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Open Access Highly Accessed Database

PepBank - a database of peptides based on sequence text mining and public peptide data sources

Timur Shtatland1*, Daniel Guettler1, Misha Kossodo12, Misha Pivovarov1 and Ralph Weissleder1

Author Affiliations

1 Center for Molecular Imaging Research, Massachusetts General Hospital, Harvard Medical School, Bldg. 149, 13th Street, Room 5406, Charlestown, MA 02129, USA

2 Northern Essex Community College, 100 Elliott Street, Haverhill, MA 01830, USA

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BMC Bioinformatics 2007, 8:280  doi:10.1186/1471-2105-8-280

Published: 1 August 2007

Abstract

Background

Peptides are important molecules with diverse biological functions and biomedical uses. To date, there does not exist a single, searchable archive for peptide sequences or associated biological data. Rather, peptide sequences still have to be mined from abstracts and full-length articles, and/or obtained from the fragmented public sources.

Description

We have constructed a new database (PepBank), which at the time of writing contains a total of 19,792 individual peptide entries. The database has a web-based user interface with a simple, Google-like search function, advanced text search, and BLAST and Smith-Waterman search capabilities. The major source of peptide sequence data comes from text mining of MEDLINE abstracts. Another component of the database is the peptide sequence data from public sources (ASPD and UniProt). An additional, smaller part of the database is manually curated from sets of full text articles and text mining results. We show the utility of the database in different examples of affinity ligand discovery.

Conclusion

We have created and maintain a database of peptide sequences. The database has biological and medical applications, for example, to predict the binding partners of biologically interesting peptides, to develop peptide based therapeutic or diagnostic agents, or to predict molecular targets or binding specificities of peptides resulting from phage display selection. The database is freely available on http://pepbank.mgh.harvard.edu/ webcite, and the text mining source code (Peptide::Pubmed) is freely available above as well as on CPAN (http://www.cpan.org/ webcite).