Theoretical investigation of the conformational intricacies and thermodynamic functions of noradrenaline
Bibliographic record
Abstract
Noradrenaline is a neurotransmitter that is involved in various psychological processes. In the neurotransmission process, noradrenaline binds to an adrenergic receptor by forming a complex of hydrogen bonds between its two catechol ring hydroxyl groups and the amino acid residues of adrenergic receptors. Although the two catechol ring hydroxyl groups play a crucial role in making hydrogen bonds to the binding site of the adrenergic receptor, the contribution of the catechol ring hydroxyl groups to the intramolecular stability that may affect docking has not been fully studied. To reveal the specific role that the catechol ring hydroxyl groups might play in stabilizing noradrenaline, the quantum chemical computations of geometry optimization and thermodynamic functions of N-protonated noradrenaline conformers were performed at both the B3LYP/6–31G(d,p) and G3MP2B3 levels of theory, using the Gaussian 03 program. The results were compared with those of N-protonated β-hydroxy-β-phenylethylamine, which is identical to noradrenaline except it lacks two catechol ring hydroxyl groups. For the first time, post-Hartree–Fock computations were used to obtain thermodynamic functions to establish relative stabilities of all possible conformers of N-protonated noradrenaline. In this study, 18 distinct structures of N-protonated noradrenaline were revealed, and the catechol ring hydroxyl groups were found to affect noradrenaline stability positively or negatively depending on the conformational orientations. On the basis of available experimental results, the issue that the least stable conformation of two catechol ring hydroxyl groups may be involved in the docking process has been raised. These findings may be useful in synthesis of derivatives of noradrenaline in drug design.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".