Investigating a New Generation of Ribozymes in Order to Target HCV
Bibliographic record
Abstract
For a long time nucleic acid-based approaches directed towards controlling the propagation of Hepatitis C Virus (HCV) have been considered to possess high potential. Towards this end, ribozymes (i.e. RNA enzymes) that specifically recognize and subsequently catalyze the cleavage of their RNA substrate present an attractive molecular tool. Here, the unique properties of a new generation of ribozymes are taken advantage of in order to develop an efficient and durable ribozyme-based technology with which to target HCV (+) RNA strands. These ribozymes resulted from the coupling of a specific on/off adaptor (SOFA) to the ribozyme domain derived from the Hepatitis Delta Virus (HDV). The former switches cleavage activity "on" solely in the presence of the desired RNA substrate, while the latter was the first catalytic RNA reported to function naturally in human cells, specifically in hepatocytes. In order to maximize the chances for success, a step-by-step approach was used for both the design and the selection of the ribozymes. This approach included the use of both bioinformatics and biochemical methods for the identification of the sites possessing the greatest potential for targeting, and the subsequent in vitro testing of the cleavage activities of the corresponding SOFA-HDV ribozymes. These efforts led to a significant improvement in the ribozymes' designs. The ability of the resulting SOFA-HDV ribozymes to inhibit HCV replication was further examined using a luciferase-based replicon. Although some of the ribozymes exhibited high levels of cleavage activity in vitro, none appears to be a potential long term inhibitor in cellulo. Analysis of recent discoveries in the cellular biology of HCV might explain this failure, as well as provide some ideas on the potential limits of using nucleic acid-based drugs to control the propagation of HCV. Finally, the above conclusions received support from experiments performed using a collection of SOFA-HDV ribozymes directed against HCV (-) strands.
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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) | 0.001 | 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".