Signaling profile of a new PAR2 inhibitor with anti‐inflammatory effects
Bibliographic record
Abstract
The protease‐activated receptor‐2 (PAR2) belongs to an atypical subfamily of G protein–coupled receptors (GPCR), activated by the proteolytic cleavage of their N‐terminal region by enzymes such as thrombin or trypsin. This cleavage exposes a region of the N‐terminal extracellular domain (the “tethered ligand”) to bind to the extracellular loop 2 and others domains of the PAR2. This results in the stabilization of an active conformation of the receptor. Short synthetic peptides mimicking the tethered ligand sequence are also able to activate PAR2. This subfamily of GPCR is largely involved in inflammatory responses and may therefore represent a promising therapeutic target for the treatment of immune‐mediated inflammatory diseases. It is now recognized that activated‐GPCRs can engage multiple signaling pathways and that specific ligands can selectively promote the engagement of different subsets of these pathways. We therefore characterized the functional selectivity of PAR2 modulators in the context of their potential action as anti‐inflammatory drugs. Elucidating the various signaling pathways should help directed targeting in the quest for therapeutic efficacy; and reciprocally minimize undesirable side effects. For this, we have established the exhaustive signaling signatures of PAR2 modulators using bioluminescence resonance energy transfer (BRET)‐based biosensors in heterologous and native human cell based systems. First, the repertoire of signaling pathways that can be triggered by trypsin and a PAR2 activating peptide (SLIGKV‐NH 2 ) were established. We then identified a compound with a particularly interesting signaling profile among the different modulators tested. Indeed, we showed that compound C5 acts as a negative allosteric modulator (NAM) for the Gα 13 /Gα q /DAG/Ca 2+ /PKC signaling pathways activated by both agonists (SLIGKV‐NH 2 or trypsin) whereas it has no effect on Gα 12 /Gα i2 /Gα oA /Gα oB pathways activated by trypsin or SLIGKV‐NH 2 and acts as a positive allosteric modulator (PAM) for βarrestin2 recruitment induced by the short peptide. Using a mouse BRET‐based signaling array, we showed that C5 presents a similar signaling profile on the mouse PAR2, establishing inter‐species translation of the results obtained with human receptor in rodent model. Finally, we have evaluated the anti‐inflammatory activity of C5 by measuring its impact on (i) cytokines secretion induced by PAR2 in HCT‐116 cells and (ii) volume of paw edema in rodent inflammatory models. Our preliminary data indicated that C5 presents anti‐inflammatory properties in vitro and in vivo . Overall, our results suggest that C5, by selectively inhibiting PAR2‐induced Gα 13 /Gα q /DAG/Ca 2+ /PKC signaling pathways, leads to the anti‐inflammatory effects observed in vitro and in vivo . PAR2 functional selectivity highlights the opportunity to design new drugs that specifically block PAR2‐activated signaling pathway in disease, without affecting beneficial PAR2 signaling in normal physiology. Support or Funding Information Canadian Institutes of Health Research This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".