From general base to general acid catalysis in a sodium-specific DNAzyme by a guanine-to-adenine mutation
Bibliographic record
Abstract
Recently, a few Na+-specific RNA-cleaving DNAzymes were reported, where nucleobases are likely to play critical roles in catalysis. The NaA43 and NaH1 DNAzymes share the same 16-nt Na+-binding motif, but differ in one or two nucleotides in a small catalytic loop. Nevertheless, they display an opposite pH-dependency, implicating distinct catalytic mechanisms. In this work, rational mutation studies locate a catalytic adenine residue, A22, in NaH1, while previous studies found a guanine (G23) to be important for the catalysis of NaA43. Mutation with pKa-perturbed analogs, such as 2-aminopurine (∼3.8), 2,6-diaminopurine (∼5.6) and hypoxanthine (∼8.7) affected the overall reaction rate. Therefore, we propose that the N1 position of G23 (pKa ∼6.6) in NaA43 functions as a general base, while that of A22 (pKa ∼6.3) in NaH1 as a general acid. Further experiments with base analogs and a phosphorothioate-modified substrate suggest that the exocyclic amine in A22 and both of the non-bridging oxygens at the scissile phosphate are important for catalysis for NaH1. This is an interesting example where single point mutations can change the mechanism of cleavage from general base to general acid, and it can also explain this Na+-dependent DNAzyme scaffold being sensitive to a broad range of metal ions and molecules.
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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 | 0.000 |
| 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".