Revisiting the Reactivity of Uracil During Collision Induced Dissociation: Tautomerism and Charge-Directed Processes
Bibliographic record
Abstract
In our recent work towards the nontarget identification of products of nucleic acid (NA) damage in urine, we have found previous work describing the dissociation of NA bases not adequate to fully explain their observed reactivity. Here we revisit the gas-phase chemistry of protonated uracil (U) during collision induced dissociation (CID) using two modern tandem mass spectrometry techniques; quadrupole ion trap (QIT) and quadrupole time of flight (Q-TOF). We present detailed mechanistic proposals that account for all observed products of our experiments and from previous isotope labeling data, and that are supported by previous ion spectroscopy results and theoretical work. The diverse product-ions of U cannot be explained adequately by only considering the lowest energy form of protonated U as a precursor. The tautomers adopted by U during collisional excitation make it possible to relate the complex reactivity observed to reasonable mechanistic proposals and feasible product-ion structures for this small highly conjugated heterocycle. These reactions proceed from four different stable tautomers, which are excited to a specific activated precursor from which dissociation can occur via a charge-directed process through a favorable transition state to give a stabilized product. Understanding the chemistry of uracil at this level will facilitate the identification of new modified uracil derivatives in biological samples based solely on their reactivity during CID. Our integrated approach to describing ion dissociation is widely applicable to other NA bases and similar classes of biomolecules.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".