A Silver-Specific DNAzyme with a New Silver Aptamer and Salt-Promoted Activity
Bibliographic record
Abstract
Most RNA-cleaving DNAzymes require a metal ion to interact with the scissile phosphate for activity. Therefore, few unmodified DNAzymes work with thiophilic metals because of their low affinity for phosphate. Recently, an Ag + -specific Ag10c DNAzyme was reported via in vitro selection. Herein, Ag10c is characterized to rationalize the role of the strongly thiophilic Ag + . Systematic mutation studies indicate that Ag10c is a highly conserved DNAzyme and its Ag + binding is unrelated to C-Ag + -C interaction. Its activity is enhanced by increasing Na + concentrations in buffer. At the same metal concentration, activity decreases in the following order: Li + > Na + > K + . Ag10c binds one Na + ion and two Ag + ions for catalysis. The pH–rate profile has a slope of ∼1, indicating a single deprotonation step. Phosphorothioate substitution at the scissile phosphate suggests that Na + interacts with the pro- R p oxygen of the phosphate, and dimethyl sulfate footprinting indicates that the DNAzyme loop is a silver aptamer binding two Ag + ions. Therefore, Ag + exerts its function allosterically, while the scissile phosphate interacts with Na +, Li +, Na +, or Mg 2+ . This work suggests the possibility of isolating thiophilic metal aptamers based on DNAzyme selection, and it also demonstrates a new Ag + aptamer.
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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) | 0.001 | 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 | 0.001 | 0.000 |
| 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".