A cane toad (Rhinella marina) N-methyltransferase converts primary indolethylamines to tertiary psychedelic amines
Bibliographic record
Abstract
Psychedelic indolethylamines have emerged as potential medicines to treat several psychiatric pathologies. Natural sources of these compounds include ‘magic mushrooms' ( Psilocybe spp.), plants used to prepare ayahuasca, and toads. The skin and parotid glands of certain toads accumulate a variety of specialized metabolites including toxic guanidine alkaloids, lipophilic alkaloids, poisonous steroids, and hallucinogenic indolethylamines such as DMT, 5-methoxy-DMT, and bufotenin. The occurrence of psychedelics has contributed to the ceremonial use of toads, particularly among Mesoamerican peoples. Yet, the biosynthesis of psychedelic alkaloids has not been elucidated. Herein, we report a novel indolethylamine N -methyltransferase (RmNMT) from cane toad ( Rhinella marina ). The RmNMT sequence was used to identify a related NMT from the common toad, Bufo bufo . Close homologs from various frog species were inactive, suggesting a role for psychedelic indolethylamine biosynthesis in toads. Enzyme kinetic analyses and comparison with functionally similar enzymes showed that recombinant RmNMT was an effective catalyst and not product inhibited. The substrate promiscuity of RmNMT enabled the bioproduction of a variety of substituted indolethylamines at levels sufficient for purification, pharmacological screening, and metabolic stability assays. Since the therapeutic potential of psychedelics has been linked to activity at serotonergic receptors, we evaluated binding of derivatives at 5-HT 1A and 5-HT 2A receptors. Primary amines exhibited enhanced affinity at the 5-HT 1A receptor compared with tertiary amines. With the exception of 6-substituted derivatives, N,N -dimethylation also protected against catabolism by liver microsomes.
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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) | 0.001 | 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".