Deciphering the interaction surface between the West Nile virus NS3 and NS5 proteins
Bibliographic record
Abstract
West Nile virus (WNV) is the most prevalent mosquito-borne virus and the leading cause of viral encephalitis in the continental United States. It belongs to the family Flaviviridae which includes other important human pathogens such as dengue virus (DENV), Japanese encephalitis virus (JEV) and Zika viruses (ZIKV). Despite several decades of research, no specific antiviral drugs are available to treat flavivirus infections. The present study characterizes the interaction between the WNV NS3 and NS5 proteins for the purpose of identifying hotspots in the protein-protein interaction which could be targeted for the development of antiviral therapeutics. We previously developed an interaction model in silico based on data available in the literature. Here, potential interacting residues on NS3 and NS5 were mutated in a WNV replicon, and seven mutations in the NS3 protein were found to drastically reduce viral replication. In addition to being well conserved among mosquito-borne flaviviruses, these residues are located on the protein’s surface in two clusters which might be interesting new targets for future drug development.
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 | 0.001 |
| 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".