Digital Quadrupole Isolation and Electron Capture Dissociation on an Extended Mass Range Q-TOF Provides Sequence and Structure Information on Proteins and Protein Complexes
Bibliographic record
Abstract
Electron capture dissociation (ECD) is now a well-established method for sequencing peptides and performing top-down analysis on proteins of less than 30 kDa, and there is growing interest in using this approach for studies of larger proteins and protein complexes. Although much progress on ECD has been made over the past few decades, establishing methods for obtaining informative spectra still poses a significant challenge. Here we describe how digital quadrupole (DigiQ) ion isolation can be used for the mass selection of single charge states of proteins and protein complexes prior to undergoing ECD and/or charge reduction. First, we demonstrate that the DigiQ can isolate single charge states of monomeric proteins such as ubiquitin (8.6 kDa) and charge states of large protein complexes such as pyruvate kinase (234 kDa) using a hybrid quadrupole-TOF-MS (Agilent extended m / z range 6545XT). Next, we demonstrate that fragment ions resulting from ECD can be utilized to provide information about the sequence and structure of the cytochrome c/heme complex and the ubiquitin monomer. Lastly, an especially interesting result for DigiQ isolation and electron capture (EC) was noted; namely, the 16+ charge state of the streptavidin/biotin complex reveals different electron capture patterns for the biotinylated proteoforms of streptavidin. This result is consistent with previous reports that apo streptavidin exists in multiple conformations and that biotin binding shifts the conformational dynamics of the complex (Quintyn, R. Chem. Biol. 2015, 22 (55), 583−592).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.004 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".