InterPro: the protein sequence classification resource in 2025
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.
Authors
- Damiano Piovesan (ORCID: https://orcid.org/0000-0001-8210-2390)
- Matthias Blum (ORCID: https://orcid.org/0000-0001-5773-4724)
- Beatriz Lázaro (ORCID: https://orcid.org/0000-0001-6837-2941)
- Antonina Andreeva (ORCID: https://orcid.org/0000-0002-0450-0091)
- Darren A. Natale (ORCID: https://orcid.org/0000-0001-5809-9523)
- Typhaine Paysan‐Lafosse (ORCID: https://orcid.org/0000-0001-5663-0894)
- Narmada Thanki (ORCID: https://orcid.org/0000-0003-1181-2509)
- Paul D. Thomas (ORCID: https://orcid.org/0000-0002-9074-3507)
- Gustavo A Salazar (ORCID: https://orcid.org/0000-0001-9208-4966)
- Laetitia Meng-Papaxanthos (ORCID: https://orcid.org/0000-0002-0521-621X)
- Aron Marchler‐Bauer (ORCID: https://orcid.org/0000-0003-1516-0712)
- Daniel H. Haft (ORCID: https://orcid.org/0000-0001-8101-4938)
- Arun Prasad Pandurangan (ORCID: https://orcid.org/0000-0001-7168-7143)
- Nicola Bordin (ORCID: https://orcid.org/0000-0002-6568-9035)
- Françoise Thibaud‐Nissen (ORCID: https://orcid.org/0000-0003-4957-7807)
- Catherine Rivoire (ORCID: https://orcid.org/0000-0002-5979-8382)
- Lucy J. Colwell (ORCID: https://orcid.org/0000-0003-3148-0337)
- Christine Orengo (ORCID: https://orcid.org/0000-0002-7141-8936)
- Cathy H. Wu (ORCID: https://orcid.org/0000-0001-6379-8601)
- Christian J A Sigrist (ORCID: https://orcid.org/0000-0002-4348-0070)
- Sara Chuguransky (ORCID: https://orcid.org/0000-0002-0520-0736)
- Emma Hobbs (ORCID: https://orcid.org/0000-0002-8470-4739)
- Alex Bateman
- Tiago Grego (ORCID: https://orcid.org/0000-0002-7946-7062)
- Huaiyu Mi (ORCID: https://orcid.org/0000-0001-8721-202X)
- Julian Gough
- Silvio C. E. Tosatto (ORCID: https://orcid.org/0000-0003-4525-7793)
- Ivica Letunić (ORCID: https://orcid.org/0000-0003-3560-4288)
- Peer Bork (ORCID: https://orcid.org/0000-0002-2627-833X)
- Alan Bridge (ORCID: https://orcid.org/0000-0003-2148-9135)
- Irina Ponamareva (ORCID: https://orcid.org/0009-0009-6041-5869)
- Felipe Llinares-López
- A. Orr
- Laise Cavalcanti Florentino
Institutions
- University of Southern California (US)
- SIB Swiss Institute of Bioinformatics (CH)
- Google (United States) (US)
- National Institutes of Health (US)
- European Bioinformatics Institute (GB)
- University of Padua (IT)
- MRC Laboratory of Molecular Biology (GB)
- Georgetown University (US)
- National Academies of Sciences, Engineering, and Medicine (US)
- Georgetown University Medical Center (US)
- Google DeepMind (United Kingdom) (GB)
- Biobyte Solutions (Germany) (DE)
- National Center for Biotechnology Information (US)
- Institute of Biomembranes, Bioenergetics and Molecular Biotechnologies (IT)
- European Molecular Biology Laboratory (DE)
- National Research Council (IT)
- Institute of Structural and Molecular Biology (GB)
- University College London (GB)
- Medical Research Council (GB)
Publication Details
- Journal
- Nucleic Acids Research
- Published
- 2024-11-20
- DOI
- https://doi.org/10.1093/nar/gkae1082
- Citations
- 707
- Primary Topic
- Genomics and Phylogenetic Studies
- Type
- article
- Field-Weighted Citation Impact
- 165.08
Funders
- Wellcome Trust
- European Molecular Biology Laboratory
- UK Research and Innovation
- European Commission
- National Institutes of Health
- Directorate for Biological Sciences
- Biotechnology and Biological Sciences Research Council
- U.S. National Library of Medicine
- Centro Nacional de Biotecnología