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InterPro: the protein sequence classification resource in 2025

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Blum, Matthias, Andreeva, Antonina, Florentino, Laise Cavalcanti, Chuguransky, Sara Rocio, Grego, Tiago, Hobbs, Emma, Pinto, Beatriz Lazaro, Orr, Ailsa, Paysan-Lafosse, Typhaine, Ponamareva, Irina, Salazar, Gustavo A, Bordin, Nicola, Bork, Peer, Bridge, Alan, Colwell, Lucy, Gough, Julian, Haft, Daniel H, Letunic, Ivica, Llinares-López, Felipe, Marchler-Bauer, Aron, Meng-Papaxanthos, Laetitia, Mi, Huaiyu, Natale, Darren A, Orengo, Christine A, Pandurangan, Arun P, Piovesan, Damiano, Rivoire, Catherine, Sigrist, Christian J A, Thanki, Narmada, Thibaud-Nissen, Françoise, Thomas, Paul D, Tosatto, Silvio C E, Wu, Cathy H, Bateman, Alex·2025·Nucleic Acids Research
DOI 10.1093/nar/gkae1082
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Abstract

InterPro (https://www.ebi.ac.uk/interpro) is a freely accessible resource for the classification of protein sequences into families. It integrates predictive models, known as signatures, from multiple member databases to classify sequences into families and predict the presence of domains and significant sites. The InterPro database provides annotations for over 200 million sequences, ensuring extensive coverage of UniProtKB, the standard repository of protein sequences, and includes mappings to several other major resources, such as Gene Ontology (GO), Protein Data Bank in Europe (PDBe) and the AlphaFold Protein Structure Database. In this publication, we report on the status of InterPro (version 101.0), detailing new developments in the database, associated web interface and software. Notable updates include the increased integration of structures predicted by AlphaFold and the enhanced description of protein families using artificial intelligence. Over the past two years, more than 5000 new InterPro entries have been created. The InterPro website now offers access to 85 000 protein families and domains from its member databases and serves as a long-term archive for retired databases. InterPro data, software and tools are freely available.

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Metadata

Authors
Blum, M., Andreeva, A., Florentino, L. C., Chuguransky, S. R., Grego, T., Hobbs, E., Pinto, B. L., Orr, A., Paysan-Lafosse, T., Ponamareva, I., Salazar, G. A., Bordin, N., Bork, P., Bridge, A., Colwell, L., Gough, J., Haft, D. H., Letunic, I., Llinares-López, F., Marchler-Bauer, A., Meng-Papaxanthos, L., Mi, H., Natale, D. A., Orengo, C. A., Pandurangan, A. P., Piovesan, D., Rivoire, C., Sigrist, C. J. A., Thanki, N., Thibaud-Nissen, F., Thomas, P. D., Tosatto, S. C. E., Wu, C. H., & Bateman, A.
Venue
Nucleic Acids Research
Publisher
Oxford University Press (OUP)
Published
2024-11-20
Volume
53
Issue
D1
Pages
D444-D456
ISSN
  • 0305-1048 (ISSN-L)
  • 1362-4962
DOI
10.1093/nar/gkae1082
OpenAlex
W4404531735
Cited by
1,062
References
8
FWCI
123.39
Type
journal article
Language
en
Open access
gold
Licence
creativecommons.org/licenses/by/4.0/ (vor)
Funders
  • Wellcome Trust (221 320/Z/20/Z)
  • Biotechnology and Biological Sciences Research Council (BB/S020381/1, BB/X012492/1, BB/X018660/1)
  • European Molecular Biology Laboratory
  • Italiadomani-PNRR (IR0000010)
  • National Center for Biotechnology
  • National Library of Medicine
  • National Institutes of Health

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