Behind the curtain: cellular mechanisms for allosteric modulation of calcium‐sensing receptors
Bibliographic record
Abstract
Calcium‐sensing receptors (CaSR) are integral to regulation of systemic Ca2+homeostasis. Altered expression levels or mutations in CaSR cause Ca2+handling diseases. CaSR is regulated by both endogenous allosteric modulators and allosteric drugs, including the first Food and Drug Administration‐approved allosteric agonist, Cinacalcet HCl (Sensipar®). Recent studies suggest that allosteric modulators not only alter function of plasma membrane‐localized CaSR, but regulate CaSR stability at the endoplasmic reticulum. This brief review summarizes our current understanding of the role of membrane‐permeant allosteric agonists in cotranslational stabilization of CaSR, and highlights additional, indirect, signalling‐dependent role(s) for membrane‐impermeant allosteric drugs. Overall, these studies suggest that allosteric drugs act at multiple cellular organelles to control receptor abundance and hence function, and that drug hydrophobicity can bias the relative contributions of plasma membrane and intracellular organelles to CaSR abundance and signalling. LINKED ARTICLESThis article is part of a themed section on the Molecular Pharmacology of G Protein‐Coupled Receptors (GPCRs). To view the other articles in this section visit http://dx.doi.org/10.1111/bph.2012.165.issue‐6 . To view the 2010 themed section on the same topic visit http://onlinelibrary.wiley.com/doi/10.1111/bph.2010.159.issue‐5/issuetoc
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".