The Broad Spectrum Antiviral Nucleoside Ribavirin as a Substrate for a Viral RNA Capping Enzyme
Bibliographic record
Abstract
The broad spectrum antiviral nucleoside ribavirin displays activity against a variety of RNA and DNA viruses. A number of possible mechanisms have been proposed during the past 30 years to account for the antiviral activity of ribavirin, including the possibility that ribavirin might have a negative effect on the synthesis of the RNA cap structure of viral RNA transcripts. In the present study, we investigated the possibility that ribavirin can directly serve as a substrate for the vaccinia virus RNA capping enzyme. We demonstrate that ribavirin triphosphate can be used as a substrate by the capping enzyme and can form a covalent ribavirin monophosphate-enzyme intermediate reminiscent of the classical GMP-enzyme intermediate. Furthermore, our data indicate that ribavirin monophosphate can be transferred to the diphosphate end of an RNA transcript to form the unusual RpppN structure. Finally, we provide evidence that RNA transcripts that possess ribavirin as the blocking nucleoside are more stable than unblocked transcripts. However, in vitro translation assays indicate that RNA transcripts blocked with ribavirin are not translated efficiently. Our study provides the first biochemical evidences that ribavirin can directly interact with a viral capping enzyme. The ability of a purified RNA capping enzyme to utilize ribavirin as a substrate has not been previously documented and has implications for our understanding of the catalytic mechanisms of RNA capping enzymes. The biological implications of these findings for the proposed ribavirin-mediated inhibition of capping are discussed.
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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 | 0.001 | 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".