Efficient Peptide Identification for Immunopeptidomics DDA data

Exploring the immunopeptidome improves our ability to understand diseases and assess cellular health. Mass spectrometry-based peptidomics provides an unbiased workflow for systematically identifying, quantifying, and characterizing thousands of peptides, even from minimal sample material. However, unspecific searches are particularly challenging due to the large search spaces, making processing more complex and computationally demanding. Additionally, non-tryptic peptides have different peptide properties than tryptic ones, further complicating analysis. This is why robust, scalable, and highly efficient software is essential for handling these datasets efficiently. To address these obstacles, we refined our search engine Pulsar and introduced Kuiper, a novel search engine. This makes SpectroMine™ both faster and more sensitive to non-tryptic data. In this study, we show how the newest version of SpectroMine increases identifications, reduces processing time, while providing biological meaningful information from publicly available immunopeptidomics samples.