Assessing Protein Sequence Database Suitability Using De Novo Sequencing
peer-reviewed · Molecular & Cellular Proteomics · 2020
peer-reviewed · Molecular & Cellular Proteomics · 2020. Richard S. Johnson et al. The analysis of samples from unsequenced and/or understudied species as well as samples where the proteome is…
| Date | 2020-01-01 |
| Type | peer-reviewed |
| Venue | Molecular & Cellular Proteomics |
| Publisher | Elsevier BV |
| Contribution | downstream-application |
| DOI | 10.1074/mcp.tir119.001752 |
| Citations (OpenAlex) | 38 |
| Venue 2-year citedness | 4.69 |
Abstract
The analysis of samples from unsequenced and/or understudied species as well as samples where the proteome is derived from multiple organisms poses two key questions. The first is whether the proteomic data obtained from an unusual sample type even contains peptide tandem mass spectra. The second question is whether an appropriate protein sequence database is available for proteomic searches. We describe the use of automated de novo sequencing for evaluating both the quality of a collection of tandem mass spectra and the suitability of a given protein sequence database for searching that data. Applications of this method include the proteome analysis of closely related species, metaproteomics, and proteomics of extinct organisms.
Methods and tools
- De novo database suitability assessment: Uses automated de novo sequencing to test whether a set of spectra holds peptide spectra at all and whether a protein database suits it, for unsequenced species, metaproteomes and extinct organisms.
Data used
- Assessing protein sequence database suitability using de novo sequencing (as deposited) · PXD015083
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Cited by (19)
- AbNovoBench: a resource and benchmarking platform for monoclonal antibody de novo sequencing (2026) both
- A procedure for controlling the false discovery rate of de novo peptide sequencing (2025) both
- Limitations of de novo sequencing in resolving sequence ambiguity (2025) both
- MARLOWE: An Untargeted Proteomics, Statistical Approach to Taxonomic Classification for Forensics (2025) crossref
- Metaproteomics Beyond Databases: Addressing the Challenges and Potentials of De Novo Sequencing (2025) both
- Sequence-to-sequence translation from mass spectra to peptides with a transformer model (2024) both
- NovoLign: metaproteomics by sequence alignment (2024) crossref
- NovoLign: metaproteomics by sequence alignment (2024) both
- Deep learning-driven fragment ion series classification enables highly precise and sensitive de novo peptide sequencing (2024) semanticscholar
- 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
- Deep learning-driven fragment ion series classification enables highly precise and sensitive de novo peptide sequencing (2023) crossref
- Sequence-to-sequence translation from mass spectra to peptides with a transformer model (2023) crossref
- Current state, existing challenges, and promising progress for de novo sequencing and assembly of monoclonal antibodies (2022) both
- Metaproteomic Characterization of Forensic Samples (2022) crossref
- Database-independent de novo metaproteomics of complex microbial communities (2021) crossref
- De novo sequencing of proteins by mass spectrometry (2020) semanticscholar
- Flying blind, or just flying under the radar? The underappreciated power of de novo methods of mass spectrometric peptide identification (2020) crossref
- Quantitative profiling of microbial communities by de novo metaproteomics (2020) both