThermodynamicsThermotoga maritimaBacterial ProteinsCold Shock Proteins and PeptidesProteins

Identifiers

PMID27626458
PMCPMC5597958

What OpenQuestion holds

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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.