Dysregulation of Human Mitochondrial ClpP Protease Activity by Acyldepsipeptides Analogs Leads to Apoptotic Cell Death
Bibliographic record
Abstract
Acyldepsipeptides (ADEPs) are potential novel antibiotics. They dysregulate the activity of the highly conserved tetradecameric bacterial ClpP protease leading to bacterial cell death. Here, we identified several ADEP analogs that are potent dysregulators of the human mitochondrial ClpP (HsClpP). These ADEPs interact tightly with HsClpP causing the protease to non‐specifically degrade model substrates. Dysregulation of HsClpP activity by these ADEPs was found to have cytotoxic effects in multiple human cell lines as a result of the activation of the intrinsic, caspase‐dependent apoptosis. ADEP‐HsClpP co‐crystal structure was solved for one of the analogs revealing a highly complementary binding interface formed by two HsClpP neighbouring subunits but, unexpectedly, with HsClpP in the compact conformation. Given that HsClpP is highly expressed in multiple cancers and has important roles in cell metastasis, our findings suggest a novel therapeutic potential for ADEPs in cancer treatment. Support or Funding Information This work was funded by Natural Sciences and Engineering Research Council of Canada grant (RGPIN 2014‐05393) to WAH This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
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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) | 0.000 | 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) | 0.001 | 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 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".