Targeting the Ubiquitin E1 as a Novel Anti-Cancer Strategy
Bibliographic record
Abstract
The proteasomal pathway of protein degradation involves two discrete steps: ubiquitination and degradation. Blocking protein degradation by inhibiting the proteasome has well described biologic effects and proteasome inhibitors are approved for the treatment of multiple myeloma and mantle cell lymphoma. In contrast, the biological effects and potential therapeutic utility of inhibiting the ubiquitination cascade and the initiating enzyme UBA1 are less well understood. UBA1 is the initial enzyme in the ubiquitination cascade and initiates the transfer of ubiquitin molecules to target proteins where they are degraded by the proteasome. Here, we review the biological effects of UBA1 inhibition and discuss UBA1 inhibitors as potential anti-cancer agents. Similar to proteasome inhibition, blocking UBA1 elicits an unfolded protein response and induces cell death in malignant cells over normal cells. Chemical UBA1 inhibitors have been developed that target different regions of the enzyme and inhibit its function through different mechanisms. These molecules are useful tools to understand the biology of UBA1 and highlight the potential of inhibiting this target for the treatment of malignancy.
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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) | 0.001 | 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".