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Record W2969585325 · doi:10.1101/746693

Molecular Basis for G-protein-Coupled Receptor (GPCR) Activation and Biased Signalling at the Platelet Thrombin Receptor Proteinase Activated Receptor-4 (PAR4)

2019· preprint· en· W2969585325 on OpenAlexafffund
Pierre E. Thibeault, Jordan C LeSarge, D’Arcy Arends, Michaela Fernandes, Peter Chidiac, Peter B. Stathopulos, Leonard G. Luyt, Rithwik Ramachandran

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2019
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicReceptor Mechanisms and Signaling
Canadian institutionsLawson Health Research InstituteWestern University
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsProtease-activated receptorG protein-coupled receptorReceptorArrestinThrombinBiochemistryG protein-coupled receptor kinaseCell biologyChemistryFunctional selectivityFormyl peptide receptorPeptideProtease-activated receptor 2Biology5-HT5A receptorChemotaxisPlatelet

Abstract

fetched live from OpenAlex

Abstract Proteinase Activated Receptor-4 (PAR4) is a member of the proteolytically-activated PAR family of G-Protein-coupled Receptors (GPCRs). PARs are activated following proteolytic cleavage of the receptor N-terminus by enzymes such as thrombin, trypsin, and cathepsin-G to reveal the receptor-activating motif termed the tethered ligand. The tethered ligand binds intramolecularly to the receptor and triggers receptor signalling and cellular responses. In spite of this unusual mechanism of activation, PARs are fundamentally peptide receptors and can also be activated by exogenous application of short synthetic peptides derived from the tethered ligand sequence. In order to gain a better understanding of the molecular basis for PAR4-dependent signalling, we examined signalling responses to a library of peptides derived from the canonical PAR4 activating peptide (PAR4-AP), AYPGKF-NH 2 . We examined peptide residues involved in activation of the G α q/11 -coupled calcium signalling pathway, β-arrestin recruitment, and mitogen-activated protein kinase pathway activation. The peptide N -methyl-alanine-YPGKF-NH 2 was identified as a compound that is a poor activator of PAR4-dependent calcium signalling but was fully competent in recruiting β-arrestin-1 and -2. In order to gain a better understanding of the ligand-binding pocket, we used in silico docking to identify key residues involved in PAR4 interaction with AYPGKF-NH 2 . The predicted interactions were verified by site-directed mutagenesis and analysis of calcium signalling and β-arrestin-1/-2 recruitment following proteolytic activation (with thrombin) or activation with the synthetic agonist peptide (AYPGKF-NH 2 ). We determined that a key extracellular loop-2 aspartic acid residue (Asp 230 ) is critical for signalling following both proteolytic and peptide activation of PAR4. Finally, we investigated platelet aggregation in response to A y PGKF-NH 2 (a peptide with D-tyrosine in position two) which is unable to activate calcium signalling, and AYPG R F-NH 2 a peptide that is equipotent to the parental peptide AYPGKF-NH 2 for calcium signalling but is more potent at recruiting β-arrestins. We found that A y PGKF-NH 2 fails to activate platelets while AYPG R F-NH 2 causes a platelet aggregation response that is greater than that seen with the parental peptide and is comparable to that seen with thrombin stimulation. Overall, these studies uncover molecular determinants for agonist binding and signalling through a non-canonically activated GPCR and provide a template for development of small molecule modulators of PAR4.

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 score0.002
Threshold uncertainty score0.005

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)0.0020.000

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 head0.013
GPT teacher head0.216
Teacher spread0.203 · 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

Citations0
Published2019
Admission routes2
Has abstractyes

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