Evidence map›Paper›PMID 40654171›Full record

ArticleActa crystallographica. Section D, Structural biology2025

Q-score as a reliability measure for protein, nucleic acid and small-molecule atomic coordinate models derived from 3DEM maps.

Grigore Pintilie, Chenghua Shao, Zhe Wang, Brian P Hudson, Justin W Flatt, Michael F Schmid, Kyle L Morris, Stephen K Burley, Wah Chiu

Abstract read
In one paragraph

Article in Acta crystallographica. Section D, Structural biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

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  13. DeepSSETracer 2.0: Improved Deep Learning Model Performance for Protein Secondary Structure Segmentation from Cryo-EM Maps.ACM-BCB ... ... : the ... ACM Conference on Bioinformatics, Computational Biology and Biomedicine. ACM Conference on Bioinformatics, Computational Biology and Biomedicine · 2025
    Article
4 · The record

Corrections and comments

  • Update of
    2025
5 · Who and what money

Authors and funding

9 authors.

Grigore PintilieDepartments of Bioengineering and of Microbiology and Immunology, Stanford University, Stanford, CA 94305, USA.
Chenghua ShaoResearch Collaboratory for Structural Bioinformatics Protein Data Bank, Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA.
Zhe WangEuropean Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton CB10 1SD, United Kingdom.ORCID 0000-0003-1119-1765
Brian P HudsonResearch Collaboratory for Structural Bioinformatics Protein Data Bank, Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA.
Justin W FlattResearch Collaboratory for Structural Bioinformatics Protein Data Bank, Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA.ORCID 0000-0001-5406-8156
Michael F SchmidRutgers Artificial Intelligence and Data Science (RAD) Collaboratory, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA.
Kyle L MorrisEuropean Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton CB10 1SD, United Kingdom.ORCID 0000-0002-1717-8134
Stephen K BurleyResearch Collaboratory for Structural Bioinformatics Protein Data Bank, Institute for Quantitative Biomedicine, Rutgers, The State University of New Jersey, Piscataway, NJ 08854, USA.
Wah ChiuDepartments of Bioengineering and of Microbiology and Immunology, Stanford University, Stanford, CA 94305, USA.ORCID 0000-0002-8910-3078

Funding

The Stanford-SLAC CryoEM CenterR24GM154186 · NIGMS · STANFORD UNIVERSITY · PI Wah Chiu, BRITT HEDMAN · 2024 to 2026
$19.3M
PDB Management by the Research Collaboratory for Structural BioinformaticsR01GM157729 · NIGMS · RUTGERS, THE STATE UNIV OF N.J. · PI STEPHEN K BURLEY · 2024 to 2026
$11.6M
Resource for Biocomputing Visualization and InformaticsP41GM103311 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI FERRIN, THOMAS E · 2012 to 2017
$8.2M
ChimeraX -- Next Generation Visualization and Analysis Software for Multiscale ModelingR01GM129325 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI FERRIN, THOMAS E · 2018 to 2025
$5.2M
National Institutes of Health, National Institute of General Medical Sciences P41GM103311National Institutes of Health, National Institute of General Medical Sciences R01GM129325National Institutes of Health, National Institute of General Medical Sciences R01GM157729National Institutes of Health, National Institute of General Medical Sciences R24GM154186National Science Foundation, Directorate for Biological Sciences DBI-2321666NIGMS NIH HHS P41 GM103311NIGMS NIH HHS R01 GM129325NIGMS NIH HHS R01 GM157729NIGMS NIH HHS R24 GM154186U.S. Department of Energy, Office of Science DE-SC0019749Wellcome TrustWellcome Trust 212977/Z/18/Z
6 · The paper itself

Abstract

Atomic coordinate models are important for the interpretation of 3D maps produced with cryoEM and cryoET (3D electron microscopy; 3DEM). In addition to visual inspection of such maps and models, quantitative metrics can inform about the reliability of the atomic coordinates, in particular how well the model is supported by the experimentally determined 3DEM map. A recently introduced metric, Q-score, was shown to correlate well with the reported resolution of the map for well fitted models. Here, we present new statistical analyses of Q-score based on its application to ∼10 000 maps and models archived in the EMDB (Electron Microscopy Data Bank) and PDB (Protein Data Bank). Further, we introduce two new metrics based on Q-score to represent each map and model relative to all entries in the EMDB and those with similar resolution. We explore through illustrative examples of proteins, nucleic acids and small molecules how Q-scores can indicate whether the atomic coordinates are well fitted to 3DEM maps and also whether some parts of a map may be poorly resolved due to factors such as molecular flexibility, radiation damage and/or conformational heterogeneity. These examples and statistical analyses provide a basis for how Q-scores can be interpreted effectively in order to evaluate 3DEM maps and atomic coordinate models prior to publication and archiving.

Indexed as

Cryoelectron MicroscopyModels, MolecularNucleic AcidsProteinsDatabases, ProteinProtein ConformationReproducibility of ResultsNucleic AcidsProteinsB factorscryoEMQ-scoresstructurevalidation

Identifiers

PMID40654171
PMCPMC12315582

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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.