Cell‐based high‐throughput screen for small molecule inhibitors of Bax translocation
Bibliographic record
Abstract
Aberrant regulation of programmed cell death (PCD) has been tied to an array of human pathologies ranging from cancers to autoimmune disorders to diverse forms of neurodegeneration. Pharmacologic modulation of PCD signalling is therefore of central interest to a number of clinical and biomedical applications. A key component of PCD signalling involves the modulation of pro- and anti-apoptotic Bcl-2 family members. Among these, Bax translocation represents a critical regulatory phase in PCD. In the present study, we have employed a high-content high-throughput screen to identify small molecules which inhibit the cellular process of Bax re-distribution to the mitochondria following commitment of the cell to die. Screening of 6246 Generally Recognized As Safe compounds from four chemical libraries post-induction of cisplatin-mediated PCD resulted in the identification of 18 compounds which significantly reduced levels of Bax translocation. Further examination revealed protective effects via reduction of executioner caspase activity and enhanced mitochondrial function. Consistent with their effects on Bax translocation, these compounds exhibited significant rescue against in vitro and in vivo cisplatin-induced apoptosis. Altogether, our findings identify a new set of clinically useful small molecules PCD inhibitors and highlight the role which cAMP plays in regulating Bax-mediated PCD.
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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 | 0.001 | 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 | 0.001 |
| 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".