Evidence map›Paper›PMID 34288138›Full record

ArticleProteins2021

Evaluation of model refinement in CASP14.

Adam J Simpkin, Filomeno Sánchez Rodríguez, Shahram Mesdaghi, Andriy Kryshtafovych, Daniel J Rigden

Open access · hybridAbstract read
In one paragraph

Article in Proteins, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
1.9field-weighted citation impact, top 14% of its field
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

15 citing papers in PubMed, 26 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. More than just pattern recognition: Prediction of uncommon protein structure features by AI methods.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  5. Article
  6. Review
  7. Article
  8. Theoretical Studies of Cyanophycin Dipeptides as Inhibitors of Tyrosinases.International journal of molecular sciences · 2022
    Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Review
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

5 authors at 2 institutions in 2 countries.

Adam J SimpkinInstitute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, United Kingdom.
Filomeno Sánchez RodríguezInstitute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, United Kingdom.ORCID 0000-0002-6377-7269
Shahram MesdaghiInstitute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, United Kingdom.
Andriy KryshtafovychGenome Center, University of California, Davis, California, USA.ORCID 0000-0001-5066-7178
Daniel J RigdenInstitute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, United Kingdom.ORCID 0000-0002-7565-8937
University of Liverpool · GBUniversity of California, Davis · US

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
Biotechnology and Biological Sciences Research Council BB/S007105/1NIGMS NIH HHS R01 GM100482
6 · The paper itself

Abstract

We report here an assessment of the model refinement category of the 14th round of Critical Assessment of Structure Prediction (CASP14). As before, predictors submitted up to five ranked refinements, along with associated residue-level error estimates, for targets that had a wide range of starting quality. The ability of groups to accurately rank their submissions and to predict coordinate error varied widely. Overall, only four groups out-performed a "naïve predictor" corresponding to the resubmission of the starting model. Among the top groups, there are interesting differences of approach and in the spread of improvements seen: some methods are more conservative, others more adventurous. Some targets were "double-barreled" for which predictors were offered a high-quality AlphaFold 2 (AF2)-derived prediction alongside another of lower quality. The AF2-derived models were largely unimprovable, many of their apparent errors being found to reside at domain and, especially, crystal lattice contacts. Refinement is shown to have a mixed impact overall on structure-based function annotation methods to predict nucleic acid binding, spot catalytic sites, and dock protein structures.

Indexed as

Models, MolecularProteinsSoftwareComputational BiologyProtein ConformationSequence Analysis, ProteinProteinsCASPfunction predictionrefinementstructure prediction

Identifiers

PMID34288138
PMCPMC8616799
OpenAlexW3164905191

What OpenQuestion holds

Textmetadata
LicenceTDM
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.