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Behind the curtain: cellular mechanisms for allosteric modulation of calcium‐sensing receptors

2011· review· en· W1581940992 on OpenAlexaff
Alice Cavanaugh, Ying Huang, Gerda E. Breitwieser

Bibliographic record

VenueBritish Journal of Pharmacology · 2011
Typereview
Languageen
FieldNursing
TopicBiochemical Analysis and Sensing Techniques
Canadian institutionsMcGill UniversityRoyal Victoria Hospital
FundersNational Institute of General Medical SciencesNational Institutes of Health
KeywordsAllosteric regulationAllosteric modulatorCalcium-sensing receptorReceptorCell biologyIntracellularChemistryEndoplasmic reticulumAgonistAllosteric enzymeCalcium signalingBiophysicsBiologyBiochemistryCalciumCalcium metabolism

Abstract

fetched live from OpenAlex

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

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0020.004
Open science0.0010.001
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0060.003

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.

Opus teacher head0.069
GPT teacher head0.351
Teacher spread0.282 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations24
Published2011
Admission routes1
Has abstractyes

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