Substrate specificity and kinetic framework of a DNAzyme with an expanded chemical repertoire: a putative RNaseA mimic that catalyzes RNA hydrolysis independent of a divalent metal cation
Bibliographic record
Abstract
This work addresses the binding, cleavage and dissociation rates for the substrate and products of a synthetic RNaseA mimic that was combinatorially selected using chemically modified nucleoside triphosphates. This trans-cleaving DNAzyme, 9(25)-11t, catalyzes sequence-specific ribophosphodiester hydrolysis in the total absence of a divalent metal cation, and in low ionic strength at pH 7.5 and in the presence of EDTA. It is the first such sequence capable of multiple turnover. 9(25)-11t consists of 31 bases, 18 of which form a catalytic domain containing 4 imidazole and 6 allylamino modified nucleotides. This sequence cleaves the 15 nt long substrate, S1, at one embedded ribocytosine at the eighth position to give a 5'-product terminating in a 2',3'-phosphodiester and a 3'-product terminating in a 5'-OH. Under single turnover conditions at 24 degrees C, 9(25)-11t displays a maximum first-order rate constant, k(cat), of 0.037 min(-1) and a catalytic efficiency, k(cat)/K(m), of 5.3 x 10(5) M(-1) min(-1). The measured value of k(cat) under catalyst excess conditions agrees with the value of k(cat) observed for steady-state multiple turnover, implying that slow product release is not rate limiting with respect to multiple turnover. The substrate specificity of 9(25)-11t was gauged in terms of k(cat) values for substrate sequence variants. Base substitutions on the scissile ribose and at the two bases immediately downstream decrease k(cat) values by a factor of 4 to 250, indicating that 9(25)-11t displays significant sequence specificity despite the lack of an apparent Watson-Crick base-pairing scheme for recognition.
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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 | 0.001 |
| 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".