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 identifications are gleaned from mass spectra. With highly variable sequence lengths, neuropeptides must be analyzed in their endogenous state. Further, neuropeptides share great homology within families, differing by as little as a single amino acid residue, complicating even routine analyses and necessitating optimized computational strategies for confident and accurate 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 reidentification. This work describes an algorithm capable of reporting more neuropeptide identifications at 1% false-discovery rate than alternative software in five Callinectes sapidus neuronal tissue types.

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

“…A schematic of the program workflow is shown in Figure . Final peptide identifications from mass spectra were analyzed using EndoGenius …”

“…MotifQuest computes a motif score that is designed to be sensitive to both short and long sequences, ensuring that motifs found in longer sequences are not excessively penalized or those in shorter peptides over rewarded. This initial score is part of a broader scoring framework that includes a weighted coverage-based motif assessment score, previously reported and now with the addition of a global motif database frequency normalized score, unique to MotifQuest.…”

“…These databases were also used to construct the final motif databases in MotifQuest for NPs and AMPs, available in Supporting Information, Files 5 and 6, respectively. Additionally, the NP motif database built in MotifQuest was compared with previously published, manually constructed motif database (Supporting Information, File 7).…”

“…The MotifQuest algorithm was initially evaluated using NP databases in EndoGenius, as documented previously . Following algorithm validation, the MotifQuest algorithm was used for AMP assessment.…”

“…Thus, cleavage patterns remain unknown and cannot be used to guide the computational search space. EndoGenius, an optimized database searching program for a class of endogenous peptides, neuropeptides (NPs), was released earlier this year and leverages amino acid motifs within its algorithm to confidently identify NPs. Incorporating motifs into its algorithm enables EndoGenius to surpass the performance of both open source and commercial database search tools, offering enhanced NP identification capabilities.…”