SARS-CoV-2 hijacks cellular kinase CDK2 to promote viral RNA synthesis
Bibliographic record
Abstract
The coronavirus disease 2019 (COVID-19) pandemic has devastated global health. Identifying key host factors essential for SARS-CoV-2 RNA replication is expected to unravel cellular targets for the development of broad-spectrum antiviral drugs which have been quested for the preparedness of future viral outbreaks. Here, we have identified host proteins that associate with nonstructural protein 12 (nsp12), the RNA-dependent RNA polymerase (RdRp) of SARS-CoV-2 using a mass spectrometry (MS)-based proteomic approach. Among the candidate factors, CDK2 (Cyclin-dependent kinase 2), a member of cyclin-dependent kinases, interacts with nsp12 and causes its phosphorylation at T20, thus facilitating the assembly of the RdRp complex consisting of nsp12, nsp7 and nsp8 and promoting efficient synthesis of viral RNA. The crucial role of CDK2 in viral RdRp function is further supported by our observation that CDK2 inhibitors potently impair viral RNA synthesis and SARS-CoV-2 infection. Taken together, we have discovered CDK2 as a key host factor of SARS-CoV-2 RdRp complex, thus serving a promising target for the development of SARS-CoV-2 RdRp inhibitors.
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) | 0.002 | 0.001 |
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".