Functional Analyses of the EBNA1 Origin DNA Binding Protein of Epstein-Barr Virus
Bibliographic record
Abstract
The EBNA1 protein of Epstein-Barr virus (EBV) governs the replication and segregation of the viral episomes in latently infected cells and transactivates the expression of other EBV latency proteins through direct interactions with DNA sequences in the EBV latent origin of replication, oriP. To better understand how EBNA1 controls these processes, we have assessed the contribution of various EBNA1 sequences to its replication, segregation, and transactivation functions. Here we show that EBNA1 residues 325 to 376 are responsible for the transactivation activity of EBNA1. This region coincides with the DNA looping domain previously shown to mediate interactions at a distance between DNA-bound EBNA1 molecules. The same residues mediate DNA segregation but have no apparent role in DNA replication, indicating that the replication and transcription activation activities of EBNA1 are distinct. The acidic C-terminal tail of EBNA1 was not found to contribute to replication, transactivation, or segregation. We have also investigated the functional significance of two structural motifs within the DNA binding and dimerization domains of EBNA1, the proline loop and the WF motif. Although the amino acids in these motifs do not directly contact the DNA, both of these motifs were found to contribute to EBNA1 functions by increasing the DNA-binding ability of EBNA1. Mechanisms by which DNA binding is stimulated by these motifs are discussed.
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) | 0.001 | 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".