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EndoGenius: Optimized neuropeptide identification from mass spectrometry datasets

ABSTRACT: Neuropeptides represent a unique class of signaling molecules that have garnered much attention but require special consideration when gleaning identifications from mass spectra. With highly variable sequence lengths, neuropeptides must by analyzed in their endogenous state. Further, neuropeptides share great homology within families, differing by as little as a single residue, complicating even routine analyses and necessitating optimized computational strategies for identifications. We present EndoGenius, a database searching strategy designed specifically for elucidating neuropeptide identifications from mass spectra by leveraging optimized peptide-spectrum matching approaches, an expansive motif database, and a novel scoring algorithm to achieve broader representation of the neuropeptidome and minimize re-identification. This work describes an algorithm capable of reporting more neuropeptide identifications at 1% false discovery rate than PEAKS DB in five Callinectes sapidus neuronal tissue types.

INSTRUMENT(S): Q Exactive HF

ORGANISM(S): Callinectes Sapidus (ncbitaxon:6763)

SUBMITTER: Lingjun Li

PROVIDER: MSV000092654 | MassIVE | Mon Aug 14 16:22:00 BST 2023

SECONDARY ACCESSION(S): PXD044576

REPOSITORIES: MassIVE

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