Evidence map›Paper›PMID 26988127›Full record

ArticleMethods (San Diego, Calif.)2016

Refinement of atomic models in high resolution EM reconstructions using Flex-EM and local assessment.

Agnel Praveen Joseph, Sony Malhotra, Tom Burnley, Chris Wood, Daniel K Clare, Martyn Winn, Maya Topf

Abstract read
In one paragraph

Article in Methods (San Diego, Calif.), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers.

0numbers the graph read from it
0cells of the map it votes in
62citing 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

62 citing papers in PubMed.

  1. Article
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  12. Using deep-learning predictions of inter-residue distances for model validation.Acta crystallographica. Section D, Structural biology · 2022
    Article
  13. Review
  14. Article
  15. Article
  16. Article
  17. Sequence-assignment validation in cryo-EM models with checkMySequence.Acta crystallographica. Section D, Structural biology · 2022
    Article
  18. Validation analysis of EMDB entries.Acta crystallographica. Section D, Structural biology · 2022
    Article
  19. Snapshots of actin and tubulin folding inside the TRiC chaperonin.Nature structural & molecular biology · 2022
    Article
  20. Atomic model validation using the CCP-EM software suite.Acta crystallographica. Section D, Structural biology · 2022
    Article

2 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

7 authors.

Agnel Praveen JosephInstitute of Structural and Molecular Biology, Department of Biological Sciences, Birkbeck College, University of London, Malet Street, London WC1E 7HX, United Kingdom.
Sony MalhotraScientific Computing Department, Science and Technology Facilities Council, Research Complex at Harwell, Didcot OX11 0FA, United Kingdom.
Tom BurnleyScientific Computing Department, Science and Technology Facilities Council, Research Complex at Harwell, Didcot OX11 0FA, United Kingdom.
Chris WoodScientific Computing Department, Science and Technology Facilities Council, Research Complex at Harwell, Didcot OX11 0FA, United Kingdom.
Daniel K ClareElectron Bio-Imaging Centre (eBIC), Diamond Light Source, Harwell Science & Innovation Campus, OX11 0DE, United Kingdom.
Martyn WinnScientific Computing Department, Science and Technology Facilities Council, Research Complex at Harwell, Didcot OX11 0FA, United Kingdom. Electronic address: martyn.winn@stfc.ac.uk.
Maya TopfInstitute of Structural and Molecular Biology, Department of Biological Sciences, Birkbeck College, University of London, Malet Street, London WC1E 7HX, United Kingdom. Electronic address: m.topf@mail.cryst.bbk.ac.uk.

Funding

Medical Research Council G0600084Medical Research Council MR/J000825/1Medical Research Council MR/M019292/1Medical Research Council MR/N009614/1
6 · The paper itself

Abstract

As the resolutions of Three Dimensional Electron Microscopic reconstructions of biological macromolecules are being improved, there is a need for better fitting and refinement methods at high resolutions and robust approaches for model assessment. Flex-EM/MODELLER has been used for flexible fitting of atomic models in intermediate-to-low resolution density maps of different biological systems. Here, we demonstrate the suitability of the method to successfully refine structures at higher resolutions (2.5-4.5Å) using both simulated and experimental data, including a newly processed map of Apo-GroEL. A hierarchical refinement protocol was adopted where the rigid body definitions are relaxed and atom displacement steps are reduced progressively at successive stages of refinement. For the assessment of local fit, we used the SMOC (segment-based Manders' overlap coefficient) score, while the model quality was checked using the Qmean score. Comparison of SMOC profiles at different stages of refinement helped in detecting regions that are poorly fitted. We also show how initial model errors can have significant impact on the goodness-of-fit. Finally, we discuss the implementation of Flex-EM in the CCP-EM software suite.

Indexed as

Imaging, Three-DimensionalSoftwareAdenylate KinaseChaperonin 60Cryoelectron MicroscopyEscherichia coli ProteinsEukaryotic Initiation FactorsModels, MolecularRibosome Subunits, Large, EukaryoticAdenylate KinaseChaperonin 60Escherichia coli ProteinsEukaryotic Initiation Factors3D-EMDensity fittingFlexible fittingModel validationProtein structure modellingStructure refinement

Identifiers

PMID26988127
PMCPMC4854230

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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.