Nucleic Acid-Based Gene-Silencing Molecules as Potential Antiviral Therapeutics
Bibliographic record
Abstract
Graphical Abstract: Nucleic-acid-based gene silencing molecules, including antisense oligodeoxyribonucleotides, ribozymes, DNAzymes and small interfering RNA, have been discussed on their mechanisms of action and potential applications in antiviral therapy. The sequencing of many human viral genomes and the elucidation of molecular mechanisms of viral replication as well as signal transduction pathways involved in viral pathogenesis have provided unprecedented opportunities for the development of new therapeutics. One type of the most promising molecules in drug development is the nucleic-acid-based therapeutics, including antisense oligodeoxyribonucleotides (AODN), ribozymes, DNAzyme and small interfering RNA (siRNA). AODNs have shown great potential as powerful tools in gene functional studies, as well as highly selective therapeutic agents in drug development. Although several problems have been encountered such as toxicity, non-stability, side effects, and low intracellular uptake, there has been at least one antisense drug approved for the treatment of cytomegalovirus retinitis, and over twenty other antisense candidates are undergoing clinical trials. Ribozymes and DNAzymes, by binding to substrate RNA through base pairing, offer sequence-specific cleavage of disease-associated RNA transcripts and show great potential for development of novel antiviral agents. RNA interference has emerged as a novel tool that offers great hope and promise to study gene functions and to develop therapeutics against viral infection. This powerful antiviral effect is mediated by siRNAs that target the viral mRNA for degradation by cellular enzymes. The potential of siRNA to treat or prevent diseases in clinical settings remains to be proven. This article first overviews current nucleic acid-based approaches in gene silencing, and then focuses on the potential applications in antiviral therapy including our own data on coxsackieviral infection. Keywords: antisense odn, ribozymes, dnazyme, small interfering rna, antiviral agents, coxsackievirus b
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.041 | 0.007 |
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".