ECOD: Classification of domains in AFDB Swiss-Prot structure predictions
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Abstract
The development of highly accurate protein structure prediction algorithms has led to an explosion of structural data, transforming our understanding of protein structure-function relationships across diverse organisms. Domain classifications such as the Evolutionary Classification of Protein Domains (ECOD) have incorporated these computational predictions alongside experimental structures to create comprehensive resources for the research community. The AlphaFold Protein Structure Database (AFDB) plays a unique role, providing millions of predicted structures that ECOD has systematically classified for human proteins, small pathogens, and reference proteomes. Here, we extend this classification framework to the UniProtKB/Swiss-Prot dataset, applying the Domain Parser for AlphaFold Models (DPAM) pipeline to classify domains from over 542,000 Swiss-Prot protein structure predictions, resulting in more than 1,032,000 classified domains. These domains span 3,493 ECOD topologies and display high assignment confidence (mean DPAM probability: 0.992), with extensive taxonomic and functional diversity. Notably, over 100,000 domains lack existing Pfam mappings, reflecting the extended sensitivity of structure-based classification and identifying domain groups not yet captured by sequence-based profiles. These results significantly expand ECOD’s coverage into a functionally and taxonomically diverse protein space, anchoring high-confidence structure predictions in an evolutionary framework. By integrating Swiss-Prot predictions, we enhance the utility and interpretability of AlphaFold models and establish a foundation for future large-scale, functionally informed domain classifications.
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Computational Resources for Molecular Biology 2026.
Casadio, R., Lu, Z.-H., Mathews, D. H., & Sternberg, M. J. E. (2026) · Journal of Molecular Biology · doi:10.1016/j.jmb.2026.169898
- Authors
- Schaeffer, R. D., Zhang, J., Cong, Q., & Grishin, N. V.
- Affiliations
- The University of Texas Southwestern Medical Center (US)
- Corresponding author
- Schaeffer, R. Dustin
- Venue
- PLOS Computational Biology
- Publisher
- Public Library of Science (PLoS)
- Published
- 2026-03-30
- Volume
- 22
- Issue
- 3
- Pages
- e1013431
- ISSN
- 1553-734X (ISSN-L)
- 1553-7358
- OpenAlex
- W7143516912
- Cited by
- 2
- References
- 42
- Citations by year
- 2026: 2
- FWCI
- 4.13
- Type
- journal article
- Language
- en
- Update notices
- new_version (2026-04-03)
- Open access
- gold
- doi.org
- Licence
- Locations
- PLoS Computational Biology (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
- PubMed (publishedVersion)
- PubMed Central (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- National Institute of General Medical Sciences (GM147367)
- Division of Intramural Research, National Institute of Allergy and Infectious Diseases (1K99AI180984-01A1)
- National Science Foundation (2224128)
- Welch Foundation (I-1505, I-2095-20220331)
- NSF ACCESS (BIO250039, MED240004)
- Texas Advanced Computing Center (MCB24018, MCB23014)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Physical Sciences › Materials Science › Materials Chemistry › Enzyme Structure and Function
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Machine Learning in Bioinformatics
- Keywords
- protein domain classification, ECOD, Swiss-Prot, AlphaFold structure prediction, protein structure-function relationship, Pfam, protein evolution
- MeSH terms
- Protein Domains, Prediction Algorithms, Algorithms, Humans, Models, Molecular, Protein Conformation, Proteins, Evolution, Molecular, Computational Biology, Databases, Protein
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