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Record W2887604271 · doi:10.1038/s42003-018-0101-z

Bioluminescence resonance energy transfer-based biosensors allow monitoring of ligand- and transducer-mediated GPCR conformational changes

2018· article· en· W2887604271 on OpenAlexafffund
Louis-Philippe Picard, Anne Marie Schönegge, Martin J. Lohse, Michel Bouvier

Bibliographic record

VenueCommunications Biology · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicReceptor Mechanisms and Signaling
Canadian institutionsUniversité de MontréalInstitute for Research in Immunology and Cancer
FundersFonds de Recherche du Québec - SantéCanadian Institutes of Health Research
KeywordsBioluminescenceTransducerBiosensorG protein-coupled receptorFörster resonance energy transferEnergy transferBiophysicsLigand (biochemistry)Resonance (particle physics)ChemistryReceptorBiologyPhysicsFluorescenceBiochemistryChemical physicsAcoustics

Abstract

fetched live from OpenAlex

G protein-coupled receptors (GPCRs) are seven-transmembrane proteins that mediate a variety of cellular response which make them a target of choice for drug development in many indications. It is now well established that GPCRs can adopt several distinct conformations that can be differentially stabilized by various ligands resulting in different biological outcomes, a concept known as functional selectivity. However, due to the highly hydrophobic nature of GPCRs, tools to monitor these conformational ensembles are limited and addressing their conformation dynamics remains a challenge with current structural biology approaches. Here we describe new bioluminescent resonance energy transfer-based biosensors that can probe the conformational rearrangement promoted by ligands with different signaling efficacies as well as the impact of transducers such as G proteins and β-arrestin on these conformational transitions. The design of such sensors for other receptors should be useful to further explore the structural determinants of GPCR functional selectivity.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.033
Threshold uncertainty score0.459

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.027
GPT teacher head0.273
Teacher spread0.246 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations32
Published2018
Admission routes2
Has abstractyes

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