XA-Novo: an accurate and high-throughput mass spectrometry-based de novo sequencing technology for monoclonal antibodies and antibody mixtures
peer-reviewed · Nature Communications · 2026
| Date | 2026-02-15 |
| Type | peer-reviewed |
| Venue | Nature Communications |
| Publisher | Springer Nature |
| Contribution | algorithm |
| DOI | 10.1038/s41467-026-70496-y |
| Citations (OpenAlex) | 0 |
| Venue 2-year citedness | 15.88 |
Preprint version: XA-Novo: an accurate and high-throughput mass spectrometry-based de novo sequencing technology for monoclonal antibodies and antibody mixtures (2025-02-07, Research Square)
Abstract
Elucidating antibody sequences by mass spectrometry-based de novo sequencing is essential but remains technically challenging. Here we present XA-Novo, an accurate and high-throughput de novo sequencing solution that integrates a single-pot multi-enzymatic gradient digestion method with a beam search-based assembler (Fusion) to reconstruct full-length antibody sequences directly from bottom-up mass spectrometry data. Benchmarking across well-characterized antibodies from multiple species demonstrates that XA-Novo outperforms commercial solutions in identification sensitivity, sequence completeness, and reconstruction accuracy. Furthermore, XA-Novo successfully reconstructs six immunotherapeutic antibodies with unknown sequences, and in vitro/vivo assays validate that these generated antibodies exhibit functionality equivalent to their commercial counterparts. Moreover, XA-Novo achieves over 99.54% accurate sequence coverage in distinguishing mixed COVID-19 neutralizing antibodies, exceeding the performance of current assemblers reported for single-antibody sequencing. Overall, XA-Novo establishes a reliable, scalable, and broadly applicable workflow for routine antibody sequencing, thereby accelerating both fundamental antibody research and therapeutic antibody development.
Methods and tools
- XA-Novo: NAR knowledge distillation
Cites (7)
- A multi-species benchmark for training and validating mass spectrometry proteomics machine learning models (2024) crossref
- Sequence-to-sequence translation from mass spectra to peptides with a transformer model (2024) both
- Comprehensive evaluation of peptide de novo sequencing tools for monoclonal antibody assembly (2023) crossref
- De novo mass spectrometry peptide sequencing with a transformer model (2022) crossref
- De novo peptide sequencing by deep learning (2017) both
- De Novo MS/MS Sequencing of Native Human Antibodies (2017) both
- Sequencing-Grade De novo Analysis of MS/MS Triplets (CID/HCD/ETD) From Overlapping Peptides (2013) both