Molecular Mechanism by Which a Potent Hepatitis C Virus NS3-NS4A Protease Inhibitor Overcomes Emergence of Resistance
Bibliographic record
Abstract
Although optimizing the resistance profile of an inhibitor can be challenging, it is potentially important for improving the long term effectiveness of antiviral therapy. This work describes our rational approach toward the identification of a macrocyclic acylsulfonamide that is a potent inhibitor of the NS3-NS4A proteases of all hepatitis C virus genotypes and of a panel of genotype 1-resistant variants. The enhanced potency of this compound versus variants D168V and R155K facilitated x-ray determination of the inhibitor-variant complexes. In turn, these structural studies revealed a complex molecular basis of resistance and rationalized how such compounds are able to circumvent these mechanisms. Background: Antivirals must often be given in combinations to avoid rapid emergence of resistance. Results: We identified and structurally characterized protease inhibitors that maintain potency against genotype and resistant variants. Conclusion: Pan-variant potency was achieved by targeting invariant regions and incorporating flexibility where pocket variability occurs. Significance: Such inhibitors may yield simplified and/or more successful treatments for hepatitis C infections.
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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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".