EndoGenius: Enabling comprehensive identification and quantitation of endogenous peptides

Area of Science:

• Biochemistry
• Bioinformatics
• Analytical Chemistry

Background:

• Investigating endogenous peptides, particularly neuropeptides, via mass spectrometry faces significant bioinformatics challenges.
• These challenges include low *in vivo* abundance, susceptibility to degradation, and a vast search space for potential peptides.

Purpose of the Study:

• To present EndoGenius, an expanded open-source software package designed to optimize the search for endogenous peptides.
• To provide a comprehensive pipeline for peptide quantitation, spectral library building, motif extraction, and data-independent acquisition (DIA) workflows.

Main Methods:

• Development and expansion of the EndoGenius software package.
• Integration of a bioinformatics pipeline for various peptide analysis tasks.
• Application to mass spectrometry data for endogenous peptide discovery.

Main Results:

• EndoGenius offers an optimized approach to searching endogenous peptides, overcoming common bioinformatics bottlenecks.
• The software facilitates crucial downstream analyses such as quantitation and spectral library generation.
• It supports advanced workflows, including data-independent acquisition, for comprehensive peptide profiling.

Conclusions:

• EndoGenius provides a robust and versatile solution for the identification and analysis of endogenous peptides from mass spectrometry data.
• The software's expanded capabilities address key limitations in neuropeptide research.
• Its open-source nature promotes accessibility and further development in the field.