Using Förster Resonance Energy Transfer (FRET) to Understand the Ubiquitination Landscape
Bibliographic record
Abstract
Förster resonance energy transfer (FRET) is a fluorescence technique that allows quantitative measurement of protein interactions, kinetics and dynamics. This review covers the use of FRET to study the structures and mechanisms of ubiquitination and related proteins. We survey FRET assays that have been developed where donor and acceptor fluorophores are placed on E1, E2 or E3 enzymes and ubiquitin (Ub) to monitor steady-state and real-time transfer of Ub through the ubiquitination cascade. Specialized FRET probes placed on Ub and Ub-like proteins have been developed to monitor Ub removal by deubiquitinating enzymes (DUBs) that result in a loss of a FRET signal upon cleavage of the FRET probes. FRET has also been used to understand conformational changes in large complexes such as multimeric E3 ligases and the proteasome, frequently using sophisticated single molecule methods. Overall, FRET is a powerful tool to help unravel the intricacies of the complex ubiquitination system.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".