MotifQuest: An Automated Pipeline for Motif Database Creation to Improve Peptidomics Database Searching Programs

Endogenous peptides are an abundant and versatile class
of biomolecules
with vital roles pertinent to the functionality of the nervous, endocrine,
and immune systems and others. Mass spectrometry stands as a premier
technique for identifying endogenous peptides, yet the field still
faces challenges due to the lack of optimized computational resources
for reliable raw mass spectra analysis and interpretation. Current
database searching programs can exhibit discrepancies due to the unique
properties of endogenous peptides, which typically require specialized
search considerations. Herein, we present a high throughput, novel
scoring algorithm for the extraction and ranking of conserved amino
acid sequence motifs within any endogenous peptide database. Motifs
are conserved patterns across organisms, representing sequence moieties
crucial for biological functions, including maintenance of homeostasis.
MotifQuest, our novel motif database generation algorithm, is designed
to work in partnership with EndoGenius, a program optimized for database
searching of endogenous peptides and that is powered by a motif database
to capitalize on biological context to produce identifications. MotifQuest
aims to quickly develop motif databases without any prior knowledge,
a laborious task not possible with traditional sequence alignment
resources. In this work we illustrate the utility of MotifQuest to
expand EndoGenius’ identification utility to other endogenous
peptides by showcasing its ability to identify antimicrobial peptides.
Additionally, we discuss the potential utility of MotifQuest to parse
out motifs from a FASTA database file that can be further validated
as new peptide drug candidates.