The GlycoPaSER prototype as a real-time N-glycopeptide identification tool based on the PaSER parallel computing platform

Real-time database searching allows for simpler and automated proteomics workflows as it eliminates technical bottlenecks in high throughput experiments. Most importantly, it enables results dependent acquisition (RDA) where search results can be used to guide data acquisition during acquisition. This is especially beneficial for glycoproteomics since the wide range of physicochemical properties of glycopeptides lead to a wide range of optimal acquisition parameters. We established here the GlycoPaSER prototype by extending the Parallel Search Engine in Real-time (PaSER) functionality for real-time glycopeptide identification from fragmentation spectra. Glycopeptide fragmentation spectra were decomposed into peptide- and glycan-moiety spectra using common N-glycan fragments. Each moiety was subsequently identified by a specialized algorithm running in real-time. GlycoPaSER can keep up with the rate of data acquisition for real-time analysis with similar performance to other glycoproteomics software and produces results that are in line with literature reference data. The GlycoPaSER prototype presented here provides the first proof-of-concept for real-time glycopeptide identification that unlocks future development of RDA technology to transcend data acquisition. ### Competing Interest Statement The appointment of Gad Armony was in part funded by Bruker Daltonics and co-authors Sven Brehmer, Tharan Srikumar, Lennard Pfennig, Dennis Trede, and Gary Kruppa are employees of Bruker Daltonics. Bruker Daltonics is the manufacturer of the mass spectrometry hardware and software platforms used in this work.