Exploring structural diversity across the protein universe with The Encyclopedia of Domains
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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.
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Cites
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Chainsaw: protein domain segmentation with fully convolutional neural networks
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- Authors
- Lau, A. M., Bordin, N., Kandathil, S. M., Sillitoe, I., Waman, V. P., Wells, J., Orengo, C. A., & Jones, D. T.
- Affiliations
- University College London (GB)
- Institute of Structural and Molecular Biology (GB)
- Corresponding author
- Orengo, Christine A.
- Jones, David T.
- ORCID
- Venue
- Science
- Published
- 2024-11
- Volume
- 386
- Issue
- 6721
- Pages
- eadq4946-eadq4946
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- PMC
- PMC7618865
- OpenAlex
- W4403925091
- Cited by
- 140
- References
- 11
- Citations by year
- 2026: 71 · 2025: 61 · 2024: 8
- FWCI
- 19.06
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by
- Locations
- Science (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Padua Research Archive (University of Padova) (submittedVersion, cc-by)
- Funders
- Wellcome Trust (221327/Z/20/Z, 221327, 218529/Z/19/Z)
- Alan Turing Institute (218529/Z/19/Z)
- University College London
- Medical Research Council (HDR-23005)
- Biotechnology and Biological Sciences Research Council (BB/W008556/1, BB/W018802/1, BB/Y001117/1, BB/T019409/1)
- Health Data Research UK
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Machine Learning in Bioinformatics
- Physical Sciences › Materials Science › Materials Chemistry › Enzyme Structure and Function
- Keywords
- protein domains, domain detection, domain classification, protein superfamilies, protein fold, structural diversity, deep learning, protein structure prediction
- MeSH terms
- Protein Domains, Deep Learning, Proteins, Protein Folding, Databases, Protein
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