Non-nucleoside inhibitors of the HCV NS5B polymerase: progress in the discovery and development of novel agents for the treatment of HCV infections.
Bibliographic record
Abstract
The severe health conditions associated with chronic HCV infection remain a global concern. Small-molecule drugs that specifically target essential virally encoded enzymes have not yet progressed to market, and the current standard of care continues to rely on a combination of pegylated IFN with ribavirin. This therapy has serious side effects and a significant proportion of patients infected with HCV genotype 1 (the major genotype in industrialized countries) have an unsatisfactory outcome with this therapy. Major advances have been realized in the development of specific non-nucleoside inhibitors of the viral NS5B RNA-dependent RNA polymerase. This well-characterized replicative enzyme is a highly drugable target that, in addition to its active site, features at least three known allosteric binding pockets that regulate RNA synthesis and are suitable for inhibitor design. Clinical proof-of-concept for allosteric non-nucleoside HCV polymerase inhibitors has been reported and several compounds have progressed into preclinical studies. It is likely that in the future NS5B inhibitors will form an integral part of more effective anti-HCV therapies, combining the use of small-molecule antiviral drugs with or without the assistance of immune modulators such as IFNs in order to minimize the emergence of resistance.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".