A Systematic Approach to the Optimization of Substrate-Based Inhibitors of the Hepatitis C Virus NS3 Protease: Discovery of Potent and Specific Tripeptide Inhibitors
Why this work is in the frame
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Bibliographic record
Abstract
The inadequate efficacy and tolerability of current therapies for the infectious liver disease caused by the hepatitis C virus have warranted significant efforts in the development of new therapeutics. We have previously reported competitive peptide inhibitors of the NS3 serine protease based on the N-terminal cleavage products of peptide substrates. A detailed study of the interactions of these substrate-based inhibitors with the different subsites of the serine protease active site led to the discovery of novel residues that increased the affinity of the inhibitors. In this paper, we report the combination of the best binding residues in a tetrapeptide series that resulted in extremely potent inhibitors that bind exquisitely well to this enzyme. A substantial increase in potency was obtained with the simultaneous introduction of a 7-methoxy-2-phenyl-4-quinolinoxy moiety at the gamma-position of the P2 proline and a tert-leucine as a P3 residue. The increase in potency allowed for the further truncation and led to the identification of tripeptide inhibitors. Structure activity relationship studies on this inhibitor series led to the identification of carbamate-containing tripeptides that are able to inhibit replication of subgenomic HCV RNA in cell culture with potencies below 1 microM. This inhibitor series has the potential of becoming antiviral agents for the treatment of HCV infections.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it