Calpastatin Subdomains A and C Are Activators of Calpain
Bibliographic record
Abstract
The inhibitory domains of calpastatin contain three highly conserved regions, A, B, and C, of which A and C bind calpain in a strictly Ca(2+)-dependent manner but have no inhibitory activity whereas region B inhibits calpain on its own. We synthesized the 19-mer oligopeptides corresponding to regions A and C of human calpastatin domain I and tested their effect on human erythrocyte mu-calpain and rat m-calpain. The two peptides significantly activate both calpains: the Ca(2+) concentration required for half-maximal activity is lowered from 4.3 to 2.4 microm for mu-calpain and from 250 to 140 microm for m-calpain. The EC(50) concentration of the peptides is 7.5 microm for mu-calpain and 25 microm for m-calpain. It is noteworthy that at low Ca(2+) concentrations (1-2 microm for mu-calpain and 70-110 microm for m-calpain) both enzymes are activated about 10-fold by the peptides. Based on these findings, it is suggested that calpastatin fragments may have a role in calpain activation in vivo. Furthermore, these activators open new avenues to cell biological studies of calpain function and eventually may alleviate pathological states caused by calpain malfunction.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".