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Bioinformatic Analysis of Peptide Precursor Proteins
Author(s) -
BAGGERMAN G.,
LIU F,
WETS G.,
SCHOOFS L
Publication year - 2005
Publication title -
annals of the new york academy of sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.712
H-Index - 248
eISSN - 1749-6632
pISSN - 0077-8923
DOI - 10.1196/annals.1327.006
Subject(s) - peptide , drosophila melanogaster , computational biology , genome , signal peptide , biology , peptide sequence , peptide biosynthesis , neuropeptide , biochemistry , chemistry , gene , rna , receptor , ribosome
A bstract : Neuropeptides are among the most important signal molecules in animals. Traditional identification of peptide hormones through peptide purification is a tedious and time‐consuming process. With the advent of the genome sequencing projects, putative peptide precursor can be mined from the genome. However, because bioactive peptides are usually quite short in length and because the active core of a peptide is often limited to only a few amino acids, using the BLAST search engine to identify neuropeptide precursors in the genome is difficult and sometimes impossible. To overcome these shortcomings, we subject the entire set of all known Drosophila melanogaster peptide precursor sequences to motif‐finding algorithms in search of a motif that is common for all prepropeptides and that could be used in the search for new peptide precursors.