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A Practical Guide to Phylogenetics for Nonexperts
Published on: February 5, 2014
PIR-ALN: a database of protein sequence alignments
G Y Srinivasarao1, L S Yeh, C R Marzec
1Protein Information Resource (PIR), National Biomedical Research Foundation, 3900 Reservoir Road NW, Washington, DC 20007, USA. Geetha@nbrf.georgetown.edu
Bioinformatics (Oxford, England)
|June 15, 1999
Summary
The Protein Information Resource (PIR) alignment database (PIR-ALN) Release 22.0 offers 3806 curated alignments for protein sequence analysis. This resource aids in classifying sequences, identifying conserved regions, and defining homology domains.
Area of Science:
- Bioinformatics
- Structural Biology
- Computational Biology
Background:
- The Protein Information Resource (PIR) curates annotated alignments to represent sequence interrelationships within the PIR-International Protein Sequence Database.
- Standardizing protein nomenclature, features, and keywords across families and superfamilies is crucial for biological classification.
- These alignments assist in identifying conserved regions and defining novel homology domains.
Purpose of the Study:
- To provide a comprehensive dataset of curated protein sequence alignments for various bioinformatics applications.
- To facilitate the standardization and dissemination of protein annotation through homology.
- To support the understanding of multidomain protein architecture.
Main Methods:
- The PIR-ALN database (Release 22.0) comprises 3806 curated alignments.
- Includes 1303 superfamily, 2131 family, and 372 homology domain alignments.
- Utilizes the ATLAS information retrieval system for browsing and querying alignments.
Main Results:
- PIR-ALN Release 22.0 contains 3806 alignments, suitable for developing patterns, testing profiles, and training models like Hidden Markov Models (HMMs).
- Identifies 529 alignments for developing patterns not found in PROSITE, Blocks, PRINTS, and Pfam.
- Supports annotation standardization for new protein members via homology.
Conclusions:
- The PIR-ALN database serves as a valuable resource for protein sequence analysis and annotation.
- Facilitates the discovery of conserved regions and the definition of new homology domains.
- Enables a deeper understanding of protein modular architecture and evolutionary relationships.
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