Enhancing De Novo Protein Sequencing through the C-Terminal Labeling Strategy: Resolving Isobaric Ambiguities by Electron-Transfer/Higher Energy Collision Dissociation (EThcD)
peer-reviewed · Analytical Chemistry · 2024
| Date | 2024-10-22 |
| Type | peer-reviewed |
| Venue | Analytical Chemistry |
| Publisher | American Chemical Society (ACS) |
| Contribution | adjacent |
| DOI | 10.1021/acs.analchem.4c03459 |
| Citations (OpenAlex) | 2 |
| Venue 2-year citedness | 7.10 |
Abstract
De novo protein sequencing via a bottom-up approach requires various proteases to produce overlapping peptides. However, peptides generated by proteases other than trypsin, LysC, and ArgC often yield C-terminal fragments with suboptimal ionization in positive mode mass spectrometry (MS). This study introduces a novel peptide labeling strategy that involves modifying peptides at the C-terminal and at the carboxyl groups of Aspartic and Glutamic acid with arginine methyl ester (R-met) to improve peptide fragmentation and resolve isobaric ambiguities encountered during sequencing. An amidation reaction is used with coupling reagents to conjugate R-met to the peptide’s C-terminal end, introducing a functional group that enhances the detectability of C-terminal peptide fragment ions by mass spectrometry. Subsequently, selecting a charge state of +2 or higher can facilitate optimal fragmentation of the derivatized peptides using electron-transfer/higher energy collision dissociation (EThcD), thereby generating essential w-ions to resolve common isobaric ambiguities. Demonstrating this strategy across diverse protein types, including albumin and antibodies and using different proteases for digestion, highlights the unique characteristics of combining the proposed amidation reaction with the specific proteases tested.
Methods and tools
- R-met C-terminal labeling de novo sequencing: Labels the peptide C-terminus and Asp/Glu carboxyl groups with arginine methyl ester so non-tryptic peptides fragment well, and EThcD then resolves isobaric ambiguities for bottom-up de novo protein sequencing.