Updated MS²PIP web server supports cutting-edge proteomics applications

peer-reviewed · Nucleic Acids Research · 2023

peer-reviewed · Nucleic Acids Research · 2023. Arthur Declercq et al. Interest in the use of machine learning for peptide fragmentation spectrum prediction has been strongly on…
Date 2023-07-05
Type peer-reviewed
Venue Nucleic Acids Research
Publisher Oxford University Press (OUP)
Contribution adjacent
DOI 10.1093/nar/gkad335
Citations (OpenAlex) 33
Venue 2-year citedness 16.42

Abstract

Interest in the use of machine learning for peptide fragmentation spectrum prediction has been strongly on the rise over the past years, especially for applications in challenging proteomics identification workflows such as immunopeptidomics and the full-proteome identification of data independent acquisition spectra. Since its inception, the MS²PIP peptide spectrum predictor has been widely used for various downstream applications, mostly thanks to its accuracy, ease-of-use, and broad applicability. We here present a thoroughly updated version of the MS²PIP web server, which includes new and more performant prediction models for both tryptic- and non-tryptic peptides, for immunopeptides, and for CID-fragmented TMT-labeled peptides. Additionally, we have also added new functionality to greatly facilitate the generation of proteome-wide predicted spectral libraries, requiring only a FASTA protein file as input. These libraries also include retention time predictions from DeepLC. Moreover, we now provide pre-built and ready-to-download spectral libraries for various model organisms in multiple DIA-compatible spectral library formats. Besides upgrading the back-end models, the user experience on the MS²PIP web server is thus also greatly enhanced, extending its applicability to new domains, including immunopeptidomics and MS3-based TMT quantification experiments. MS²PIP is freely available at https://iomics.ugent.be/ms2pip/.

Authors

  1. Arthur Declercq · VIB
  2. Robbin Bouwmeester · Ghent University, VIB
  3. Cristina Chiva · Barcelona Institute of Science and Technology, University Pompeu Fabra
  4. Eduard Sabidó · Barcelona Institute of Science and Technology, Centre for Genomic Regulation, Universitat Pompeu Fabra, University Pompeu Fabra
  5. Aurélie Hirschler · University of Strasbourg
  6. Christine Carapito · University of Strasbourg
  7. Lennart Martens · Ghent University, Infrastructure Nationale de Protéomique (ProFI-FR2048), University of Strasbourg, VIB
  8. Sven Degroeve · VIB
  9. Ralf Gabriels · Ghent University, VIB

Methods and tools

  • MS2PIP: Predictor of MS/MS fragment-ion peak intensities, used to rescore search-engine and de novo sequencing results. Introduced in 2013 as a random-forest model; the 2019 web-server update added models for further fragmentation methods, instruments and labelling techniques, and the 2023 update added tryptic, non-tryptic, immunopeptide and TMT models and proteome-wide predicted spectral libraries with DeepLC retention times.

Cites (3)

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