Dissecting the Chemistry of Nicotinic Receptor-Ligand Interactions with Infrared Difference Spectroscopy
Bibliographic record
Abstract
The physical interactions that occur between the nicotinic acetylcholine receptor from Torpedo and the agonists carbamylcholine and tetramethylamine have been studied using both conventional infrared difference spectroscopy and a novel double-ligand difference technique. The latter was developed to isolate vibrational bands from residues in a membrane receptor that interact with individual functional groups on a small molecule ligand. The binding of either agonist leads to an increase in vibrational intensity at frequencies centered near 1663, 1655, 1547, 1430, and 1059 cm(-1) indicating that both induce a conformational change from the resting to the desensitized state. Vibrational shifts near 1580, 1516, 1455, 1334, and between 1300 and 1400 cm(-1) are assigned to structural perturbations of tyrosine and possibly both tryptophan and charged carboxylic acid residues upon the formation of receptor-quaternary amine interactions, with the relatively intense feature near 1516 cm(-1) indicating a key role for tyrosine. Other vibrational bands suggest the involvement of additional side chains in agonist binding. Two side-chain vibrational shifts from 1668 and 1605 cm(-1) to 1690 and 1620 cm(-1), respectively, could reflect the formation of a hydrogen bond between the ester carbonyl of carbamylcholine and an arginine residue. The results demonstrate the potential of the double-ligand difference technique for dissecting the chemistry of membrane receptor-ligand interactions and provide new insight into the nature of nicotinic receptor-agonist interactions.
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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 | 0.001 |
| 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 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".