Role of Detergents in Conformational Exchange of a G Protein-coupled Receptor
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Bibliographic record
Abstract
The G protein-coupled β(2)-adrenoreceptor (β(2)AR) signals through the heterotrimeric G proteins G(s) and G(i) and β-arrestin. As such, the energy landscape of β(2)AR-excited state conformers is expected to be complex. Upon tagging Cys-265 of β(2)AR with a trifluoromethyl probe, (19)F NMR was used to assess conformations and possible equilibria between states. Here, we report key differences in β(2)AR conformational dynamics associated with the detergents used to stabilize the receptor. In dodecyl maltoside (DDM) micelles, the spectra are well represented by a single Lorentzian line that shifts progressively downfield with activation by appropriate ligand. The results are consistent with interconversion between two or more states on a time scale faster than the greatest difference in ligand-dependent chemical shift (i.e. >100 Hz). Given that high detergent off-rates of DDM monomers may facilitate conformational exchange between functional states of β(2)AR, we utilized the recently developed maltose-neopentyl glycol (MNG-3) diacyl detergent. In MNG-3 micelles, spectra indicated at least three distinct states, the relative populations of which depended on ligand, whereas no ligand-dependent shifts were observed, consistent with the slow exchange limit. Thus, detergent has a profound effect on the equilibrium kinetics between functional states. MNG-3, which has a critical micelle concentration in the nanomolar regime, exhibits an off-rate that is 4 orders of magnitude lower than that of DDM. High detergent off-rates are more likely to facilitate conformational exchange between distinct functional states associated with the G protein-coupled receptor.
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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) | 0.001 | 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 it