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Record W4214889856 · doi:10.1152/ajpcell.00044.2022

Dynamics and mechanistic underpinnings to pharmacology of class A GPCRs: an NMR perspective

2022· review· en· W4214889856 on OpenAlexafffund
Shuya Kate Huang, R. Scott Prosser

Bibliographic record

VenueAmerican Journal of Physiology-Cell Physiology · 2022
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicReceptor Mechanisms and Signaling
Canadian institutionsUniversity of Toronto
FundersCanadian Institutes of Health ResearchGovernment of Canada
KeywordsAllosteric regulationG protein-coupled receptorComputational biologyReceptorSignal transductionDrug discoveryNeuroscienceBiologyChemistryBiophysicsBioinformaticsCell biologyBiochemistry

Abstract

fetched live from OpenAlex

One-third of current pharmaceuticals target G protein-coupled receptors (GPCRs), the largest receptor superfamily in humans and mediators of diverse physiological processes. This review summarizes the recent progress in GPCR structural dynamics, focusing on class A receptors and insights derived from nuclear magnetic resonance (NMR) and other spectroscopic techniques. We describe the structural aspects of GPCR activation and the various pharmacological models that capture aspects of receptor signaling behavior. Spectroscopic studies revealed that receptors and their signaling complexes are dynamic allosteric systems that sample multiple functional states under basal conditions. The distribution of states within the conformational ensemble and the kinetics of transitions between states are regulated through the binding of ligands, allosteric modulators, and the membrane environment. This ensemble view of GPCRs provides a mechanistic framework for understanding many of the pharmacological phenomena associated with receptor signaling, such as basal activity, efficacy, and functional bias.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.909
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.016
GPT teacher head0.310
Teacher spread0.294 · 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 teacher head, not a consensus.

Study designBench or experimental
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

Citations23
Published2022
Admission routes2
Has abstractyes

Explore more

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