Evidence map›Paper›PMID 39480926›Full record

ArticleScience (New York, N.Y.)2024

Exploring structural diversity across the protein universe with The Encyclopedia of Domains.

Andy M Lau, Nicola Bordin, Shaun M Kandathil, Ian Sillitoe, Vaishali P Waman, Jude Wells, Christine A Orengo, David T Jones

Abstract read
In one paragraph

Article in Science (New York, N.Y.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 85 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
85citing papers in PubMed, 1 pooled it
–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

85 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. High-throughput analyses ofGut microbes · 2026
    Article
  3. Review
  4. Article
  5. Article
  6. Systematic discovery of circular permutations across the protein universe using CIRPIN.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  7. Article
  8. Investigating enzyme function by geometric matching of catalytic motifs.Protein science : a publication of the Protein Society · 2026
    Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Review
  18. Article
  19. Article
  20. Article

25 more citing papers are in PubMed but not listed here.

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

8 authors.

Andy M Lau *Department of Computer Science, University College London, London WC1E 6BT, UK.ORCID 0000-0003-0572-7826
Nicola Bordin *Institute of Structural and Molecular Biology, University College London, London WC1E 6BT, UK.ORCID 0000-0002-6568-9035
Shaun M KandathilDepartment of Computer Science, University College London, London WC1E 6BT, UK.ORCID 0000-0002-2671-2140
Ian SillitoeInstitute of Structural and Molecular Biology, University College London, London WC1E 6BT, UK.ORCID 0000-0003-1091-9144
Vaishali P WamanInstitute of Structural and Molecular Biology, University College London, London WC1E 6BT, UK.ORCID 0000-0001-5627-8827
Jude WellsInstitute of Structural and Molecular Biology, University College London, London WC1E 6BT, UK.ORCID 0000-0002-5358-2310
Christine A OrengoInstitute of Structural and Molecular Biology, University College London, London WC1E 6BT, UK.ORCID 0000-0002-7141-8936
David T JonesDepartment of Computer Science, University College London, London WC1E 6BT, UK.ORCID 0000-0001-8626-3765

Funding

Wellcome Trust
6 · The paper itself

Abstract

The AlphaFold Protein Structure Database (AFDB) contains more than 214 million predicted protein structures composed of domains, which are independently folding units found in multiple structural and functional contexts. Identifying domains can enable many functional and evolutionary analyses but has remained challenging because of the sheer scale of the data. Using deep learning methods, we have detected and classified every domain in the AFDB, producing The Encyclopedia of Domains. We detected nearly 365 million domains, over 100 million more than can be found by sequence methods, covering more than 1 million taxa. Reassuringly, 77% of the nonredundant domains are similar to known superfamilies, greatly expanding representation of their domain space. We uncovered more than 10,000 new structural interactions between superfamilies and thousands of new folds across the fold space continuum.

Indexed as

Databases, ProteinDeep LearningProtein DomainsProtein FoldingProteinsProteins

Identifiers

PMID39480926
PMCPMC7618865

What OpenQuestion holds

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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.