Baculovirus protein PK2 subverts eIF2α kinase function by mimicry of its kinase domain C-lobe
Bibliographic record
Abstract
Phosphorylation of eukaryotic translation initiation factor 2α (eIF2α) by eIF2α family kinases is a conserved mechanism to limit protein synthesis under specific stress conditions. The baculovirus-encoded protein PK2 inhibits eIF2α family kinases in vivo, thereby increasing viral fitness. However, the precise mechanism by which PK2 inhibits eIF2α kinase function remains an enigma. Here, we probed the mechanism by which PK2 inhibits the model eIF2α kinase human RNA-dependent protein kinase (PKR) as well as native insect eIF2α kinases. Although PK2 structurally mimics the C-lobe of a protein kinase domain and possesses the required docking infrastructure to bind eIF2α, we show that PK2 directly binds the kinase domain of PKR (PKR(KD)) but not eIF2α. The PKR(KD)-PK2 interaction requires a 22-residue N-terminal extension preceding the globular PK2 body that we term the "eIF2α kinase C-lobe mimic" (EKCM) domain. The functional insufficiency of the N-terminal extension of PK2 implicates a role for the adjacent EKCM domain in binding and inhibiting PKR. Using a genetic screen in yeast, we isolated PK2-activating mutations that cluster to a surface of the EKCM domain that in bona fide protein kinases forms the catalytic cleft through sandwiching interactions with a kinase N-lobe. Interaction assays revealed that PK2 associates with the N- but not the C-lobe of PKR(KD). We propose an inhibitory model whereby PK2 engages the N-lobe of an eIF2α kinase domain to create a nonfunctional pseudokinase domain complex, possibly through a lobe-swapping mechanism. Finally, we show that PK2 enhances baculovirus fitness in insect hosts by targeting the endogenous insect heme-regulated inhibitor (HRI)-like eIF2α kinase.
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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 | 0.001 |
| 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".