HyPep: An Open-Source Software for Identification and Discovery of Neuropeptides Using Sequence Homology Search

Neuropeptides are a class of endogenous peptides that
have key
regulatory roles in biochemical, physiological, and behavioral processes.
Mass spectrometry analyses of neuropeptides often rely on protein
informatics tools for database searching and peptide identification.
As neuropeptide databases are typically experimentally built and comprised
of short sequences with high sequence similarity to each other, we
developed a novel database searching tool, HyPep, which utilizes sequence
homology searching for peptide identification. HyPep aligns de novo sequenced peptides, generated through PEAKS software,
with neuropeptide database sequences and identifies neuropeptides
based on the alignment score. HyPep performance was optimized using
LC-MS/MS measurements of peptide extracts from various Callinectes
sapidus neuronal tissue types and compared with a commercial
database searching software, PEAKS DB. HyPep identified more neuropeptides
from each tissue type than PEAKS DB at 1% false discovery rate, and
the false match rate from both programs was 2%. In addition to identification,
this report describes how HyPep can aid in the discovery of novel
neuropeptides.