Sequencing-Grade De novo Analysis of MS/MS Triplets (CID/HCD/ETD) From Overlapping Peptides
peer-reviewed · Journal of Proteome Research · 2013
peer-reviewed · Journal of Proteome Research · 2013. Adrian Guthals et al. Full-length de novo sequencing of unknown proteins remains a challenging open problem. Traditional methods…
| Date | 2013-06-07 |
| Type | peer-reviewed |
| Venue | Journal of Proteome Research |
| Publisher | American Chemical Society (ACS) |
| Contribution | algorithm |
| DOI | 10.1021/pr400173d |
| Citations (OpenAlex) | 72 |
| Venue 2-year citedness | 3.83 |
Abstract
Full-length de novo sequencing of unknown proteins remains a challenging open problem. Traditional methods that sequence spectra individually are limited by short peptide length, incomplete peptide fragmentation, and ambiguous de novo interpretations. We address these issues by determining consensus sequences for assembled tandem mass (MS/MS) spectra from overlapping peptides (e.g., by using multiple enzymatic digests). We have combined electron-transfer dissociation (ETD) with collision-induced dissociation (CID) and higher-energy collision-induced dissociation (HCD) fragmentation methods to boost interpretation of long, highly charged peptides and take advantage of corroborating b/y/c/z ions in CID/HCD/ETD. Using these strategies, we show that triplet CID/HCD/ETD MS/MS spectra from overlapping peptides yield de novo sequences of average length 70 AA and as long as 200 AA at up to 99% sequencing accuracy.
Methods and tools
- MS/MS Triplets: Sequencing-grade de novo analysis from overlapping CID/HCD/ETD MS/MS triplets.
Data used
- Upload for CID/HCD/ETD MetaSPS paper (JPR, 2013) (as deposited) · MSV000078436
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- Paired single residue‐transposed Lys‐N and Lys‐C digestions for label‐free identification of N‐terminal and C‐terminal MS/MS peptide product ions: ultrahigh resolution Fourier transform ion cyclotron resonance mass spectrometry and tandem mass spectrometry for peptide de novo sequencing (2015) crossref
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Cited in patents (2)
- US11573239B2 Methods and systems for de novo peptide sequencing using deep learning ↗ (Bioinformatics Solutions Inc., priority 2017-07-17, active)
- US11694769B2 Systems and methods for de novo peptide sequencing from data-independent acquisition using deep learning ↗ (Bioinformatics Solutions Inc., priority 2017-07-17, active)
Patents that list this paper among the literature they cite, whether the applicant or the examiner added it.