Using Gas-Phase Guest–Host Chemistry to Probe the Structures of <b><i>b</i></b> Ions of Peptides
Bibliographic record
Abstract
Middle-sized b(n) (n ≥ 5) fragments of protonated peptides undergo selective complex formation with ammonia under experimental conditions typically used to probe hydrogen-deuterium exchange in Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS). Other usual peptide fragments like y, a, a*, etc., and small b(n) (n ≤ 4) fragments do not form stable ammonia adducts. We propose that complex formation of b(n) ions with ammonia is characteristic to macrocyclic isomers of these fragments. Experiments on a protonated cyclic peptide and N-terminal acetylated peptides fully support this hypothesis; the protonated cyclic peptide does form ammonia adducts while linear b(n) ions of acetylated peptides do not undergo complexation. Density functional theory (DFT) calculations on the proton-bound dimers of all-Ala b(4), b(5), and b(7) ions and ammonia indicate that the ionizing proton initially located on the peptide fragment transfers to ammonia upon adduct formation. The ammonium ion is then solvated by N(+)-H…O H-bonds; this stabilization is much stronger for macrocyclic b(n) isomers due to the stable cage-like structure formed and entropy effects. The present study demonstrates that gas-phase guest-host chemistry can be used to selectively probe structural features (i.e., macrocyclic or linear) of fragments of protonated peptides. Stable ammonia adducts of b(9), b(9)-A, and b(9)-2A of A(8)YA, and b(13) of A(20)YVFL are observed indicating that even these large b-type ions form macrocyclic structures.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".