Inverse agonism: more than reverting constitutively active receptor signaling
Bibliographic record
Abstract
Seven-transmembrane receptors constitute one of the major families of proteins encoded by the genome. This type of receptor is one of the most important targets of the pharmaceutical industry, and many of the drugs with significant therapeutic action have been shown to be inverse agonists. Concepts regarding the mechanisms by which ligands activate and inactivate receptors are thought to be far more complex that a simple on-off switch. For both drug design and pharmacology principles, it is important to understand the mechanisms by which these drugs achieve their effects. Recent studies have demonstrated intriguing actions of inverse agonists. They have been shown not only to block constitutive responses of receptors but also to activate and regulate seven-transmembrane receptor signaling and trafficking. The activation of pathways by inverse agonists was shown to occur mainly via G-protein-independent mechanisms. These findings emphasize the importance of inverse agonism as a principle of receptor regulation. In this paper, we will review the evidence supporting inverse agonist promoted signaling and trafficking.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".