Hepatitis C Virus NS3/4A Protease Inhibitors: A Light at the End of the Tunnel
Bibliographic record
Abstract
Hepatitis C virus (HCV) infection is a serious and growing threat to human health. The current treatment provides limited efficacy and is poorly tolerated, highlighting the urgent medical need for novel therapeutics. The membrane-targeted NS3 protein in complex with the NS4A comprises a serine protease domain (NS3/4A protease) that is essential for viral polyprotein maturation and contributes to the evasion of the host innate antiviral immunity by HCV. Therefore, the NS3/4A protease represents an attractive target for drug discovery, which is tied in with the challenge to develop selective small-molecule inhibitors. A rational drug design approach, based on the discovery of N-terminus product inhibition, led to the identification of potent and orally bioavailable NS3 inhibitors that target the highly conserved protease active site. This review summarizes the NS3 protease inhibitors currently challenged in clinical trials as one of the most promising antiviral drug class, and possibly among the first anti-HCV agents to be approved for the treatment of HCV infection.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".