Temperature‐dependent variations of ligand‐receptor contact points in hAT<sub>1</sub>
Bibliographic record
Abstract
Photoaffinity labelling is regularly used to investigate proteins, including peptidergic G protein-coupled receptors (GPCR). To this purpose benzophenone photolabels have been widely used to identify many contact residues in ligand-binding pockets. The three-dimensional binding environment of the human angiotensin II type 1 receptor hAT(1) has been determined using an iterative methionine mutagenesis strategy based on the photochemical properties and preferential incorporation of benzophenone onto methionine. This has led to the construction of a ligand-bound receptor structure. The present study investigated the effect of temperature on the accessibility of some of these contact points. The hAT(1) receptor and two representative Met mutants (H256M-hAT(1) and F293M-hAT(1)) from the iterative mutagenesis study were photolabelled with the benzophenone-ligand (125)I-[Sar(1), Bpa(8)]AngII at temperatures ranging from - 15 degrees C to 37 degrees C. Labelled receptors were partially purified and digested with cyanogen bromide to identify the contact points or segments. There were no changes in receptor contacts or labelling in the 7th transmembrane domains (TMD) of hAT(1) and F293M-hAT(1) across the temperature range. However, a temperature-dependent change in the ligand-receptor contact of H256M-hAT(1) was observed. At - 15 degrees C, H256M labelling was identical to that of hAT(1), indicating that the interaction was specific to the 7th TMD. Significant labelling changes were observed at higher temperatures and at 37 degrees C labelling occurred almost exclusively at mutated residue H256M-hAT(1) in the 6th TMD. Simultaneous competitive labelling of different areas of this target protein indicated that the ligand-receptor structure became increasingly fluctual at physiological temperatures, while a more compact, low mobility, and low energy conformation prevailed at low temperatures.
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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 | 0.000 | 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 | 0.001 |
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".