Evidence map›Paper›PMID 35916020›Full record

ReviewFaraday discussions2022

Overview and applications of map and model validation tools in the CCP-EM software suite.

Agnel Praveen Joseph, Sony Malhotra, Tom Burnley, Martyn D Winn

Abstract readReview
In one paragraph

Review in Faraday discussions, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Agnel Praveen JosephScientific Computing Department, Science and Technology Facilities Council, Didcot OX11 0FA, UK. agnel-praveen.joseph@stfc.ac.uk.ORCID 0000-0002-0997-8422
Sony MalhotraScientific Computing Department, Science and Technology Facilities Council, Didcot OX11 0FA, UK. agnel-praveen.joseph@stfc.ac.uk.
Tom BurnleyScientific Computing Department, Science and Technology Facilities Council, Didcot OX11 0FA, UK. agnel-praveen.joseph@stfc.ac.uk.ORCID 0000-0001-5307-348X
Martyn D WinnScientific Computing Department, Science and Technology Facilities Council, Didcot OX11 0FA, UK. agnel-praveen.joseph@stfc.ac.uk.ORCID 0000-0003-0496-6796

Funding

Medical Research Council MR/N009614/1Medical Research Council MR/V000403/1Wellcome Trust 208398/Z/17/Z
6 · The paper itself

Abstract

Cryogenic electron microscopy (cryo-EM) has recently been established as a powerful technique for solving macromolecular structures. Although the best resolutions achievable are improving, a significant majority of data are still resolved at resolutions worse than 3 Å, where it is non-trivial to build or fit atomic models. The map reconstructions and atomic models derived from the maps are also prone to errors accumulated through the different stages of data processing. Here, we highlight the need to evaluate both model geometry and fit to data at different resolutions. Assessment of cryo-EM structures from SARS-CoV-2 highlights a bias towards optimising the model geometry to agree with the most common conformations, compared to the agreement with data. We present the CoVal web service which provides multiple validation metrics to reflect the quality of atomic models derived from cryo-EM data of structures from SARS-CoV-2. We demonstrate that further refinement can lead to improvement of the agreement with data without the loss of geometric quality. We also discuss the recent CCP-EM developments aimed at addressing some of the current shortcomings.

Indexed as

COVID-19SARS-CoV-2Cryoelectron MicroscopyHumansModels, MolecularProtein ConformationSoftware

Identifiers

PMID35916020
PMCPMC9642004

What OpenQuestion holds

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LicenceCC BY
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.