Methylating Peptides to Prevent Adduct Ion Formation Also Directs Cleavage in Collision-Induced Dissociation Mass Spectrometry
Bibliographic record
Abstract
We investigated the effect of N-terminal amino group and carboxyl group methylation on peptide analysis by electrospray mass spectrometry (ESI-MS) and tandem mass spectrometry (ESI-MS/MS). Permethylation of the N-terminal amino group and the carboxyl groups can reduce metal ion adducts but does not enhance sensitivity in electrospray as previously observed for matrix-assisted laser desorption/ionization (MALDI) mass spectrometry. N-terminal trimethylated peptides exhibit collision-induced dissociation (CID) tandem mass spectra that differ from their unmodified analogs; the results support the mobile proton hypothesis of peptide fragmentation. A permanent positive charge at the N-terminus leads to competition between permanent-charge directed processes and loss of the N-terminal trimethyl amino group. Carboxyl methylation has no effect on fragmentation behavior other than to shift the mass of fragments containing methylated carboxyl groups. Comparison of regular and tandem mass spectra of different methylated peptides allowed probing the location of incomplete methylation, the proton displaced by alkali metal ions and the purity of a mass-selected methylated peptide ion.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".