Effect of the sarcosine residue on sequence scrambling in peptide b<sub>5</sub> ions
Bibliographic record
Abstract
The effect of N-methylation on sequence scrambling in the fragmentation of b5 ions has been investigated by studying a variety of peptides containing sarcosine (N-methylglycine). The product ion mass spectra for the b5 ions derived from Sar-A-A-A-Y-A and Sar-A-A-Y-A-A show only minor signals for non-direct sequence ions the major fragmentation reactions occurring from the unrearranged structures. This is in contrast to the b5 ions where the Sar residue is replaced by Ala and sequence scrambling occurs. The b5 ion derived from Y-Sar-A-A-A-A shows a product ion mass spectrum essentially identical to the spectrum of the b5 ion derived from Sar-A-A-A-Y-A, indicating that in the former case macrocyclization has occurred but the macrocyclic form shows a strong preference to reopen to put the Sar residue in the N-terminal position. Similar results were obtained in the comparison of b5 ions derived from A-Sar-A-A-Y-A and Sar-A-A-Y-A-A. The product ion mass spectra of the MH(+) ions of Y-Sar-A-A-A-A and A-Sar-A-A-Y-A show substantial signals for non-direct sequence ions indicating that fragmentation of the MH(+) ions channels extensively through the respective b5 ions and further fragmentation of these species.
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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 | 0.000 | 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".