The ionic environment determines ribozyme cleavage rate by modulation of nucleobase p <i>K</i> <sub>a</sub>
Bibliographic record
Abstract
Several small ribozymes employ general acid-base catalysis as a mechanism to enhance site-specific RNA cleavage, even though the functional groups on the ribonucleoside building blocks of RNA have pK (a) values far removed from physiological pH. The rate of the cleavage reaction is strongly affected by the identity of the metal cation present in the reaction solution; however, the mechanism(s) by which different cations contribute to rate enhancement has not been determined. Using the Neurospora VS ribozyme, we provide evidence that different cations confer particular shifts in the apparent pK (a) values of the catalytic nucleobases, which in turn determines the fraction of RNA in the protonation state competent for general acid-base catalysis at a given pH, which determines the observed rate of the cleavage reaction. Despite large differences in observed rates of cleavage in different cations, mathematical models of general acid-base catalysis indicate that k (1), the intrinsic rate of the bond-breaking step, is essentially constant irrespective of the identity of the cation(s) in the reaction solution. Thus, in contrast to models that invoke unique roles for metal ions in ribozyme chemical mechanisms, we find that most, and possibly all, of the ion-specific rate enhancement in the VS ribozyme can be explained solely by the effect of the ions on nucleobase pK (a). The inference that k (1) is essentially constant suggests a resolution of the problem of kinetic ambiguity in favor of a model in which the lower pK (a) is that of the general acid and the higher pK (a) is that of the general base.
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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 | 0.001 |
| 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 | 0.001 |
| 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".