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A Pattern Search Method for Discovering Conserved Motifs in Bioactive Peptide Families

Authors :
Feng Liu
Geert Wets
Liliane Schoofs
Geert Baggerman
Marleen Lindemans
Mahdavi, Mahmood A
Source :
Bioinformatics-Trends and Methodologies
Publication Year :
2011
Publisher :
InTech, 2011.

Abstract

Bioactive peptides play critical roles in regulating most biological processes in animals, and they have considerable biological, medical and industrial importance. Peptides belonging to the same family are often characterized by a typical short sequence motif (pattern) that is highly functionally preserved among the family members. In this chapter, we design a pattern search method to facilitate the detection of such conserved motifs. First, all known bioactive peptides annotated in Uniprot are collected and classified, and the program Pratt is used to search these unaligned peptide sequences in each family for conserved patterns. The obtained patterns are then refined by taking into account the information on amino acids at important functional sites collected from literature, and are further tested by scanning them against all the Uniprot proteins. The diagnostic power of the patterns is demonstrated by the fact that, while the false positive is kept to zero to ensure that the signatures are exclusive to peptides and their precursors, nearly 94% of all known peptide family members accommodate one or several of the identified patterns. In total, we brought to light 155 novel peptide patterns in addition to the 56 established ones in the PROSITE database. All the patterns represent 110 peptide families; among which 55 are not characterized by PROSITE and 12 are also dismissed by other existing motif databases, such as Pfam. Using the newly uncovered peptide patterns as a search tool, we predicted 95 hypothetical proteins as putative peptides or peptide precursors.

Details

Language :
English
Database :
OpenAIRE
Journal :
Bioinformatics-Trends and Methodologies
Accession number :
edsair.doi.dedup.....8b551490141d7981a1bb667b9f8c1f39