Design and Characterization of a Novel eEF2K Degrader with Potent Therapeutic Efficacy Against Triple‐Negative Breast Cancer
Bibliographic record
Abstract
Dysregulated eEF2K expression is implicated in the pathogenesis of many human cancers, including triple-negative breast cancer (TNBC), making it a plausible therapeutic target. However, specific eEF2K inhibitors with potent anti-cancer activity have not been available so far. Targeted protein degradation has emerged as a new strategy for drug discovery. In this study, a novel small molecule chemical is designed and synthesized, named as compound C1, which shows potent activity in degrading eEF2K. C1 selectively binds to F8, L10, R144, C146, E229, and Y236 of the eEF2K protein and promotes its proteasomal degradation by increasing the interaction between eEF2K and the ubiquitin E3 ligase βTRCP in the form of molecular glue. C1 significantly inhibits the proliferation and metastasis of TNBC cells both in vitro and in vivo and in TNBC patient-derived organoids, and these antitumor effects are attributed to the degradation of eEF2K by C1. Additionally, combination treatment of C1 with paclitaxel, a commonly used chemotherapeutic drug, exhibits synergistic anti-tumor effects against TNBC. This study not only generates a powerful research tool to investigate the therapeutic potential of targeting eEF2K, but also provides a promising lead compound for developing novel drugs for the treatment of TNBC and other cancers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.002 |
| 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) | 0.000 | 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 teacher head, 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".