Two Completely Different Mechanisms for Highly Specific Na<sup>+</sup> Recognition by DNAzymes
Bibliographic record
Abstract
Abstract Our view of the interaction between Na+ and nucleic acids was changed by a few recently discovered Na+‐specific RNA‐cleaving DNAzymes. In addition to nonspecific electrostatic interactions, highly specific recognition is also possible. Herein, two such DNAzymes, named EtNa and Ce13d, are compared to elucidate their mechanisms of Na+ binding. Mutation studies indicate that they have different sequence requirements. Phosphorothioate (PS) substitution at the scissile phosphate drops the activity of EtNa 140‐fold, and it cannot be rescued by thiophilic Cd2+ or Mn2+, whereas the activity of PS‐modified Ce13d can be rescued. Na+‐dependent activity assays indicate that two Na+ ions bind cooperatively in EtNa, and each Na+ likely interacts with a nonbridging oxygen atom in the scissile phosphate, whereas Ce13d binds only one Na+ ion in a well‐defined Na+ aptamer, and this Na+ ion does not directly interact with the scissile phosphate. Both DNAzymes display a normal pH–rate profile, with a single deprotonation reaction required for catalysis. For EtNa, Na+ fails to protect the conserved nucleotides from dimethyl sulfate attack, and no specific Na+ binding is detected by 2‐aminopurine fluorescence, both of which are different from those observed for Ce13d. This work suggests that EtNa binds Na+ mainly through its scissile phosphate without significant involvement of the nucleotides in the enzyme strand, whereas Ce13d has a well‐defined aptamer for Na+ binding. Therefore, DNA has at least two distinct ways to achieve highly selective Na+ binding.
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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) | 0.001 | 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 | 0.001 |
| 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".