Protein Interaction Domains of the Ubiquitin-specific Protease, USP7/HAUSP
Bibliographic record
Abstract
USP7 or HAUSP is a ubiquitin-specific protease in human cells that regulates the turnover of p53 and is bound by at least two viral proteins, the ICP0 protein of herpes simplex type 1 and the EBNA1 protein of Epstein-Barr virus. We have overexpressed and purified USP7 and shown that the purified protein is monomeric and is active for cleaving both a linear ubiquitin substrate and conjugated ubiquitin on EBNA1. Using partial proteolysis of USP7 coupled with matrix-assisted laser desorption ionization time-of-flight mass spectrometry, we showed that USP7 comprises four structural domains; an N-terminal domain known to bind p53, a catalytic domain, and two C-terminal domains. By passing a mixture of USP7 domains over EBNA1 and ICP0 affinity columns, we showed that the N-terminal p53 binding domain was also responsible for the EBNA1 interaction, while the ICP0 binding domain mapped to a C-terminal domain between amino acids 599-801. Tryptophan fluorescence assays showed that an EBNA1 peptide mapping to residues 395-450 was sufficient to bind the USP7 N-terminal domain and did so with a dissociation constant of 0.9-2 microM, whereas p53 peptides spanning the USP7-binding region gave dissociation constants of 9-17 microM in the same assay. In keeping with these relative affinities, gel filtration analyses of the complexes showed that the EBNA1 peptide efficiently competed with the p53 peptide for USP7 binding, suggesting that EBNA1 could affect p53 function in vivo by competing for USP7.
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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 | 0.001 |
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".