Using BRET to Detect Ligand-Specific Conformational Changes in Preformed Signalling Complexes
Bibliographic record
Abstract
Bioluminescence energy transfer (BRET) has become a powerful tool to study protein-protein interactions and conformational changes among interacting proteins. In particular, BRET assays performed in living cells have revealed that heptahelical receptors (7TMRs), heterotrimeric G proteins and their proximal effectors form constitutive signalling complexes. BRET technology has also allowed us to demonstrate that these multimeric protein arrays remain intact throughout initial stages of receptor signalling, thus providing a platform for direct transmission of conformational information from activated receptors to downstream signalling partners. A clear example of the latter are the distinct intermolecular re-arrangements undergone by 7TMRs and G protein subunits following activation of the receptor by different ligands. Here we present protocols describing the type of BRET assay that has been used to reveal the existence of constitutive signalling arrays formed by 7TMRs and proximal signalling partners as well as the ability of complex components to undergo ligand-specific conformational changes.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".