Improvements to Casanovo, a Deep Learning De Novo Peptide Sequencer.

Journal: Journal of proteome research
Published Date: Dec 30, 2025

Abstract

Casanovo is a state-of-the-art deep learning model for de novo peptide sequencing from mass spectrometry and proteomics data. Here, we report on a series of enhancements to Casanovo, aimed at improving the interpretability of the scores assigned to predicted peptides, generalizing the software for use in database searches, speeding up training and prediction runtimes, and providing workflows and visualization tools to facilitate adoption of Casanovo and interpretation of its results. Our goal is to make Casanovo accurate and easy to use for applications such as metaproteomics, antibody sequencing, immunopeptidomics, and the discovery of novel peptide sequences in standard proteomics analyses. Casanovo is available as open source at https://github.com/Noble-Lab/casanovo.

Authors

  • Gwenneth Straub
    Department of Genome Sciences, University of Washington, Seattle, Washington 98195, United States.
  • Varun Ananth
    Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, Washington 98195, United States.
  • William E Fondrie
    Center for Vascular and Inflammatory Diseases, University of Maryland School of Medicine, Baltimore, MD, 21201, USA.
  • Chris Hsu
    Department of Genome Sciences, University of Washington, Seattle, WA, USA.
  • Daniela Klaproth-Andrade
    Computational Molecular Medicine, School of Computation, Information and Technology, Technical University of Munich, Garching, Germany.
  • Marina Pominova
    Department of Computer Science, University of Antwerp, 2020 Antwerp, Belgium.
  • Michael Riffle
    Department of Genome Sciences, University of Washington, Seattle, WA, USA.
  • Justin Sanders
    Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, WA, USA.
  • Bo Wen
  • Lingwen Xu
    Department of Electrical and Computer Engineering, University of Washington, Seattle, Washington 98195, United States.
  • Melih Yilmaz
    Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, Washington 98195, United States.
  • Michael J MacCoss
    Department of Genome Sciences, University of Washington, Seattle, WA, USA.
  • Sewoong Oh
    Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, WA, USA.
  • Wout Bittremieux
    Department of Computer Science, University of Antwerp, Antwerp, Belgium. [email protected].
  • William Stafford Noble
    1] Department of Computer Science and Engineering, University of Washington, 185 Stevens Way, Seattle, Washington 98195-2350, USA. [2] Department of Genome Sciences, University of Washington, 3720 15th Ave NE Seattle, Washington 98195-5065, USA.

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