Physical Interactions between Phospholamban and Sarco(endo)plasmic Reticulum Ca2+-ATPases Are Dissociated by Elevated Ca2+, but Not by Phospholamban Phosphorylation, Vanadate, or Thapsigargin, and Are Enhanced by ATP
Bibliographic record
Abstract
Previous co-immunoprecipitation studies (Asahi, M., Kimura, Y., Kurzydlowski, K., Tada, M., and MacLennan, D. H. (1999) J. Biol. Chem. 274, 32855-32862) revealed that physical interactions between phospholamban (PLN) and the fast-twitch skeletal muscle sarco(endo)plasmic reticulum Ca(2+) ATPase (SERCA1a) were retained, even with PLN monoclonal antibody 1D11 bound to an epitope lying between PLN residues 7 and 17. Because the 1D11 antibody relieves inhibitory interaction between the two proteins, it was of interest to determine whether PLN phosphorylation or elevation of Ca(2+), which also relieves inhibitory interactions between PLN and SERCA, would disrupt physical interactions. Co-immunoprecipitation was measured in the presence of increasing concentrations of Ca(2+) or after phosphorylation of PLN by protein kinase A. Physical interactions were dissociated by elevated Ca(2+) but not by PLN phosphorylation. The addition of ATP enhanced interactions between PLN and SERCA. The further addition of vanadate and thapsigargin, both of which stabilize the E(2) conformation, did not diminish binding of PLN to SERCA. These data suggest that physical interactions between PLN and SERCA are stable when SERCA is in the Ca(2+)-free E(2) conformation but not when it is in the E(1) conformation and that phosphorylation of PLN does not dissociate physical interactions between PLN and SERCA.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".