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Pfam data and new releases are available through InterPro

The Pfam website now serves as a static page with no data updates. All links below redirect to the closest alternative page in the InterPro website.

The Pfam database is a large collection of protein families, each represented by multiple sequence alignments and hidden Markov models (HMMs).

Proteins are generally composed of one or more functional regions, commonly termed domains. Different combinations of domains give rise to the diverse range of proteins found in nature. The identification of domains that occur within proteins can therefore provide insights into their function.

Pfam also generates higher-level groupings of related entries, known as clans. A clan is a collection of Pfam entries which are related by similarity of sequence, structure or profile-HMM.

The data presented for each entry is based on the UniProt Reference Proteomes but information on individual UniProtKB sequences can still be found by entering the protein accession. Pfam full alignments are available from searching a variety of databases, either to provide different accessions (e.g. all UniProt and NCBI GI) or different levels of redundancy.


You can find data in Pfam in various ways…

Analyze your protein sequence for Pfam matches

Paste your protein sequence here to find matching Pfam entries.

You will be redirected to InterPro sequence search. You can customize your query there.

View Pfam annotation and alignments

Enter an accession (e.g. PF02171) to see all data for that entry.

You can also browse through the list of all Pfam families.

Enter a clan accession (e.g. CL0005) to see information about that clan.

You can also browse through a list of clans.

View domain organisation of a protein sequence

Enter a sequence identifier (e.g. VAV_HUMAN) or accession (e.g. P15498).

You can browse proteins with Pfam domains.

Find the domains on a PDB structure

Enter the PDB identifier (e.g. 2abl) for the structure in the Protein DataBank.

Query Pfam by keyword

Search for keywords in text data in the Pfam database.


Citing Pfam

If you find Pfam useful, please consider citing the reference that describes this work:

Pfam: The protein families database in 2021: J. Mistry, S. Chuguransky, L. Williams, M. Qureshi, G.A. Salazar, E.L.L. Sonnhammer, S.C.E. Tosatto, L. Paladin, S. Raj, L.J. Richardson, R.D. Finn, A. Bateman, Nucleic Acids Research (2021) doi: 10.1093/nar/gkaa913

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