Investigating the Role of Metal Ions in the Catalytic Mechanism of the Yeast RNA Triphosphatase
Bibliographic record
Abstract
The Saccharomyces cerevisiae RNA triphosphatase (Cet1) requires the presence of metal ion cofactors to catalyze its phosphohydrolase activity, the first step in the formation of the 5'-terminal cap structure of mRNAs. We have used endogenous tryptophan fluorescence studies to elucidate both the nature and the role(s) of the metal ions in the Cet1-mediated phosphohydrolase reaction. The association of Mg2+, Mn2+, and Co2+ ions with the enzyme resulted in a decrease in the intensity of the tryptophan emission spectrum. This decrease was then used to determine the apparent dissociation constants for these ions. Subsequent dual ligand titration experiments demonstrated that the metal ions bind to a common site, for which they compete. The kinetics of real-time metal ion binding to the Cet1 protein were also investigated, and the effects on RNA and nucleotide binding were evaluated. To provide additional insight into the relationship between Cet1 structure and metal ion binding, we correlated the effect of ion binding on protein structure using both circular dichroism and guanidium hydrochloride-induced denaturation as structural indicators. Our data indicate that binding of RNA, nucleotides, and metal ion cofactors does not lead to significant structural modifications of the Cet1 architecture. This suggests a model in which Cet1 possesses a preformed active site, and where major domain rearrangements are not required to form an active catalytic site. Finally, denaturation studies demonstrate that the metal ion cofactors can act by stabilizing the ground state binding of the phosphohydrolase substrate.
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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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".