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Record W3066049608 · doi:10.1073/pnas.2003787117

Agonist-induced formation of unproductive receptor-G <sub>12</sub> complexes

2020· article· en· W3066049608 on OpenAlexafffund
Najeah Okashah, Shane C. Wright, Kouki Kawakami, Signe Mathiasen, Joris Zhou, Sumin Lu, Jonathan A. Javitch, Asuka Inoue, Michel Bouvier, Nevin A. Lambert

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicReceptor Mechanisms and Signaling
Canadian institutionsUniversité de MontréalInstitute for Research in Immunology and Cancer
FundersNational Institute of General Medical SciencesNational Institute of Mental HealthCanadian Institutes of Health ResearchSvenska Sällskapet för Medicinsk ForskningJapan Society for the Promotion of ScienceMinistry of Education, Culture, Sports, Science and TechnologyGovernment of CanadaJapan Agency for Medical Research and Development
KeywordsHeterotrimeric G proteinG protein-coupled receptorAgonistG proteinReceptorChemistryG beta-gamma complexCell biologySignal transductionTernary complexBiochemistryBiology

Abstract

fetched live from OpenAlex

Significance G protein-coupled receptors (GPCRs) are targeted by a large fraction of approved drugs and regulate many important cellular processes. Association of GPCRs with heterotrimeric G proteins in response to agonist activation is thought to invariably lead to G protein activation. We find instead that G 12 heterotrimers can associate with agonist-bound receptors in a manner that does not lead to activation. These unproductive agonist–receptor-G protein ternary complexes sequester G 12 heterotrimers and thus inhibit rather than support G 12 signaling. These findings reveal a mechanism whereby agonist activation of GPCRs can inhibit as well as promote G protein signaling.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.048
GPT teacher head0.278
Teacher spread0.230 · 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 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

Citations60
Published2020
Admission routes2
Has abstractyes

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Same venueProceedings of the National Academy of SciencesSame topicReceptor Mechanisms and SignalingFrench-language works237,207