Effect of Metal Ion Binding on the Structural Stability of the Hepatitis C Virus RNA Polymerase
Bibliographic record
Abstract
The RNA polymerase activity of the hepatitis C virus, a major human pathogen, has previously been shown to be supported by metal ions. In the present study, we report a systematic analysis of the effect of metal ion binding on the structural stability of the hepatitis C virus RNA polymerase. Chemical and thermal denaturation assays revealed that the stability of the protein is increased significantly in the presence of metal ions. Structural analyses clearly established that metal ion binding increases hydrophobic exposure on the RNA polymerase surface. Furthermore, our denaturation studies, coupled with polymerization assays, demonstrate that the active site region of the polymerase is more sensitive to chemical denaturant than other structural scaffolds. We also report the first detailed study of the thermodynamic parameters involved in the interaction between the hepatitis C virus RNA polymerase and metal ions. Finally, a mutational analysis was also performed to investigate the importance of Asp(220), Asp(318), and Asp(319) for metal ion binding. This mutational study underscores a strict requirement for each of the residues for metal binding, indicating that the active center of the HCV RNA polymerase is intolerant to virtually any perturbations of the metal coordination sphere, thereby highlighting the critical role of the enzyme-bound metal ions. Overall, our results indicate that metal ions play a dual modulatory role in the RNA polymerase reaction by promoting both a favorable geometry of the active site for catalysis and by increasing the structural stability of the enzyme.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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".