InterPro is a database of protein families, protein domains and functional sites in which identifiable features found in known proteins can be applied to new protein sequences in order to functionally characterise them.
The contents of InterPro consist of diagnostic signatures and the proteins that they significantly match. The signatures consist of models (simple types, such as regular expressions or more complex ones, such as Hidden Markov models) which describe protein families, domains or sites. Models are built from the amino acid sequences of known families or domains and they are subsequently used to search unknown sequences (such as those arising from novel genome sequencing) in order to classify them. Each of the member databases of InterPro contributes towards a different niche, from very high-level, structure-based classifications (SUPERFAMILY and CATH-Gene3D) through to quite specific sub-family classifications (PRINTS and PANTHER).
InterPro's intention is to provide a one-stop-shop for protein classification, where all the signatures produced by the different member databases are placed into entries within the InterPro database. Signatures which represent equivalent domains, sites or families are put into the same entry and entries can also be related to one another. Additional information such as a description, consistent names and Gene Ontology (GO) terms are associated with each entry, where possible.
InterPro contains three main entities: proteins, signatures (also referred to as "methods" or "models") and entries. The proteins in UniProtKB are also the central protein entities in InterPro. Information regarding which signatures significantly match these proteins are calculated as the sequences are released by UniProtKB and these results are made available to the public (see below). The matches of signatures to proteins are what determine how signatures are integrated together into InterPro entries: comparative overlap of matched protein sets and the location of the signatures' matches on the sequences are used as indicators of relatedness.
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