Abstract
Databases of multiple sequence alignments are a valuable aid to protein sequence classification and analysis. One of the main challenges when constructing such a database is to simultaneously satisfy the conflicting demands of completeness on the one hand and quality of alignment and domain definitions on the other. The latter properties are best dealt with by manual approaches, whereas completeness in practice is only amenable to automatic methods. Herein we present a database based on hidden Markov model profiles (HMMs), which combines high quality and completeness. Our database, Pfam, consists of parts A and B. Pfam-A is curated and contains well-characterized protein domain families with high quality alignments, which are maintained by using manually checked seed alignments and HMMs to find and align all members. Pfam-B contains sequence families that were generated automatically by applying the Domainer algorithm to cluster and align the remaining protein sequences after removal of Pfam-A domains. By using Pfam, a large number of previously unannotated proteins from the Caenorhabditis elegans genome project were classified. We have also identified many novel family memberships in known proteins, including new kazal, Fibronectin type III, and response regulator receiver domains. Pfam-A families have permanent accession numbers and form a library of HMMs available for searching and automatic annotation of new protein sequences.
Keywords
AnnotationProtein familyHidden Markov modelSequence alignmentSequence databaseProtein domainComputational biologyProtein sequencingSequence (biology)Computer scienceMultiple sequence alignmentCompleteness (order theory)DatabaseData miningBiologyBioinformaticsGeneticsPeptide sequenceArtificial intelligenceGeneMathematics
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Publication Info
- Year
- 1997
- Type
- article
- Volume
- 28
- Issue
- 3
- Pages
- 405-420
- Citations
- 1235
- Access
- Closed
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Cite This
Erik L. L. Sonnhammer,
Sean R. Eddy,
Richard Durbin
(1997).
Pfam: A comprehensive database of protein domain families based on seed alignments.
Proteins Structure Function and Bioinformatics
, 28
(3)
, 405-420.
https://doi.org/10.1002/(sici)1097-0134(199707)28:3<405::aid-prot10>3.0.co;2-l
Identifiers
- DOI
- 10.1002/(sici)1097-0134(199707)28:3<405::aid-prot10>3.0.co;2-l