Serotonin 2A Receptor (5-HT<sub>2A</sub>R) Activation by 25H-NBOMe Positional Isomers: <i>In Vitro</i> Functional Evaluation and Molecular Docking
Bibliographic record
Abstract
Abstract Serotonergic psychedelics are defined as compounds having serotonin 2A receptor (5-HT2AR) activation as an important pharmacological mechanism. These compounds include the phenylalkylamine class, containing substances with e.g. 2C-X structures (phenethylamines) or their N-methoxybenzyl analogues (NBOMes). Besides their abuse potential, psychedelics are increasingly recognized for having therapeutic benefits. However, many psychedelics remain incompletely characterized, even concerning their structure–activity relationships. Here, five positional isomers of 25H-NBOMe, with two methoxy groups on the different positions of the phenyl ring of the phenethylamine moiety, were subjected to split-nanoluciferase assays assessing the in vitro recruitment of cytosolic proteins to the 5-HT2AR. Furthermore, molecular docking at the 5-HT2AR allowed estimation of which residues interact with the specific isomers’ methoxy groups. Although the optimal substitution pattern of N-unsubstituted phenylalkylamines has been extensively studied, this is the first comparative evaluation of the functional effects of the positioning of the methoxy groups in the phenethylamine moiety of NBOMes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.002 | 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".