Specific targeting of the deubiquitinase and E3 ligase families with engineered ubiquitin variants
Bibliographic record
Abstract
The ubiquitin proteasome system (UPS) has garnered much attention due to its potential for the development of therapeutics. Following a successful clinical application of general proteasome inhibitors much effort has been devoted to targeting individual UPS components including E3 enzymes and deubiquitinases that control specificity of ubiquitination. Our group has developed a novel approach for targeting the UPS proteins using engineered ubiquitin variants (Ubvs). These drug-like proteins can serve as valuable tools to study biological function of UPS components and assist in the development of small molecules for clinical use. In this review, we summarize studies of Ubvs targeting members of three major families, including deubiquitinases, HECT E3 ligases, and CRL E3 ligases. In particular, we focus on Ubv binding mechanisms, structural studies, and effects on enzyme function. Furthermore, new insights gained from the Ubvs are discussed in the context of small molecule studies.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".