Mechanism of action of a nanomolar potent, allosteric antagonist of the thyroid‐stimulating hormone receptor
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Graves' disease (GD) is an autoimmune disease in which the thyroid is overactive, producing excessive amounts of thyroid hormones, caused by thyroid-stimulating hormone (TSH) receptor-stimulating immunoglobulins (TSIs). Many GD patients also suffer from thyroid eye disease (Graves' ophthalmopathy or GO), as TSIs also activate TSH receptors in orbital tissue. We recently developed low molecular weight (LMW) TSH receptor antagonists as a novel therapeutic strategy for the treatment of GD and GO. Here, we determined the molecular pharmacology of a prototypic, nanomolar potent LMW TSH receptor antagonist, Org 274179-0. EXPERIMENTAL APPROACH: Using CHO cells heterogeneously expressing human TSH receptors and rat FRTL-5 cells endogenously expressing rat TSH receptors, we determined the potency and efficacy of Org 274179-0 at antagonizing TSH- and TSI-induced TSH receptor signalling and its cross-reactivity at related follicle-stimulating hormone and luteinizing hormone receptors. We analysed the allosteric mode of interaction of Org 274179-0 and determined whether it is an inverse agonist at five naturally occurring, constitutively active TSH receptor mutants. KEY RESULTS: Nanomolar concentrations of Org 274179-0 completely inhibited TSH (and TSI)-mediated TSH receptor activation with little effect on the potency of TSH, in accordance with an allosteric mechanism of action. Conversely, increasing levels of TSH receptor stimulation only marginally reduced the antagonist potency of Org 274179-0. Org 274179-0 fully blocked the increased basal activity of all the constitutively active TSH receptor mutants tested with nanomolar potencies. CONCLUSIONS AND IMPLICATIONS: Nanomolar potent TSH receptor antagonists like Org 274179-0 have therapeutic potential for the treatment of GD and GO.
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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 | 0.000 | 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) | 0.000 | 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".