Characterization of Hsp90 Co-Chaperone p23 Cleavage by Caspase-7 Uncovers a Peptidase–Substrate Interaction Involving Intrinsically Disordered Regions
Bibliographic record
Abstract
Caspases are cysteinyl peptidases involved in inflammation and apoptosis during which hundreds of proteins are cleaved by executioner caspase-3 and -7. Despite the fact that caspase-3 has a higher catalytic activity, caspase-7 is more proficient at cleaving poly(ADP ribose) polymerase 1 (PARP1) because it uses an exosite within its N-terminal domain (NTD). Here, we demonstrate that molecular determinants also located in the NTD enhance the recognition and proteolysis of the Hsp90 co-chaperone p23. Structure–activity relationship analyses using mutagenesis of the caspase-7 NTD and kinetics show that residues 36–45 of caspase-7, which overlap with residues necessary for efficacious PARP1 cleavage, participate in p23 recognition. We also demonstrate using chimeric and truncated proteins that the caspase-7 NTD binds close to the cleavage site in the C-terminal tail of p23. Moreover, because p23 is cleaved at a site bearing a P4 Pro residue (PEVD 142 ↓G), which is far from the optimal sequence, we tested all residues at that position and found notable differences in the preference of caspase-7 and magnitude of differences between residues compared to the results of studies that have used small peptidic substrate libraries. Finally, bioinformatics shows that the regions we identified in caspase-7 and p23 are intrinsically disordered regions that contain molecular recognition features that permit a transient interaction between these two proteins. In summary, we characterized the binding mode for a caspase that is tailored to the specific recognition and cleavage of a substrate, highlighting the importance of studying the peptidase–substrate pair to understand the modalities of substrate recognition by caspases.
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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".