DRUGS, DIMERS, AND MUTATIONS: INVESTIGATING THE EFFECTS OF LIGANDS AND A ?2-ADRENERGIC POLYMORPHISM ON HOMO/HETERODIMERIZATION OF ?2-ADRENERGIC AND ANGIOTENSIN II TYPE 1 RECEPTORS
Bibliographic record
Abstract
GPCRs are known to form dimeric structures, and this affects their pharmacological properties. The ?2AR and AT1aR are GPCRs that are involved the regulation of the adrenergic and renin-angiotensin systems. The ?2AR is polymorphic at position 164, affecting its responsiveness to adrenergic ligands. Both receptors have been shown to form dimers, but little is known on how dimerization affects their trafficking and signalling following ligand treatments. Plasma membrane localization, arrestin-2 recruitment, and G-protein interactions were determined between receptor dimers using molecular biological techniques. This study demonstrates that the formation of heterodimers can change the expected response to ligand treatments, along with associated trafficking events. It was determined that ligands bind to dimers, resulting in conformational changes to the dimeric complexes. Both the ?2AR and AT1aR are targeted in cardiovascular disease and this research demonstrates the importance of dimerization when prescribing drug therapies to avoid potential unwanted drug side effects.
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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".