Evidence map›Paper›PMID 35900026›Full record

ArticleProtein science : a publication of the Protein Society2022

AlphaFold predicts the most complex protein knot and composite protein knots.

Maarten A Brems, Robert Runkel, Todd O Yeates, Peter Virnau

Abstract read
In one paragraph

Article in Protein science : a publication of the Protein Society, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

21 citing papers in PubMed.

  1. Review
  2. Tangled Tail of Mechanically Interlocked Peptides.Journal of the American Chemical Society · 2026
    Review
  3. Novel Knotted Solenoid fold with order-shifted coil arrangement leads to nontrivial 3Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Is There a Functional Role for the Knotted Topology in Protein UCH-L1?Journal of chemical information and modeling · 2024
    Article
  9. Theta-curves in proteins.Protein science : a publication of the Protein Society · 2024
    Article
  10. Article
  11. Article
  12. When Machine Learning Meets 2D Materials: A Review.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024
    Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. AlphaFold predicts novel human proteins with knots.Protein science : a publication of the Protein Society · 2023
    Article
  18. Application of artificial scaffold systems in microbial metabolic engineering.Frontiers in bioengineering and biotechnology · 2023
    Review
  19. Are there double knots in proteins? Prediction andFrontiers in molecular biosciences · 2023
    Article
  20. Article
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.

Maarten A BremsDepartment of Physics, Johannes Gutenberg University Mainz, Mainz, Germany.ORCID 0000-0002-0210-508X
Robert RunkelDepartment of Physics, Johannes Gutenberg University Mainz, Mainz, Germany.
Todd O YeatesUCLA-DOE Institute for Genomics and Proteomics, University of California Los Angeles, Los Angeles, California, USA.ORCID 0000-0001-5709-9839
Peter VirnauDepartment of Physics, Johannes Gutenberg University Mainz, Mainz, Germany.ORCID 0000-0003-2340-3884

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The computer artificial intelligence system AlphaFold has recently predicted previously unknown three-dimensional structures of thousands of proteins. Focusing on the subset with high-confidence scores, we algorithmically analyze these predictions for cases where the protein backbone exhibits rare topological complexity, that is, knotting. Amongst others, we discovered a 7

Indexed as

Artificial IntelligenceProtein FoldingModels, MolecularProtein ConformationProteinsProteinsAlphaFoldcomposite knotsprotein knotsprotein topology

Identifiers

PMID35900026
PMCPMC9278004

What OpenQuestion holds

Textmetadata
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.