The Forgotten Serine
Bibliographic record
Abstract
Previous work in the beta(2)-adrenergic receptor demonstrated critical interactions between Ser-204 and Ser-207 in the fifth membrane-spanning segment and the meta-OH and para-OH, respectively, of catecholamine agonists (Strader, C. D., Candelore, M. R., Hill, W. S., Sigal, I. S., and Dixon, R. A. (1989) J. Biol. Chem. 264, 13572-13578). Using the substituted cysteine accessibility method in the beta(2)-adrenergic receptor, we have found that in addition to Ser-204 and Ser-207, Ser-203 is also accessible on the surface of the binding-site crevice and is occluded by bound agonist. Mutation of Ser-203 to Ala, Val, or Cys reduced the binding affinity and adenylyl cyclase-activating potency of agonists containing a meta-OH, whereas their affinities and potencies were largely preserved by mutation of Ser-203 to Thr, which maintained an OH at this position. Thus both Ser-203 and Ser-204 appear to interact with the meta-OH of catecholamines, perhaps through a bifurcated H bond. Furthermore, the removal of the OH at position 203 led to a significant loss of affinity of antagonists with nitrogen in their heterocyclic ring structure. The greatest effect was seen with pindolol, a partial agonist, suggesting that a H bond between the heterocyclic ring and Ser-203 may play a role in partial agonism. In contrast, the affinities of antagonists such as propranolol or alprenolol, which have cyclic structures without H-bonding capability, were unaltered after mutation of Ser-203.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.081 | 0.046 |
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".