Resistance to excision determines efficiency of hepatitis C virus RNA-dependent RNA polymerase inhibition by nucleotide analogs
Bibliographic record
Abstract
NS5B is the RNA-dependent RNA polymerase that catalyzes the replication of the hepatitis C virus genome. It is a major target for antiviral drugs including nucleoside analogs, such as the prodrugs mericitabine and sofosbuvir, which get metabolized to 2'-fluoro-2'C-methylcytidine-5'-triphosphate and 2'-fluoro-2'C-methyluridine-5'-triphosphate, respectively. These analogs act as chain terminators after they are incorporated during RNA synthesis. Recently, it has been shown that NS5B can efficiently remove chain terminators by a nucleotide-mediated excision reaction that rescues RNA synthesis. In this study, we use transient-state kinetics to understand the efficiency of inhibition for five nucleoside analogs. We show that CTP analogs are readily incorporated into a growing primer by NS5B but are also efficiently excised. In contrast, although UMP analogs are more slowly incorporated, the excision of UMP is slow and inefficient, and modifications to the 2'-carbon of the UTP ribose ring further decreased rates of excision to an undetectable level. Taken together, these data suggest that the clinical effectiveness of sofosbuvir is largely a function of being intractable to nucleotide-mediated excision compared with similar nucleoside analogs.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".