A DNAzyme requiring two different metal ions at two distinct sites
Bibliographic record
Abstract
Most previously reported RNA-cleaving DNAzymes require only a single divalent metal ion for catalysis. We recently reported a general trivalent lanthanide-dependent DNAzyme named Ce13d. This work shows that Ce13d requires both Na(+) and a trivalent lanthanide (e.g. Ce(3+)), simultaneously. This discovery is facilitated by the sequence similarity between Ce13d and a recently reported Na(+)-specific DNAzyme, NaA43. The Ce13d cleavage rate linearly depends on the concentration of both metal ions. Sensitized Tb(3+) luminescence and DMS footprinting experiments indicate that the guanines in the enzyme loop are important for Na(+)-binding. The Na(+) dissociation constants of Ce13d measured from the cleavage activity assay, Tb(3+) luminescence and DMS footprinting are 24.6, 16.3 and 47 mM, respectively. Mutation studies indicate that the role of Ce(3+) might be replaced by G23 in NaA43. Ce(3+) functions by stabilizing the transition state phosphorane, thus promoting cleavage. G23 competes favorably with low concentration Ce(3+) (below 1 μM). The G23-to-hypoxanthine mutation suggests the N1 position of the guanine as a hydrogen bond donor. Together, Ce13d has two distinct metal binding sites, each fulfilling a different role. DNAzymes can be quite sophisticated in utilizing metal ions for catalysis and molecular recognition, similar to protein metalloenzymes.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".