Distinguishing between calpain heterodimerization and homodimerization
Bibliographic record
Abstract
The two main mammalian calpains, 1 and 2, are heterodimers of a large 80 kDa and a small 28 kDa subunit that together bind multiple calcium ions during enzyme activation. The main contact between the two subunits of these intracellular cysteine proteases is through a pairing of the fifth EF-hand of their C-terminal penta-EF-hand (PEF) domains. From modeling studies and observation of crystal structures, it is not obvious why these calpains form heterodimers with the small subunit rather than homodimers of the large subunit, as suggested for calpain 3 (p94). Therefore, we have used a differential tagging system to determine which of the other PEF domain-containing calpains form heterodimers and which form homodimers. His6-tagged PEF domains of calpains 1, 3, 9 and 13 were coexpressed with the PEF domain of the small subunit that had been tagged with an antifreeze protein. As predicted, the PEF domain of calpain 1 heterodimerized and that of calpain 3 formed a homodimer. The PEF domain of digestive tract-specific calpain 9 heterodimerized with the small subunit, and that of calpain 13, prevalent in lung and testis, was mainly found as a homodimer with a small amount of heterodimer. These results indicate whether recombinant production of a particular calpain requires coexpression of the small subunit, and whether this calpain is likely to be active in a small subunit knockout mouse. Furthermore, as the endogenous inhibitor calpastatin binds to PEF domains on the large and small subunit, it is less likely that the homodimeric calpains 3 and 13 with two active sites will bind or be silenced by calpastatin.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".