Molecular Determinants of TRIF Proteolysis Mediated by the Hepatitis C Virus NS3/4A Protease
Bibliographic record
Abstract
Persistent infections with hepatitis C virus (HCV) are a major cause of liver disease and reflect its ability to disrupt virus-induced signaling pathways activating cellular antiviral defenses. HCV evasion of double-stranded RNA signaling through Toll-like receptor 3 is mediated by the viral protease NS3/4A, which directs proteolysis of its proline-rich adaptor protein, Toll-IL-1 receptor domain containing adaptor-inducing interferon-beta (TRIF). The TRIF cleavage site has remarkable homology with the viral NS4B/5A substrate, although an 8-residue polyproline track extends upstream from the P(6) position in lieu of the acidic residue present in viral substrates. Circular dichroism (CD) spectroscopy confirmed that a substantial fraction of TRIF exists as polyproline II helices, and inclusion of the polyproline track increased affinity of P side TRIF peptides for the HCV-BK protease. A polyproline II peptide representing an SH3 binding motif (PPPVPPRRR, Sos) bound NS3 with moderate affinity, resulting in inhibition of proteolytic activity. Chemical shift perturbations in NMR spectra indicated that Sos binds a 3(10) helix close to the protease active site. Thus, a polyproline II interaction with the 3(10) helix likely facilitates NS3/4A recognition of TRIF, indicating a significant difference from NS3/4A recognition of viral substrates. Because SH3 binding motifs are also present in NS5A, a viral protein that interacts with NS3, we speculate that the NS3 3(10) helix may be a site of interaction with other viral proteins.
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 | 0.000 | 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 | 0.000 | 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".