The Nucleocapsid Proteins of SARS-CoV-2 and Its Close Relative Bat Coronavirus RaTG13 Are Capable of Inhibiting PKR- and RNase L-Mediated Antiviral Pathways
Bibliographic record
Abstract
The high transmissibility of SARS-CoV-2 is an important viral factor defining the coronavirus disease 2019 (COVID-19) pandemic. To transmit efficiently, SARS-CoV-2 must be capable of disarming the innate immune response of its host efficiently. Here, we describe that the nucleocapsid protein of SARS-CoV-2 is capable of inhibiting two critical innate antiviral pathways, PKR and OAS/RNase L. Moreover, the counterpart of the closest animal coronavirus relative of SARS-CoV-2, bat-CoV RaTG13, can also inhibit human PKR and OAS/RNase L antiviral activities. Thus, the importance of our discovery for understanding the COVID-19 pandemic is 2-fold. First, the ability of SARS-CoV-2 N to inhibit innate antiviral activity is likely a factor contributing to the transmissibility and pathogenicity of the virus. Second, the bat relative of SARS-CoV-2 has the capacity to inhibit human innate immunity, which thus likely contributed to the establishment of infection in humans. The findings described in this study are valuable for developing novel antivirals and vaccines.
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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".