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Database (Oxford). 2013 Apr 19;2013:bat023. doi: 10.1093/database/bat023. Print 2013.

The challenge of increasing Pfam coverage of the human proteome.

Author information

1
EMBL-European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK.

Abstract

It is a worthy goal to completely characterize all human proteins in terms of their domains. Here, using the Pfam database, we asked how far we have progressed in this endeavour. Ninety per cent of proteins in the human proteome matched at least one of 5494 manually curated Pfam-A families. In contrast, human residue coverage by Pfam-A families was <45%, with 9418 automatically generated Pfam-B families adding a further 10%. Even after excluding predicted signal peptide regions and short regions (<50 consecutive residues) unlikely to harbour new families, for ∼38% of the human protein residues, there was no information in Pfam about conservation and evolutionary relationship with other protein regions. This uncovered portion of the human proteome was found to be distributed over almost 25 000 distinct protein regions. Comparison with proteins in the UniProtKB database suggested that the human regions that exhibited similarity to thousands of other sequences were often either divergent elements or N- or C-terminal extensions of existing families. Thirty-four per cent of regions, on the other hand, matched fewer than 100 sequences in UniProtKB. Most of these did not appear to share any relationship with existing Pfam-A families, suggesting that thousands of new families would need to be generated to cover them. Also, these latter regions were particularly rich in amino acid compositional bias such as the one associated with intrinsic disorder. This could represent a significant obstacle toward their inclusion into new Pfam families. Based on these observations, a major focus for increasing Pfam coverage of the human proteome will be to improve the definition of existing families. New families will also be built, prioritizing those that have been experimentally functionally characterized. Database URL: http://pfam.sanger.ac.uk/.

PMID:
23603847
PMCID:
PMC3630804
DOI:
10.1093/database/bat023
[Indexed for MEDLINE]
Free PMC Article

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