Introducing π-HelixNovo for practical large-scale de novo peptide sequencing

peer-reviewed · Briefings in Bioinformatics · 2024

peer-reviewed · Briefings in Bioinformatics · 2024. Tingpeng Yang et al. De novo peptide sequencing is a promising approach for novel peptide discovery, highlighting the performance…
Date 2024-02-10
Type peer-reviewed
Venue Briefings in Bioinformatics
Publisher Briefings in Bioinformatics
Contribution algorithm
DOI 10.1093/bib/bbae021
Citations (OpenAlex) 34
Venue 2-year citedness 6.23

Preprint version: Introducing PandaNovo for practical large-scale de novo peptide sequencing (2023-07-15, bioRxiv)

Abstract

De novo peptide sequencing is a promising approach for novel peptide discovery, highlighting the performance improvements for the state-of-the-art models. The quality of mass spectra often varies due to unexpected missing of certain ions, presenting a significant challenge in de novo peptide sequencing. Here, we use a novel concept of complementary spectra to enhance ion information of the experimental spectrum and demonstrate it through conceptual and practical analyses. Afterward, we design suitable encoders to encode the experimental spectrum and the corresponding complementary spectrum and propose a de novo sequencing model \(\\pi\)-HelixNovo based on the Transformer architecture. We first demonstrated that \(\\pi\)-HelixNovo outperforms other state-of-the-art models using a series of comparative experiments. Then, we utilized \(\\pi\)-HelixNovo to de novo gut metaproteome peptides for the first time. The results show \(\\pi\)-HelixNovo increases the identification coverage and accuracy of gut metaproteome and enhances the taxonomic resolution of gut metaproteome. We finally trained a powerful \(\\pi\)-HelixNovo utilizing a larger training dataset, and as expected, \(\\pi\)-HelixNovo achieves unprecedented performance, even for peptide-spectrum matches with never-before-seen peptide sequences. We also use the powerful \(\\pi\)-HelixNovo to identify antibody peptides and multi-enzyme cleavage peptides, and \(\\pi\)-HelixNovo is highly robust in these applications. Our results demonstrate the effectivity of the complementary spectrum and take a significant step forward in de novo peptide sequencing.

Authors

  1. Tingpeng Yang · Peng Cheng Laboratory, Tsinghua Shenzhen International Graduate School, Tsinghua University
  2. Tianze Ling · Beijing Institute of Lifeomics, State Key Laboratory of Medical Proteomics, Tsinghua University
  3. Boyan Sun · Beijing Institute of Lifeomics, State Key Laboratory of Medical Proteomics
  4. Zhendong Liang · Peng Cheng Laboratory, Tsinghua University
  5. Fan Xu · Peng Cheng Laboratory
  6. Xiansong Huang · Peng Cheng Laboratory
  7. Linhai Xie · Beijing Institute of Lifeomics, International Academy of Phronesis Medicine (Guangdong), State Key Laboratory of Medical Proteomics
  8. Yonghong He · Peng Cheng Laboratory, Tsinghua University
  9. Leyuan Li · Beijing Institute of Lifeomics, State Key Laboratory of Medical Proteomics
  10. Fuchu He · Beijing Institute of Lifeomics, International Academy of Phronesis Medicine (Guangdong), National Center for Protein Sciences (Beijing), State Key Laboratory of Medical Proteomics
  11. Yu Wang · Peng Cheng Laboratory
  12. Cheng Chang · Beijing Institute of Lifeomics, International Academy of Phronesis Medicine (Guangdong), National Center for Protein Sciences (Beijing), State Key Laboratory of Medical Proteomics

Methods and tools

Cites (6)

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