Towards Understanding the Tandem Mass Spectra of Protonated Oligopeptides. 2: The Proline Effect in Collision-Induced Dissociation of Protonated Ala-Ala-Xxx-Pro-Ala (Xxx = Ala, Ser, Leu, Val, Phe, and Trp)
Bibliographic record
Abstract
The product ion spectra of proline-containing peptides are commonly dominated by y(n) ions generated by cleavage at the N-terminal side of proline residues. This proline effect is investigated in the current work by collision-induced dissociation (CID) of protonated Ala-Ala-Xxx-Pro-Ala (Xxx includes Ala, Ser, Leu, Val, Phe, and Trp) in an electrospray/quadrupole/time-of-flight (QqTOF) mass spectrometer and by quantum chemical calculations on protonated Ala-Ala-Ala-Pro-Ala. The CID spectra of all investigated peptides show a dominant y(2) ion (Pro-Ala sequence). Our computational results show that the proline effect mainly arises from the particularly low threshold energy for the amide bond cleavage N-terminal to the proline residue, and from the high proton affinity of the proline-containing C-terminal fragment produced by this cleavage. These theoretical results are qualitatively supported by the experimentally observed y(2)/b(3) abundance ratios for protonated Ala-Ala-Xxx-Pro-Ala (Xxx = Ala, Ser, Leu, Val, Phe, and Trp). In the post-cleavage phase of fragmentation the N-terminal oxazolone fragment with the Ala-Ala-Xxx sequence and Pro-Ala compete for the ionizing proton for these peptides. As the proton affinity of the oxazolone fragment increases, the y(2)/b(3) abundance ratio decreases.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".