MSBooster: improving peptide identification rates using deep learning-based features.

Autor: Yang KL; Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA., Yu F; Department of Pathology, University of Michigan, Ann Arbor, MI, USA. yufe@umich.edu., Teo GC; Department of Pathology, University of Michigan, Ann Arbor, MI, USA., Li K; Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA., Demichev V; Department of Biochemistry, Charité Universitätsmedizin, Berlin, Germany.; Department of Biochemistry, University of Cambridge, Cambridge, UK., Ralser M; Department of Biochemistry, Charité Universitätsmedizin, Berlin, Germany.; Nuffield Department of Medicine, The Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK.; Max Planck Institute for Molecular Genetics, Berlin, Germany., Nesvizhskii AI; Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA. nesvi@med.umich.edu.; Department of Pathology, University of Michigan, Ann Arbor, MI, USA. nesvi@med.umich.edu.
Jazyk: angličtina
Zdroj: Nature communications [Nat Commun] 2023 Jul 27; Vol. 14 (1), pp. 4539. Date of Electronic Publication: 2023 Jul 27.
DOI: 10.1038/s41467-023-40129-9
Abstrakt: Peptide identification in liquid chromatography-tandem mass spectrometry (LC-MS/MS) experiments relies on computational algorithms for matching acquired MS/MS spectra against sequences of candidate peptides using database search tools, such as MSFragger. Here, we present a new tool, MSBooster, for rescoring peptide-to-spectrum matches using additional features incorporating deep learning-based predictions of peptide properties, such as LC retention time, ion mobility, and MS/MS spectra. We demonstrate the utility of MSBooster, in tandem with MSFragger and Percolator, in several different workflows, including nonspecific searches (immunopeptidomics), direct identification of peptides from data independent acquisition data, single-cell proteomics, and data generated on an ion mobility separation-enabled timsTOF MS platform. MSBooster is fast, robust, and fully integrated into the widely used FragPipe computational platform.
(© 2023. The Author(s).)
Databáze: MEDLINE
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