Identification of Celastrol as a Novel YAP-TEAD Inhibitor for Cancer Therapy by High Throughput Screening with Ultrasensitive YAP/TAZ–TEAD Biosensors
Bibliographic record
Abstract
The Hippo pathway has emerged as a key signaling pathway that regulates a broad range of biological functions, and dysregulation of the Hippo pathway is a feature of a variety of cancers. Given this, some have suggested that disrupting the interaction of the Hippo core component YAP and its paralog TAZ with transcriptional factor TEAD may be an effective strategy for cancer therapy. However, there are currently no clinically available drugs targeting the YAP/TAZ-TEAD interaction for cancer treatment. To facilitate screens for small molecule compounds that disrupt the YAP-TEAD interaction, we have developed the first ultra-bright NanoLuc biosensor to quantify YAP/TAZ-TEAD protein-protein interaction (PPI) both in living cells and also in vitro using biosensor fusion proteins purified from bacteria. Using this biosensor, we have performed an in vitro high throughput screen (HTS) of small molecule compounds and have identified and validated the drug Celastrol as a novel inhibitor of YAP/TAZ-TEAD interaction. We have also demonstrated that Celastrol can inhibit cancer cell proliferation, transformation, and cell migration. In this study, we describe a new inhibitor of the YAP/TAZ-TEAD interaction warranting further investigation and offer a novel biosensor tool for the discovery of other new Hippo-targeting drugs in future work.
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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 | 0.000 |
| 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) | 0.000 | 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".