A Novel Biased Allosteric Compound Inhibitor of Parturition Selectively Impedes the Prostaglandin F2α-mediated Rho/ROCK Signaling Pathway
Bibliographic record
Abstract
The prostaglandin F2alpha (PGF2alpha) receptor (FP) is a key regulator of parturition and a target for pharmacological management of preterm labor. However, an incomplete understanding of signaling pathways regulating myometrial contraction hinders the development of improved therapeutics. Here we used a peptidomimetic inhibitor of parturition in mice, PDC113.824, whose structure was based on the NH(2)-terminal region of the second extracellular loop of FP receptor, to gain mechanistic insight underlying FP receptor-mediated cell responses in the context of parturition. We show that PDC113.824 not only delayed normal parturition in mice but also that it inhibited both PGF2alpha- and lipopolysaccharide-induced preterm labor. PDC113.824 inhibited PGF2alpha-mediated, G(alpha)(12)-dependent activation of the Rho/ROCK signaling pathways, actin remodeling, and contraction of human myometrial cells likely by acting as a non-competitive, allosteric modulator of PGF2alpha binding. In contrast to its negative allosteric modulating effects on Rho/ROCK signaling, PDC113.824 acted as a positive allosteric modulator on PGF2alpha-mediated protein kinase C and ERK1/2 signaling. This bias in receptor-dependent signaling was explained by an increase in FP receptor coupling to G(alpha)(q), at the expense of coupling to G(alpha)(12). Our findings regarding the allosteric and biased nature of PDC113.824 offer new mechanistic insights into FP receptor signaling relevant to parturition and suggest novel therapeutic opportunities for the development of new tocolytic drugs.
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 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 | 0.001 | 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".