An evaluation of the utility of <i>in vacuo</i> methylation for mass‐spectrometry‐based analyses of peptides
Bibliographic record
Abstract
In vacuo trimethylation of the N-terminus of a lyophilized peptide with methyl iodide was previously reported to enhance the peptide's signal in matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) and to suppress alkali adduct formation in electrospray ionization mass spectrometry (ESI-MS). Both the signal enhancement and alkali adduct suppression observed for methylated peptides are believed to be due to the permanent positive charge on the N-terminus of the peptide resulting from the formation of a quaternary ammonium moiety. The present work evaluates the general utility of the in vacuo methylation procedure for the MS analysis of peptides, and specifically addresses the issue of whether the methylation of nucleophilic sites other than the N-terminal amine affects the MALDI signal of modified peptides. This work establishes that, although certain side-chain modifications are inevitable using present reaction conditions, the derivatization leads to significant MALDI-MS signal improvement. The experimental results demonstrate that the N-terminal trimethylammonium derivatives of peptides exhibit MALDI signals comparable to or exceeding those of arginine-containing standards such as angiotensin I. The advantages and limitations of the in vacuo methylation procedure are discussed.
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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) | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".