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Record W4317816982 · doi:10.3390/ijms24032135

New Insights into Bitopic Orthosteric/Allosteric Ligands of Cannabinoid Receptor Type 2

2023· article· en· W4317816982 on OpenAlexafffund
Rebecca Ferrisi, Beatrice Polini, Caterina Ricardi, Francesca Gado, Kawthar A. Mohamed, Giovanna Baron, Salvatore Faiella, Giulio Poli, Simona Rapposelli, Giuseppe Saccomanni, Giancarlo Aldini, Grazia Chiellini, Robert B. Laprairie, Clementina Manera, Gabriella Ortore

Bibliographic record

VenueInternational Journal of Molecular Sciences · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicReceptor Mechanisms and Signaling
Canadian institutionsDalhousie UniversityUniversity of Saskatchewan
FundersCanadian Institutes of Health ResearchMinistero della SaluteNatural Sciences and Engineering Research Council of CanadaUniversità di PisaGlaxoSmithKline
KeywordsAllosteric regulationCannabinoid receptorChemistryAgonistCannabinoidG protein-coupled receptorLigand (biochemistry)ReceptorAllosteric modulatorCannabinoid receptor type 2PharmacologyStereochemistryNeuroscienceBiochemistryBiology

Abstract

fetched live from OpenAlex

Very recently, we have developed a new generation of ligands targeting the cannabinoid receptor type 2 (CB2R), namely JR compounds, which combine the pharmacophoric portion of the CB2R positive allosteric modulator (PAM), EC21a, with that of the CB2R selective orthosteric agonist LV62, both synthesized in our laboratories. The functional examination enabled us to identify JR14a, JR22a, and JR64a as the most promising compounds of the series. In the current study, we focused on the assessment of the bitopic (dualsteric) nature of these three compounds. Experiments in cAMP assays highlighted that only JR22a behaves as a CB2R bitopic (dualsteric) ligand. In parallel, computational studies helped us to clarify the binding mode of these three compounds at CB2R, confirming the bitopic (dualsteric) nature of JR22a. Finally, the potential of JR22a to prevent neuroinflammation was investigated on a human microglial cell inflammatory model.

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)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.013
GPT teacher head0.281
Teacher spread0.268 · 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
Published2023
Admission routes2
Has abstractyes

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