Evidence map›Paper›PMID 27383269›Full record

ArticleeLife2016

Molecular dynamics-based refinement and validation for sub-5 Å cryo-electron microscopy maps.

Abhishek Singharoy, Ivan Teo, Ryan McGreevy, John E Stone, Jianhua Zhao, Klaus Schulten

Abstract read
In one paragraph

Article in eLife, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 95 papers.

0numbers the graph read from it
0cells of the map it votes in
95citing 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

95 citing papers in PubMed.

  1. Article
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  3. Hydrogen Atomic Motions in Different Intramolecular Environments: HThe journal of physical chemistry letters · 2026
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  6. MELD in Action: Harnessing Data to Accelerate Molecular Dynamics.Journal of chemical information and modeling · 2025
    Review
  7. Article
  8. AI-based methods for biomolecular structure modeling for Cryo-EM.Current opinion in structural biology · 2025
    Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

35 more citing papers are in PubMed but not listed here.

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

6 authors.

Abhishek SingharoyBeckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, United States.
Ivan TeoBeckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, United States.
Ryan McGreevyBeckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, United States.
John E StoneBeckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, United States.
Jianhua ZhaoDepartment of Biochemistry and Biophysics, University of California San Francisco School of Medicine, San Francisco, United States.
Klaus SchultenBeckman Institute for Advanced Science and Technology, University of Illinois at Urbana-Champaign, Urbana, United States.ORCID 0000-0001-7192-9632

Funding

Synthetic Antigen Binder CoreU54GM087519 · NIGMS · UNIVERSITY OF CHICAGO · PI ROUX, BENOIT · 2010 to 2017
$31.9M
WHOLE CELL SIMULATIONP41GM104601 · NIGMS · UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN · PI TAJKHORSHID, EMAD · 2012 to 2021
$19.0M
Commodity Hardware Acceleration of Popular Modeling Software for Structural BioloR01GM098243 · NIGMS · UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN · PI SCHULTEN, KLAUS · 2011 to 2014
$1.2M
NIGMS NIH HHS P41 GM104601NIGMS NIH HHS R01 GM098243NIGMS NIH HHS U54 GM087519
6 · The paper itself

Abstract

Two structure determination methods, based on the molecular dynamics flexible fitting (MDFF) paradigm, are presented that resolve sub-5 Å cryo-electron microscopy (EM) maps with either single structures or ensembles of such structures. The methods, denoted cascade MDFF and resolution exchange MDFF, sequentially re-refine a search model against a series of maps of progressively higher resolutions, which ends with the original experimental resolution. Application of sequential re-refinement enables MDFF to achieve a radius of convergence of ~25 Å demonstrated with the accurate modeling of β-galactosidase and TRPV1 proteins at 3.2 Å and 3.4 Å resolution, respectively. The MDFF refinements uniquely offer map-model validation and B-factor determination criteria based on the inherent dynamics of the macromolecules studied, captured by means of local root mean square fluctuations. The MDFF tools described are available to researchers through an easy-to-use and cost-effective cloud computing resource on Amazon Web Services.

Indexed as

Molecular Dynamics Simulationbeta-GalactosidaseCryoelectron MicroscopyImage Processing, Computer-AssistedTRPV Cation Channelsbeta-GalactosidaseTrpv1 protein, ratTRPV Cation ChannelsB-factorsbiophysicscloud computingcomputational biologycryoelectron microscopyflexible fittinghigh-resolutionhybrid methodsnonestructural biologysystems biology

Identifiers

PMID27383269
PMCPMC4990421

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LicenceCC BY
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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.