Evidence map›Paper›PMID 41273079›Full record

ArticleNucleic acids research2026

AlphaFold Protein Structure Database 2025: a redesigned interface and updated structural coverage.

Damian Bertoni, Maxim Tsenkov, Paulyna Magana, Sreenath Nair, Ivanna Pidruchna, Marcelo Querino Lima Afonso, Adam Midlik, Urmila Paramval, Dare Lawal, Ahsan Tanweer and 19 more

Abstract read
In one paragraph

Article in Nucleic acids research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing 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

22 citing papers in PubMed.

  1. Article
  2. Review
  3. Diagnostics (Basel, Switzerland) · 2026
    Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Linear-time prediction of proteome-scale microbial protein interactions.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  11. Article
  12. Artificial Intelligence Powers Protein Functional Annotation.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Review
  13. Article
  14. Article
  15. Assessing the Performance of BioEmu in Understanding Protein Dynamics.International journal of molecular sciences · 2026
    Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. 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

29 authors.

Damian BertoniEuropean Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, CB10 1SD,United Kingdom.ORCID 0000-0001-8207-2486
Maxim TsenkovEuropean Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, CB10 1SD,United Kingdom.ORCID 0000-0002-4870-239X
Paulyna MaganaEuropean Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, CB10 1SD,United Kingdom.ORCID 0009-0004-1524-2966
Sreenath NairEuropean Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, CB10 1SD,United Kingdom.ORCID 0000-0002-6861-7627
Ivanna PidruchnaEuropean Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, CB10 1SD,United Kingdom.ORCID 0009-0001-9820-5287
Marcelo Querino Lima AfonsoEuropean Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, CB10 1SD,United Kingdom.ORCID 0000-0002-9966-8187
Adam MidlikEuropean Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, CB10 1SD,United Kingdom.ORCID 0000-0003-0455-2235
Urmila ParamvalEuropean Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, CB10 1SD,United Kingdom.ORCID 0009-0001-9221-4596
Dare LawalEuropean Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, CB10 1SD,United Kingdom.
Ahsan TanweerEuropean Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, CB10 1SD,United Kingdom.ORCID 0000-0002-4793-3700
Meera LastGoogle DeepMind, London, N1C 4DN,United Kingdom.
Risha PatelGoogle DeepMind, London, N1C 4DN,United Kingdom.ORCID 0009-0001-8014-8536
Agata LaydonGoogle DeepMind, London, N1C 4DN,United Kingdom.
Dariusz LaseckiGoogle DeepMind, London, N1C 4DN,United Kingdom.
Nick DietrichGoogle DeepMind, London, N1C 4DN,United Kingdom.
Hamish TomlinsonGoogle DeepMind, London, N1C 4DN,United Kingdom.
Augustin ŽídekGoogle DeepMind, London, N1C 4DN,United Kingdom.
Tim GreenGoogle DeepMind, London, N1C 4DN,United Kingdom.ORCID 0000-0002-3227-1505
Oleg KovalevskiyGoogle DeepMind, London, N1C 4DN,United Kingdom.ORCID 0000-0003-1106-3966
Andy LauDepartment of Computer Science, University College London, London, WC1E 6BT,United Kingdom.ORCID 0000-0003-0572-7826
Shaun KandathilDepartment of Computer Science, University College London, London, WC1E 6BT,United Kingdom.ORCID 0000-0002-2671-2140
Nicola BordinInstitute of Structural and Molecular Biology, University College London, London, England, WC1E 6BT,United Kingdom.ORCID 0000-0002-6568-9035
Ian SillitoeInstitute of Structural and Molecular Biology, University College London, London, England, WC1E 6BT,United Kingdom.ORCID 0000-0003-1091-9144
Milot MirditaSchool of Biological Sciences, Seoul National University, Seoul08826, Republic of Korea.ORCID 0000-0001-8637-6719
David JonesDepartment of Computer Science, University College London, London, WC1E 6BT,United Kingdom.ORCID 0000-0001-8626-3765
Christine OrengoInstitute of Structural and Molecular Biology, University College London, London, England, WC1E 6BT,United Kingdom.ORCID 0000-0002-7141-8936
Martin SteineggerSchool of Biological Sciences, Seoul National University, Seoul08826, Republic of Korea.ORCID 0000-0001-8781-9753
Jennifer R FlemingEuropean Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, CB10 1SD,United Kingdom.ORCID 0000-0003-4016-8740
Sameer VelankarEuropean Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, CB10 1SD,United Kingdom.ORCID 0000-0002-8439-5964

Funding

BBRSC 20-BBSRC/NSF-BIOBBRSC BB/T019409/1BBRSC BB/W008556/1BBRSC BB/W018802/1BBRSC BB/Y000455/1Creative-Pioneering Researchers Program and Novo Nordisk Foundation NNF24SA0092560European Molecular Biology LaboratoryNational Research Foundation RS-2020-NR049543National Research Foundation RS-2021-NR056571National Research Foundation RS-2021-NR061659National Research Foundation RS-2024-00396026National Research Foundation of Korea RS-2023-00250470Welcome Trust 221327/Z/20/ZWelcome Trust 310300/Z/24/Z
6 · The paper itself

Abstract

The AlphaFold Protein Structure Database (AFDB; https://alphafold.ebi.ac.uk), developed by EMBL-EBI and Google DeepMind, provides open access to hundreds of millions of high-accuracy protein structure predictions, transforming research in structural biology and the wider life sciences. Since its launch, AFDB has become a widely used bioinformatics resource, integrated into major databases, visualization platforms, and analysis pipelines. Here, we report the update of the database to align with the UniProt 2025_03 release, along with a comprehensive redesign of the entry page to enhance usability, accessibility, and structural interpretation. The new design integrates annotations directly with an interactive 3D viewer and introduces dedicated domains and summary tabs. Structural coverage has also been updated to include isoforms plus underlying multiple sequence alignments. Data are available through the website, FTP, Google Cloud, and updated APIs. Together, these advances reinforce AFDB as a sustainable resource for exploring protein sequence-structure relationships.

Indexed as

Databases, ProteinProtein ConformationProteinsComputational BiologyInternetModels, MolecularProtein FoldingSequence AlignmentSoftwareUser-Computer InterfaceProteins

Identifiers

PMID41273079
PMCPMC12807749

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.