Evidence map›Paper›PMID 37994556›Full record

ArticleProteins2023

CASP15 cryo-EM protein and RNA targets: Refinement and analysis using experimental maps.

Thomas Mulvaney, Rachael C Kretsch, Luc Elliott, Joseph G Beton, Andriy Kryshtafovych, Daniel J Rigden, Rhiju Das, Maya Topf

Abstract read
In one paragraph

Article in Proteins, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Blind prediction of complex water and ion ensembles around RNA in CASP16.bioRxiv : the preprint server for biology · 2025
    Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Assessment of three-dimensional RNA structure prediction in CASP15.bioRxiv : the preprint server for biology · 2023
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Thomas MulvaneyCentre for Structural Systems Biology (CSSB), Leibniz-Institut für Virologie (LIV), Hamburg, Germany.ORCID 0000-0002-4373-6160
Rachael C KretschBiophysics Program, Stanford University School of Medicine, California, USA.ORCID 0000-0002-6935-518X
Luc ElliottInstitute of Systems, Molecular & Integrative Biology, The University of Liverpool, Liverpool, UK.ORCID 0009-0002-0181-4041
Joseph G BetonCentre for Structural Systems Biology (CSSB), Leibniz-Institut für Virologie (LIV), Hamburg, Germany.ORCID 0000-0001-7499-3867
Andriy KryshtafovychGenome Center, University of California, Davis, California, USA.ORCID 0000-0001-5066-7178
Daniel J RigdenInstitute of Systems, Molecular & Integrative Biology, The University of Liverpool, Liverpool, UK.ORCID 0000-0002-7565-8937
Rhiju DasBiophysics Program, Stanford University School of Medicine, California, USA.ORCID 0000-0001-7497-0972
Maya TopfCentre for Structural Systems Biology (CSSB), Leibniz-Institut für Virologie (LIV), Hamburg, Germany.ORCID 0000-0002-8185-1215

Funding

Prospective analysis to determine model accuracy performance and boundaries in the post-AlphaFold2 environmentR01GM100482 · NIGMS · UNIVERSITY OF CALIFORNIA AT DAVIS · PI FIDELIS, KRZYSZTOF A · 2012 to 2025
$11.1M
Next-generation computational/chemical methods for complex RNA structuresR35GM122579 · NIGMS · STANFORD UNIVERSITY · PI Rhiju Das · 2017 to 2026
$7.2M
Howard Hughes Medical InstituteNIGMS NIH HHS R01 GM100482NIGMS NIH HHS R35 GM122579
6 · The paper itself

Abstract

CASP assessments primarily rely on comparing predicted coordinates with experimental reference structures. However, experimental structures by their nature are only models themselves-their construction involves a certain degree of subjectivity in interpreting density maps and translating them to atomic coordinates. Here, we directly utilized density maps to evaluate the predictions by employing a method for ranking the quality of protein chain predictions based on their fit into the experimental density. The fit-based ranking was found to correlate well with the CASP assessment scores. Overall, the evaluation against the density map indicated that the models are of high accuracy, and occasionally even better than the reference structure in some regions of the model. Local assessment of predicted side chains in a 1.52 Å resolution map showed that side-chains are sometimes poorly positioned. Additionally, the top 118 predictions associated with 9 protein target reference structures were selected for automated refinement, in addition to the top 40 predictions for 11 RNA targets. For both proteins and RNA, the refinement of CASP15 predictions resulted in structures that are close to the reference target structure. This refinement was successful despite large conformational changes often being required, showing that predictions from CASP-assessed methods could serve as a good starting point for building atomic models in cryo-EM maps for both proteins and RNA. Loop modeling continued to pose a challenge for predictors, and together with the lack of consensus amongst models in these regions suggests that modeling, in combination with model-fit to the density, holds the potential for identifying more flexible regions within the structure.

Indexed as

ProteinsCryoelectron MicroscopyModels, MolecularProtein ConformationProteins3D structure predictionAlphaFoldCASPCASP15cryoEMprotein structurerefinementRNARNA structure

Identifiers

PMID37994556
PMCPMC10697286

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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.