Two Domains of the Epstein-Barr Virus Origin DNA-binding Protein, EBNA1, Orchestrate Sequence-specific DNA Binding
Bibliographic record
Abstract
The EBNA1 (for Epstein-Barr nuclear antigen 1) protein of Epstein-Barr virus governs the replication and partitioning of the viral genomes during latent infection by binding to specific recognition sites in the viral origin of DNA replication. The crystal structure of the DNA binding portion of the EBNA1 protein revealed that this region comprises two structural motifs; a core domain, which mediates protein dimerization and is structurally homologous to the DNA binding domain of the papillomavirus E2 protein, and a flanking domain, which mediated all the observed sequence-specific contacts. To test the possibility that the EBNA1 core domain plays a role in sequence-specific DNA binding not revealed in the crystal structure, we examined the effects of point mutations in potential hydrogen bond donors located in an alpha-helix of the EBNA1 core domain whose structural homologue in E2 mediates sequence-specific DNA binding. We show that these mutations severely reduce the affinity of EBNA1 for its recognition site, and that the core domain, when expressed in the absence of the flanking domain, has sequence-specific DNA binding activity. Flanking domain residues were also found to contribute to the DNA binding activity of EBNA1. Thus, both the core and flanking domains of EBNA1 play direct roles in DNA recognition.
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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".