Caloxin 1c2: Experimental Evidence That It Binds Plasma Membrane Calcium Pump
Bibliographic record
Abstract
We engineered caloxin 1c2, a novel high affinity peptide (TAWSEVLDLLRRGGGSK‐amide) inhibitor of the Plasma Membrane Ca 2+ pump (PMCA). To show that caloxin 1c2 acts by binding to the PMCA, we synthesized a photoreactive derivative 3Bpa‐caloxin 1c2 (TA(Bpa)SEVLDLLRRGGGSK‐biotin), containing the photoreactive residue Bpa (benzoylphenylalanine) and biotin. 3Bpa‐caloxin 1c2 inhibited the Ca 2+ ‐Mg 2+ ‐ATPase activity of PMCA. The human erythrocyte membranes were photolabeled with 3Bpa‐caloxin 1c2 and the proteins were detected in the Western blots using HRP‐streptavidin to identify biotin or PMCA antibodies to detect PMCA. The photolabeled erythrocyte membranes showed a 250–270 kDa doublet with HRP‐streptavidin. The degree of biotinylation of the erythrocyte membranes depended on the length of the cross‐linking time, and concentrations of 3Bpa‐caloxin 1c2 and the membrane protein. Immunoprecipitates from the photolabeled erythrocyte membranes using a PMCA antibody showed a 250–270 kDa doublet with HRP‐streptavidin. Biotinylated proteins isolated from the photolabeled erythrocyte membranes using captavidin also showed a 250–270 kDa doublet with HRP‐streptavidin and PMCA antibodies. Caloxin 1c2 had been selected for binding to the extracellular domain 1 (amino acids 115–131) of PMCA isoform 4. Caloxin 1c2 and the extracellular domain 1 peptide of PMCA 4 competed with 3Bpa‐caloxin 1c2 for photolabeling the erythrocyte membranes. Pieces of de‐endothelialized pig coronary artery cross‐linked to 3Bpa‐caloxin 1c2 and treated with Alexa‐streptavidin were examined by confocal microscopy, using the Na + ‐pump inhibitor Bodipy‐ouabain as a positive control. Both the probes bound to the cell surface. Thus, the photoreactive derivative of caloxin 1c2 binds to PMCA at the cell surface. Supported by Heart & Stroke Foundation of Ontario.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".