Selectivity profiling of the novel EP<sub>2</sub> receptor antagonist, PF‐04418948, in functional bioassay systems: atypical affinity at the guinea pig EP<sub>2</sub> receptor
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Understanding the role of the EP(2) receptor has been hampered by the lack of a selective antagonist. Recently, a selective EP(2) receptor antagonist, PF-04418948, has been discovered. The aim of this study was to demonstrate the selectivity profile of PF-04418948 for the EP(2) receptor over other EP receptors using a range of isolated tissue systems. EXPERIMENTAL APPROACH: PF-04418948 was profiled on a range of isolated tissues to assess its EP receptor potency and selectivity: ONO-DI-004-induced contraction of guinea pig trachea (EP(1)); ONO-AE1-259 and PGE(2)- induced relaxation of mouse and guinea pig trachea (EP(2)); PGE(2)-induced depolarization of guinea pig isolated vagus (EP(3)); PGE(2)-induced relaxation of human and rat trachea (EP(4)). PF-04418948 was also profiled in functional murine TP, IP, DP and FP receptor assays. KEY RESULTS: In bioassay systems, where assessment of potency/selectivity is made against the 'native' receptor, PF-04418948 only acted as an antagonist of EP(2) receptor-mediated events. PF-04418948 competitively inhibited relaxations of murine and guinea pig trachea induced by ONO-AE1-259 and PGE(2) respectively. However, the affinity of PF-04418948 was not equal in the two preparations. CONCLUSIONS AND IMPLICATIONS: Using a wide range of bioassay systems, we have demonstrated that PF-04418948 is a selective EP(2)-receptor antagonist. Interestingly, an atypically low affinity was found on the guinea pig trachea, questioning its utility as an EP(2) receptor assay system. Nevertheless, this compound should be an invaluable tool for investigating the biological activity of PGE(2) and the role of EP(2) receptors in health and disease.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".