A 5-HT2A agonist whose active form, psilocin, is cleared by CYP2D6 and by UGT glucuronidation — which is the pharmacological basis of the oilahuasca corpus' potentiation claims.
Also known as: psilocin, magic mushrooms, Psilocybe. Category: plant.
What it does, mechanism by mechanism
Direct serotonin receptor agonism — agonist, strong
Binds serotonin receptors directly (5-HT1A/1B/1D/2A). Contributes to serotonergic load; 5-HT1A/2A agonism is the axis implicated in serotonin toxicity.
Slows the enzyme handling many antidepressants, antipsychotics, opioids and psilocin. For a prodrug like codeine the effect inverts — less active drug, not more.
Psilocin is a CYP2D6 substrate; inhibiting CYP2D6 raises exposure. This is the archive's own potentiation mechanism and it cuts both ways — the same rule that predicts a stronger experience predicts an unintended overdose.
A clean result means NO DOCUMENTED INTERACTION IN THIS DATASET. It does not mean safe, and it is not a clearance. Most substances are not in this dataset at all, and for many pairs that are, nobody has ever studied the combination.
Serotonergic drugs and the serotonin-toxicity mechanism
Dietary tyramine and L-dopa loads
The major cytochrome P450 pathways: CYP3A4, CYP2D6, CYP1A2, CYP2C9, CYP2C19 — inhibition and induction
P-glycoprotein inhibition and induction
11β-HSD2 inhibition (the licorice mechanism) and the potassium consequences that follow it
QT prolongation as an additive pharmacodynamic axis
Culinary seasonings and common foods with documented pharmacological activity
A selected set of narrow-therapeutic-index drugs where those shifts matter most
Not in this dataset
Any substance not named in this dataset — which is most substances. There are tens of thousands of marketed drugs and this table holds fewer than a hundred entries.
Phase-2 conjugation (UGT, SULT, NAT2, COMT) except where a specific entry names it. The oilahuasca corpus turns heavily on phase 2 and this engine models it only in passing.
Pharmacogenomics. CYP2D6 and CYP2C19 are strongly polymorphic; a poor metaboliser and an ultra-rapid metaboliser can have opposite outcomes from the same pair, and this engine does not know your genotype.
Dose, timing, duration, formulation and route — all of which change whether a documented interaction is clinically real for you.
Renal and hepatic impairment, age, pregnancy, and body composition.
Additive sedation, respiratory depression, bleeding risk, hypoglycaemia and most other pharmacodynamic axes beyond the ones listed above.
Herb–herb interactions outside the named entries, and essentially the whole botanical world: most plants have no interaction literature at all.
Allergy, intolerance, and contamination or adulteration of unregulated products.
Anything published after the last-reviewed date below.
72 substances, 20 mechanisms,
64 citations. Last reviewed .
Primary literature (every DOI resolved against the Crossref API) and FDA drug labelling. There is no free, openly-licensed, comprehensive drug-interaction dataset to draw on; NLM retired its Drug Interaction API on 2024-01-02 and DrugBank's interaction set is a commercial licence.
References
Boyer EW, Shannon M (2005). The Serotonin Syndrome. New England Journal of Medicine. doi:10.1056/NEJMra041867
Flockhart DA, Thacker D, McDonald C, Desta Z (2021). The Flockhart Cytochrome P450 Drug-Drug Interaction Table. Division of Clinical Pharmacology, Indiana University School of Medicine. https://drug-interactions.medicine.iu.edu
Every DOI above was resolved against the Crossref API on 2026-09-09 and the returned
title checked against the one printed here. Three DOIs in the first draft resolved to real but different
papers and were corrected before publication.