Quantification and structure–function analysis of calpain-1 and calpain-2 protease subunit interactions
Bibliographic record
Abstract
Calpain-1 and calpain-2 are heterodimeric proteases consisting of a common small regulatory subunit CAPNS1 and a large catalytic subunit, CAPN1 or CAPN2, respectively. These calpains have emerged as potential therapeutic targets in cancer and other diseases through their roles in cell signaling pathways affecting sensitivity to chemotherapeutic and targeted drugs, and in promoting metastasis. While inhibition of calpains has the potential to provide therapeutic benefit to cancer patients, there are currently no clinically approved active site directed drugs that specifically and effectively inhibit them. However, the structures of calpain-1 and calpain-2 make them susceptible to allosteric inhibition aimed at interfering with heterodimerization of the catalytic and regulatory subunits, which is necessary for stability and proteolytic activity. Split-Nanoluciferase biosensors were generated to quantify the protein-protein interactions (PPIs) between the calcium-binding penta-EF hand (PEF) domains of CAPN1 or CAPN2 and CAPNS1. These biosensors were used to quantify the heterodimer dissociation constants (K D ) of calpain-1 and calpain-2, estimated at 185 nM and 509 nM, respectively, in the presence of 5 mM Ca 2+ ; and 362 nM and 1651 nM, respectively, in the presence of Mg 2+ . The half-maximal Ca 2+ concentrations supporting these PPIs for calpain-1 and calpain-2 were 59.9 μM and 940.8 μM, respectively. Molecular modeling, based on the crystal structure of calpain-2, was used to predict 20 residues of the PEF domains that contribute to heterodimerization. Individual point mutation of CAPNS1 at Q263 reduced the catalytic activity of calpain-2 to 51.0 ± 6.4 % in live cells.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".