Hepatitis C viral protein translation: mechanisms and implications in developing antivirals
Bibliographic record
Abstract
Hepatitis C viral protein translation occurs in a cap-independent manner through the use of an internal ribosomal entry site (IRES) present within the viral 5'-untranslated region. The IRES is composed of highly conserved structural domains that directly recruit the 40S ribosomal subunit to the viral genomic RNA. This frees the virus from relying on a large number of translation initiation factors that are required for cap-dependent translation, conferring a selective advantage to the virus especially in times when the availability of such factors is low. Although the mechanism of translation initiation on the Hepatitis C virus (HCV) IRES is well established, modulation of the HCV IRES activity by both cellular and viral factors is not well understood. As the IRES is essential in the HCV life cycle and as such remains well conserved in an otherwise highly heterogenic virus, the process of HCV protein translation represents an attractive target in the development of novel antivirals. This review will focus on the mechanisms of HCV protein translation and how this process is postulated to be modulated by cis-acting viral factors, as well as trans-acting viral and cellular factors. Numerous therapeutic approaches investigated in targeting HCV protein translation for the development of novel antivirals will also be 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".