Trifluorinated Keto–Enol Tautomeric Switch in Probing Domain Rotation of a G Protein-Coupled Receptor
Bibliographic record
Abstract
Conformational dynamics and transitions of biologically active molecules are pivotal for understanding the physiological responses they elicit. In the case of receptor activation, there are major implications elucidating disease mechanisms and drug discovery innovation. Yet, incorporation of these factors into drug screening systems remains challenging in part due to the lack of suitable approaches to include them. Here, we present a novel strategy to probe the GPCR domain rotation by utilizing the 19fluorine signal variability of a trifluorinated keto–enol (TFKE) chemical equilibrium. The method takes advantage of the high sensitivity of the TFKE tautomerism toward microenvironmental changes resulting from receptor conformational transitions upon ligand binding. We validated the method using the adenosine A2AR receptor as a model system in which the TFKE was attached to two sites exhibiting opposing motions upon ligand binding, namely, V229C6.31 on transmembrane domain VI (TM6) and A289C7.54 on TM7. Our results demonstrated that the TFKE switch was an excellent reporter for the domain rotation and could be used to study the conformational transition and dynamics of relative domain motions. Although further studies are needed in order to establish a quantitative relationship between the rotational angle and the population distribution of different components in a particular system, the research presented here provides a foundation for its application in studying receptor domain rotation and dynamics, which could be useful in drug screening efforts.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".