Inhibiting Infectious Bronchitis Virus PLpro Using Ubiquitin Variants
Bibliographic record
Abstract
Infectious bronchitis virus (IBV) is a coronavirus first isolated in the 1930s infecting chickens. IBV causes great economic losses to the global poultry industry, as it affects egg production and causes mortality by leaving the host susceptible to secondary bacterial infections. Even though vaccines are available, they are poorly cross-protective against new variants of the virus, which are always on the cusp of emerging. Effective antiviral therapies, or possibly the production of transgenic animals immune to IBV infection, are therefore sorely needed. As the papain-like protease (PLpro) of IBV has deubiquitinating activity besides its crucial ability to cleave the viral polyprotein, we have applied a novel strategy of selecting ubiquitin variants (UbVs) from a phage-displayed library that have high affinity to this viral protease. These UbVs were found to inhibit the deubiquitinating activity of PLpro and consequently obstruct the virus's ability to evade the innate immune response in the host cell. By obstructing the proteolytic activity of PLpro, these UbVs were seemingly able to inhibit viral infection as assessed using immunofluorescence microscopy. Whilst virus infection was detected in around 5% of UbV-expressing cells, the virus was present in around 30-40% of GFP (control)-expressing cells. This suggests that the expression of UbVs indeed seems to inhibit IBV infection, making UbVs a potentially potent and innovative antiviral strategy in the quest for control of IBV infections.
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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 | 0.000 | 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".