PepNet: A Fully Convolutional Neural Network for De novo Peptide Sequencing
preprint · Research Square · 2022
| Date | 2022-02-09 |
| Type | preprint |
| Venue | Research Square |
| Publisher | Research Square |
| Contribution | algorithm |
| DOI | 10.21203/rs.3.rs-1341615/v1 |
| Citations (OpenAlex) | 78 |
Peer-reviewed version: Accurate de novo peptide sequencing using fully convolutional neural networks (2023-12-02, Nature Communications)
Abstract
The de novo peptide sequencing, which does not rely on a comprehensive target sequence database, provided us a way to identify novel peptides from tandem mass (MS/MS) spectra. However, current de novo sequencing algorithms suffer from lower accuracy and coverage, which hinders their applications in proteomics. In this paper, we present PepNet, a fully convolutional neural network (CNN) for high accuracy de novo peptide sequencing. It takes an MS/MS spectrum (represented as a high dimensional vector) as input, and outputs the optimal peptide sequence along with its confidence score. Our model was trained using a total of 30 million high-energy collisional dissociation (HCD) MS/MS spectra from multiple human peptide spectral libraries. The evaluation results show that PepNet significantly outperformed currently best-performing de novo sequencing algorithms (e.g. PointNovo and DeepNovo) at both peptide level accuracy and positional level accuracy. In addition, PepNet can sequence a large fraction of spectra that were not identified by database search engines, and thus could be used as a complementary tool of database search engines for peptide identification in proteomics.
Methods and tools
- PepNet: Temporal convolutional network
Data used
Cited by (6)
- De Novo Peptide Sequencing for Data-independent Acquisition (DIA) Using Deep Learning (2025) crossref
- Transformer-Based De Novo Peptide Sequencing for Data-Independent Acquisition Mass Spectrometry (2024) semanticscholar
- Transformer-Based De Novo Peptide Sequencing for Data-Independent Acquisition Mass Spectrometry (2023) crossref
- Algorithms for de-novo sequencing of peptides by tandem mass spectrometry: A review (2023) crossref
- Comprehensive evaluation of peptide de novo sequencing tools for monoclonal antibody assembly (2023) both
- The Current State-of-the-Art Identification of Unknown Proteins Using Mass Spectrometry Exemplified on De Novo Sequencing of a Venom Protease from Bothrops moojeni (2022) both