Examining the Influence of Phosphorylation on Peptide Ion Structure by Ion Mobility Spectrometry-Mass Spectrometry
Bibliographic record
Abstract
Ion mobility spectrometry-mass spectrometry (IMS-MS) techniques are used to study the general effects of phosphorylation on peptide structure. Cross sections for a library of 66 singly phosphorylated peptide ions from 33 pairs of positional isomers, and unmodified analogues were measured. Intrinsic size parameters (ISPs) derived from these measurements yield calculated collision cross sections for 85% of these phosphopeptide sequences that are within ±2.5% of experimental values. The average ISP for the phosphoryl group (0.64 ± 0.05) suggests that in general this moiety forms intramolecular interactions with the neighboring residues and peptide backbone, resulting in relatively compact structures. We assess the capability of ion mobility to separate positional isomers (i.e., peptide sequences that differ only in the location of the modification) and find that more than half of the isomeric pairs have >1% difference in collision cross section. Phosphorylation is also found to influence populations of structures that differ in the cis/trans orientation of Xaa-Pro peptide bonds. Several sequences with phosphorylated Ser or Thr residues located N-terminally adjacent to Pro residues show fewer conformations compared to the unmodified sequences.
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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 | 0.001 | 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".