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High Affinity Fluorescent Probe for Proteinase-Activated Receptor 2 (PAR2)

2019· article· en· W2951699133 on OpenAlexafffund
Jordan C LeSarge, Pierre E. Thibeault, Mark Milne, Rithwik Ramachandran, Leonard G. Luyt

Bibliographic record

VenueACS Medicinal Chemistry Letters · 2019
Typearticle
Languageen
FieldMedicine
TopicBlood Coagulation and Thrombosis Mechanisms
Canadian institutionsLawson Health Research InstituteWestern University
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsFluorophoreFluorescenceIn vivoPeptideReceptorIn vitroChemistryG protein-coupled receptorBiophysicsEC50Conjugated systemCombinatorial chemistryBiochemistryBiology

Abstract

fetched live from OpenAlex

PAR2 is a proteolytically activated G protein-coupled receptor (GPCR) that is implicated in various cancers and inflammatory diseases. Ligands with low nanomolar affinity for PAR2 have been developed, but there is a paucity of research on the development of PAR2-targeting imaging probes. Here, we report the development of seven novel PAR2-targeting compounds. Four of these compounds are highly potent and selective PAR2-targeting peptides (EC 50 = 10 to 23 nM) that have a primary amine handle available for facile conjugation to various imaging components. We describe a peptide of the sequence Isox-Cha-Chg-ARK(Sulfo-Cy5)-NH 2 as the most potent and highest affinity PAR2-selective fluorescent probe reported to date (EC 50 = 16 nM, K D = 38 nM). This compound has a greater than 10-fold increase in potency and binding affinity for PAR2 compared to the leading previously reported probe and is conjugated to a red-shifted fluorophore, enabling in vitro and in vivo studies.

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 score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.017
GPT teacher head0.248
Teacher spread0.231 · 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

Citations7
Published2019
Admission routes2
Has abstractyes

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Same venueACS Medicinal Chemistry LettersSame topicBlood Coagulation and Thrombosis MechanismsFrench-language works237,207