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Record W3109875140 · doi:10.1039/d0ob02175j

Activation barriers in Class F G protein-coupled receptors revealed by umbrella sampling simulations

2020· article· en· W3109875140 on OpenAlexaff
Mark Agostino, Sebastian Pohl

Bibliographic record

VenueOrganic & Biomolecular Chemistry · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHedgehog Signaling Pathway Studies
Canadian institutionsBentley (Canada)
FundersGovernment of Western AustraliaCurtin University of TechnologyRaine Medical Research FoundationAustralian Government
KeywordsSmoothenedFrizzledG protein-coupled receptorHedgehog signaling pathwayChemistryCell biologyReceptorVismodegibWnt signaling pathwayHedgehogSignal transductionBiologyBiochemistry

Abstract

fetched live from OpenAlex

The Class F G protein-coupled receptors (GPCRs) include Smoothened and the ten Frizzled receptors, which are major cell membrane receptors in the Hedgehog and Wnt signalling pathways respectively and of enormous interest in embryonic development and as therapeutic targets in cancer. Recent crystal structures of Smoothened provide the opportunity to investigate the structural biology of Class F GPCRs in more detail, in turn, informing the development of therapeutics. A key question in this area is how one receptor may trigger distinct pathways - particularly relevant for Wnt signalling, in which signals may be transduced from a Frizzled via Dishevelled or G proteins, depending on the context. In this study, we employ adiabatic biased molecular dynamics and umbrella sampling to investigate the activation of Smoothened and Frizzled-7 in both the native state and bound to endogenous ligands, as well as how the clinically used Smoothened antagonist vismodegib alters this signalling. The results highlight key energetic barriers in the activation of these receptors, and the molecular features of the receptors mediating these barriers, demonstrating our approach as a robust means of investigating signalling through these receptors.

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)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.049
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0000.000

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 head0.015
GPT teacher head0.247
Teacher spread0.232 · 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
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

Citations4
Published2020
Admission routes1
Has abstractyes

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