Differentiation of Repeat Phosphopeptide Isomers Through Metal Interactions in FAIMS
Bibliographic record
Abstract
Phosphorylation regulates RNA polymerase II (RNAPII) to transcribe RNA from DNA but remains challenging to study by standard liquid chromatography followed by electrospray ionized-mass spectrometry (LC/ESI-MS) and fragmentation studies. To this end, we employed field asymmetric waveform ion mobility spectrometry (FAIMS) to explore metal-phosphorylation adduction to facilitate the analysis of variants. We analyzed phosphoisomers inspired by RNAPII C-terminal domain (CTD) heptads YSPTSPS, indistinguishable by collision-induced dissociation. The modulation of the carrier gas with solvent modifier provided partial differentiation of gas-phase metal-peptide adducts. During the compensation voltage scan with increasing dispersion voltage, alkali metal-doped phosphoheptad isomers showed selective elution. As per PM7 models, isomers may cluster/decluster with alkali ion/methanol with different bond energies due to the varied phosphosites. These conditions were successfully applicable to biologically significant modified tryptic diheptads. Translation of such methods might allow the detection of phosphosites in finding disease-causing mutations or aid targeted therapeutics development.
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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 | 0.000 |
| 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 | 0.001 |
| 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".