Monitoring Protein‐Protein Interactions in Living Cells by Bioluminescence Resonance Energy Transfer (<scp>BRET</scp>)
Bibliographic record
Abstract
Bioluminescence resonance energy transfer (BRET) allows monitoring of protein-protein interactions in real time in living cells. One candidate interacting protein is fused to a luminescent energy donor, such as Renilla luciferase, and the other to a fluorescent energy acceptor, such the green fluorescent protein (GFP), and the two are then coexpressed in the same cells. If the two proteins interact, their close proximity allows nonradiative energy transfer (BRET) between the luciferase and the GFP. BRET does not occur if the two proteins are separated by more than 100 A, making the technique ideal for monitoring protein-protein interactions in biological systems. This unit describes the use of BRET to study constitutive and agonist-promoted interactions among signaling molecules, as illustrated by the homodimerization of the CXCR4 receptor and the recruitment of beta-arrestin2 to agonist-activated G-protein-coupled receptors. This noninvasive and homogeneous assay provides a robust and sensitive proteomic platform with applications for basic science research and drug discovery.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".