Nature Methods· 2026Q1
Limitations of de novo peptide sequencing in resolving sequence ambiguity
- 1citations
- Q1SCImago
- 2026year
Short summary
Eight state-of-the-art de novo peptide sequencing models show considerable overlap in correct identifications but fail to resolve sequence ambiguity caused by incomplete spectra, with post-processing offering minimal improvements.
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Key points
- Eight state-of-the-art de novo peptide sequencing models were benchmarked on three proteomics datasets.
- Model performance showed considerable overlap in correct identifications, but none consistently resolved sequence ambiguity.
- Post-processing methods (iterative refinement, rescoring, reranking) yielded no or only modest improvements in identification accuracy.
- The main cause of sequencing errors was identified as limited fragment ion coverage, independent of the specific model used.
AI-generated from the title and abstract; the full text is not read.
Abstract
Abstract De novo peptide sequencing enables peptide identification from fragmentation spectra without relying on sequence databases. However, incomplete spectra create ambiguity, making unambiguous identification challenging. Recent deep learning advances have produced numerous de novo models that predict sequences and refine peptide-spectrum matches under such conditions. Yet, their relative strengths, weaknesses and ability to handle spectrum ambiguity remain unclear. Here we benchmark eight state-of-the-art models on three publicly available proteomics datasets, comparing performance using established metrics and quantifying inter-model agreement. We assess post-processing approaches, including iterative refinement, rescoring and reranking, for their ability to improve identification accuracy, and perform an error analysis to identify common mispredictions and their causes. Model performance varied, with considerable overlap of correct identifications. Post-processing yielded no or only modest improvements. Most sequencing errors were model-independent and driven by limited fragment ion coverage, a limitation also observed in database searches with large search spaces.
The authors' abstract, as published at the source. Nature Methods, 2026 · DOI ↗
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Field: Spectroscopy
SpectroscopyChemistry