Bidirectional de novo peptide sequencing using a transformer model

peer-reviewed · PLOS Computational Biology · 2024

peer-reviewed · PLOS Computational Biology · 2024. Sangjeong Lee et al. In proteomics, a crucial aspect is to identify peptide sequences. De novo sequencing methods have been widely…

Date	2024-02-28
Type	peer-reviewed
Venue	PLOS Computational Biology
Publisher	PLoS Computational Biology
Contribution	algorithm
DOI	10.1371/journal.pcbi.1011892
Citations (OpenAlex)	23
Venue 2-year citedness	4.27

Abstract

In proteomics, a crucial aspect is to identify peptide sequences. De novo sequencing methods have been widely employed to identify peptide sequences, and numerous tools have been proposed over the past two decades. Recently, deep learning approaches have been introduced for de novo sequencing. Previous methods focused on encoding tandem mass spectra and predicting peptide sequences from the first amino acid onwards. However, when predicting peptides using tandem mass spectra, the peptide sequence can be predicted not only from the first amino acid but also from the last amino acid due to the coexistence of b-ion (or a- or c-ion) and y-ion (or x- or z-ion) fragments in the tandem mass spectra. Therefore, it is essential to predict peptide sequences bidirectionally. Our approach, called NovoB, utilizes a Transformer model to predict peptide sequences bidirectionally, starting with both the first and last amino acids. In comparison to Casanovo, our method achieved an improvement of the average peptide-level accuracy rate of approximately 9.8% across all species.

Authors

Methods and tools

NovoB: Bidirectional decoding

Data used

BoxCar acquisition method enables single shot proteomics at a depth of 10,000 proteins in 100 minutes (as deposited) · PXD006109
NFYB-1 regulates mitochondrial function and longevity via lysosomal prosaposin (as deposited) · PXD013233
Nine-species benchmark (version not stated)
NovoB DataSets & Trained Models (as deposited) · 10.5281/zenodo.10258874
Predictive signatures of 19 antibiotics-induced Escherichia coli proteomes (as deposited) · PXD016001
The beta subunit of nascent polypeptide associated complex plays a role in flowers and siliques development of Arabidops (as deposited) · PXD016315

Cites (11)

Mitigating the missing-fragmentation problem in de novo peptide sequencing with a two-stage graph-based deep learning model (2023) both
De novo peptide sequencing with InstaNovo: Accurate, database-free peptide identification for large scale proteomics experiments (2023) both
BiATNovo: A Self-Attention based Bidirectional Peptide Sequencing Method (2023) crossref
De novo mass spectrometry peptide sequencing with a transformer model (2022) both
Computationally instrument-resolution-independent de novo peptide sequencing for high-resolution devices (2021) both
De novo peptide sequencing by deep learning (2017) both
Novor: Real-Time Peptide de Novo Sequencing Software (2015) both
pNovo: De novo Peptide Sequencing and Identification Using HCD Spectra (2010) both
PepNovo: de novo peptide sequencing via probabilistic network modeling (2005) both
PEAKS: powerful software for peptide de novo sequencing by tandem mass spectrometry (2003) crossref
De novo peptide sequencing via tandem mass spectrometry (1999) both

Cited by (17)

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