A genus-wide interaction atlas across NS4B orthologues identifies a conserved role for UFMylation in orthoflavivirus replication
Bibliographic record
Abstract
Abstract Orthoflavivirus infections represent an increasing public health burden, with several members of the genus emerging or re-emerging globally. Despite the availability of few vaccines, no antiviral drugs are currently licensed for the treatment of orthoflavivirus infections. Several pre-clinical studies identified the non-structural protein 4B (NS4B), one of the least characterized viral proteins within the orthoflavivirus genus, as the most promising target for the development of potent direct-acting antivirals. However, its functional roles in viral replication are still elusive. Here, we employ an integrated proteomic approach to systematically identify cellular targets of NS4B across eight prototypic orthoflaviviruses and characterize their influence on the human proteome. Using this approach, we mapped high-confidence NS4B-interacting human proteins across the genus, underlying potentially divergent mechanisms of host adaptation across orthoflaviviruses spanning diverse pathologies and vector preferences. Among these, we unveil a novel function for UBA5, the E1-activating enzyme of the UFMylation pathway, in orthoflavivirus replication. Mechanistically, we map associations of distinct viral proteins with multiple members of the UFMylation pathway, which are selectively recruited to sites of viral replication to promote mitochondrial respiration. Finally, we demonstrate that pharmacological inhibition of UFMylation exerts potent antiviral activity in vitro and in vivo . This integrative study provides a rational framework for a system-level understanding of orthoflavivirus NS4B effector functions and sheds light on a conserved and unconventional role for UFMylation in orthoflavivirus replication.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".