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Record W3147531120 · doi:10.1038/s41594-021-00674-7

GPCR activation mechanisms across classes and macro/microscales

2021· article· en· W3147531120 on OpenAlexafffund
Alexander S. Hauser, Albert J. Kooistra, Christian Munk, Franziska M. Heydenreich, Dmitry B. Veprintsev, Michel Bouvier, M. Madan Babu, David E. Gloriam

Bibliographic record

VenueNature Structural & Molecular Biology · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicReceptor Mechanisms and Signaling
Canadian institutionsUniversité de MontréalInstitute for Research in Immunology and Cancer
FundersNovo Nordisk FondenEuropean CommissionCanadian Institutes of Health ResearchAmerican Lebanese Syrian Associated CharitiesNovo NordiskAmerican Heart AssociationSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungH. Lundbeck A/SLundbeckfondenNational Science Foundation
KeywordsG protein-coupled receptorComputational biologyMacroChemistryBiologyCell biologyComputer scienceSignal transduction

Abstract

fetched live from OpenAlex

Two-thirds of human hormones and one-third of clinical drugs activate ~350 G-protein-coupled receptors (GPCR) belonging to four classes: A, B1, C and F. Whereas a model of activation has been described for class A, very little is known about the activation of the other classes, which differ by being activated by endogenous ligands bound mainly or entirely extracellularly. Here we show that, although they use the same structural scaffold and share several 'helix macroswitches', the GPCR classes differ in their 'residue microswitch' positions and contacts. We present molecular mechanistic maps of activation for each GPCR class and methods for contact analysis applicable for any functional determinants. This provides a superfamily residue-level rationale for conformational selection and allosteric communication by ligands and G proteins, laying the foundation for receptor-function studies and drugs with the desired modality.

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 score0.004
Threshold uncertainty score0.012

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 communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.004
GPT teacher head0.299
Teacher spread0.295 · 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

Citations308
Published2021
Admission routes2
Has abstractyes

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