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Record W3197717323 · doi:10.1021/acsptsci.1c00157

Identification of Key Regions Mediating Human Melatonin Type 1 Receptor Functional Selectivity Revealed by Natural Variants

2021· article· en· W3197717323 on OpenAlexafffund
Alan Hégron, Eunna Huh, Xavier Deupí, Badr Sokrat, Wenwen Gao, Christian Le Gouill, Mickaël Canouil, Mathilde Boissel, G. Charpentier, Ronan Roussel, Beverley Balkau, Philippe Froguel, Bianca Plouffe, Amélie Bonnefond, Olivier Lichtarge, Ralf Jockers, Michel Bouvier

Bibliographic record

VenueACS Pharmacology & Translational Science · 2021
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 SciencesFonds de Recherche du Québec - SantéChina Scholarship CouncilInstitut National de la Santé et de la Recherche MédicaleNational Institutes of HealthCanada Research ChairsWellcome TrustAgence Nationale de la RechercheUniversité de MontréalDiabetes UKDiabetes CanadaCentre National de la Recherche ScientifiqueCanadian Institutes of Health ResearchWellcome
KeywordsIdentification (biology)Melatonin receptorKey (lock)MelatoninComputational biologyReceptorBiologyNeuroscienceGeneticsEcology

Abstract

fetched live from OpenAlex

High Resolution Image Download MS PowerPoint Slide Melatonin is a hormone mainly produced by the pineal gland and MT 1 is one of the two G protein-coupled receptors (GPCRs) mediating its action. Despite an increasing number of available GPCR crystal structures, the molecular mechanism of activation of a large number of receptors, including MT 1, remains poorly understood. The purpose of this study is to elucidate the structural elements involved in the process of MT 1 ’s activation using naturally occurring variants affecting its function. Thirty-six nonsynonymous variants, including 34 rare ones, were identified in MTNR1A (encoding MT 1 ) from a cohort of 8687 individuals and their signaling profiles were characterized using Bioluminescence Resonance Energy Transfer-based sensors probing 11 different signaling pathways. Computational analysis of the experimental data allowed us to group the variants in clusters according to their signaling profiles and to analyze the position of each variant in the context of the three-dimensional structure of MT 1 to link functional selectivity to structure. MT 1 variant signaling profiles revealed three clusters characterized by (1) wild-type-like variants, (2) variants with selective defect of βarrestin-2 recruitment, and (3) severely defective variants on all pathways. Our structural analysis allows us to identify important regions for βarrestin-2 recruitment as well as for Gα12 and Gα15 activation. In addition to identifying MT 1 domains differentially controlling the activation of the various signaling effectors, this study illustrates how natural variants can be used as tools to study the molecular mechanisms of receptor activation.

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 score0.001
Threshold uncertainty score0.004

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.293
Teacher spread0.279 · 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

Citations10
Published2021
Admission routes2
Has abstractyes

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