Functional characterization of the SOFA<i>delta</i>ribozyme
Bibliographic record
Abstract
Molecular engineering has led to the development of a novel target-dependent riboswitch that increases deltaribozyme fidelity. This delta ribozyme possesses a specific on/off adapter (SOFA) that switches the cleavage activity from off (a "safety lock") to on solely in the presence of the desired RNA substrate. In this report, we investigate the influence of both the structure and the sequence of each domain of the SOFA module. Analysis of the cleavage activity, using a large collection of substrates and SOFA-ribozyme mutants, together with RNase H probing provided several insights into the nature of the sequence and the optimal design of each domain of the SOFA module. For example, we determined that (1) the optimal size of the blocker sequence, which keeps the ribozyme off in the absence of the substrate, is 4 nucleotides (nt); (2) a single nucleotide difference between the substrate and the biosensor domain, which is responsible for the initial binding of the substrate that subsequently switches the SOFA-ribozyme on, is sufficient to cause non-recognition of the appropriate substrate; (3) the stabilizer, which joins the 5' and 3' ends of the SOFA-ribozyme, plays only a structural role; and (4) the optimal spacer sequence, which serves to separate the binding regions of the biosensor and catalytic domain of the ribozyme on the substrate, is from 1 to 5 nt long. Together, these data should facilitate the design of more efficient SOFA-ribozymes with significant potential for many applications in gene-inactivation systems.
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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) | 0.000 | 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) | 0.001 | 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".