A Polymorphic Protease-activated Receptor 2 (PAR2) Displaying Reduced Sensitivity to Trypsin and Differential Responses to PAR Agonists
Bibliographic record
Abstract
Protease-activated receptor 2 (PAR2) is a trypsin-activated member of a family of G-protein-coupled PARs. We have identified a polymorphic form of human PAR2 (PAR(2)F240S) characterized by a phenylalanine to serine mutation at residue 240 within extracellular loop 2, with allelic frequencies of 0.916 (Phe(240)) and 0.084 (Ser(240)) for the wild-type and mutant alleles, respectively. Elevations in intracellular calcium were measured in permanently transfected cell lines expressing the receptors. PAR(2)F240S displayed a significant reduction in sensitivity toward trypsin ( approximately 3.7-fold) and the PAR2-activating peptides, SLIGKV-NH(2) ( approximately 2.5-fold) and SLIGRL-NH(2) ( approximately 2.8-fold), but an increased sensitivity toward the selective PAR2 agonist, trans-cinnamoyl-LIGRLO-NH(2) ( approximately 4-fold). Increased sensitivity was also observed toward the selective PAR-1 agonist, TFLLR-NH(2) ( approximately 7-fold), but not to other PAR-1 agonists tested. Furthermore, we found that TLIGRL-NH(2) and a PAR4-derived peptide, trans-cinnamoyl-YPGKF-NH(2), were selective PAR(2)F240S agonists. By introducing the F240S mutation into rat PAR2, we observed shifts in agonist potencies that mirrored the human PAR(2)F240S, suggesting that Phe(240) is involved in determining agonist specificity of PAR2. Finally, differences in receptor signaling were paralleled in a cell growth assay. We suggest that the distinct pharmacological profile induced by this polymorphism will have important implications for the design of PAR-targeted agonists/antagonists and may contribute to, or be predictive of, an inflammatory disease.
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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 | 0.001 |
| 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".