FAAH inhibition

FAAH inhibition. Slows fatty acid amide hydrolase, the enzyme that breaks down anandamide and the related fatty-acid amides. Raises anandamide tone rather than adding an outside agonist. Additive with anything else acting on the same system, and the clinical FAAH-inhibitor programmes are a reminder that an enzyme inhibitor is not inherently mild.

MAGL inhibition. Slows monoacylglycerol lipase, which performs the large majority of 2-AG hydrolysis in brain. Raises 2-AG and simultaneously diverts it away from the arachidonic-acid pool. Sustained complete blockade produces CB1 desensitisation in animals, so more inhibition is not simply more effect.

Endocannabinoid transport inhibition. Slows the movement of anandamide and 2-AG out of the synapse and into the cell. A third route to the same raised tone, and one that stacks with FAAH and MAGL inhibition because the mechanisms are separate. The transport mechanism itself is not settled science.

CB1 agonism (partial). Activates the CB1 receptor as a partial agonist, as the plant cannabinoids do. Partial agonism has a ceiling: beyond a point more drug does not produce more receptor activation. That ceiling is the reason cannabis does not depress respiration to the point of death.

CB1 FULL agonism. Activates CB1 with full efficacy and usually with far higher affinity — the synthetic cannabimimetics. There is no ceiling. This is the pharmacological difference behind the seizures, tachyarrhythmias, agitated delirium and deaths recorded for the synthetic cannabinoids and not for cannabis.

CB2 agonism. Activates the peripheral and immune-cell cannabinoid receptor. Not psychoactive. Relevant here because several very common dietary constituents do it, so it is a real pharmacology hiding in the spice rack rather than an exotic one.

What acts on it

What is affected by it

What a clean result means here

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.

In this dataset

  • Monoamine oxidase inhibition (prescription MAOIs, RIMAs, linezolid, methylene blue, harmala alkaloids)
  • 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
  • The endocannabinoid enzymes and transport: FAAH, MAGL, endocannabinoid membrane transport, CB1 and CB2
  • Additive CNS depression and GABA-A positive modulation — the alcohol / benzodiazepine / opioid / kava axis
  • The phytocannabinoids delta-9-THC, cannabidiol and the converted cannabinoids, as both substrates and inhibitors
  • Synthetic full CB1 agonists as a class, and why they are pharmacologically unlike cannabis
  • CYP2E1, and phase-2 glucuronidation and sulfation where a specific entry names them
  • The sedative and potentiator botanicals of the kava literature, and dietary L-dopa from Mucuna

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.
  • Bleeding and antiplatelet risk, hypoglycaemia, anticholinergic load, and most other pharmacodynamic axes beyond the ones listed above. Additive CNS depression and GABA-A modulation ARE now modelled — see the covers list — but the absence of a sedation finding still only means the agents you named are not on that axis in this dataset.
  • 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.
  • Bleeding and antiplatelet risk, which is the mechanism that matters most for garlic, ginkgo and several other common supplements. It is not modelled at all, so a clean result says nothing about it.
  • Whether any of the natural FAAH, MAGL or transport inhibition reported in vitro occurs at all at a dose a person would take. For most of these compounds nobody has measured it.
  • The actual contents of an unregulated cannabinoid product. This engine models named compounds; an unidentified isomer or side-product in a converted-cannabinoid product is outside it by construction.
  • Dose. Every cannabinoid interaction here scales with dose, and consumer product labelling for this category is repeatedly found inaccurate in published surveys.
  • Inhalation-specific hazards — thermal degradation products, diluents chosen for rheology rather than for inhalation toxicology, and carrier and adulterant contamination.

101 substances, 33 mechanisms, 101 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

  1. Nicolussi S, Viveros-Paredes JM, Gachet MS, et al. (2014). Guineensine is a novel inhibitor of endocannabinoid uptake showing cannabimimetic behavioral effects in BALB/c mice. Pharmacological Research. doi:10.1016/j.phrs.2013.12.010
  2. Nicolussi S, Gertsch J (2015). Endocannabinoid transport revisited. Vitamins and Hormones. doi:10.1016/bs.vh.2014.12.011
  3. Gertsch J, Leonti M, Raduner S, et al. (2008). Beta-caryophyllene is a dietary cannabinoid. PNAS. doi:10.1073/pnas.0803601105
  4. Ligresti A, Villano R, Allarà M, Ujváry I, Di Marzo V (2012). Kavalactones and the endocannabinoid system: the plant-derived yangonin is a novel CB1 receptor ligand. Pharmacological Research. doi:10.1016/j.phrs.2012.04.003
  5. Pertwee RG (2008). The diverse CB1 and CB2 receptor pharmacology of three plant cannabinoids: delta9-tetrahydrocannabinol, cannabidiol and delta9-tetrahydrocannabivarin. British Journal of Pharmacology. doi:10.1038/sj.bjp.0707442
  6. Ligresti A, De Petrocellis L, Di Marzo V (2016). From Phytocannabinoids to Cannabinoid Receptors and Endocannabinoids: Pleiotropic Physiological and Pathological Roles Through Complex Pharmacology. Physiological Reviews. doi:10.1152/physrev.00002.2016
  7. Atwood BK, Huffman J, Straiker A, Mackie K (2010). JWH018, a common constituent of "Spice" herbal blends, is a potent and efficacious cannabinoid CB1 receptor agonist. British Journal of Pharmacology. doi:10.1111/j.1476-5381.2010.00787.x
  8. Huffman JW, Dai D, Martin BR, Compton DR (1994). Design, synthesis and pharmacology of cannabimimetic indoles. Bioorganic & Medicinal Chemistry Letters. doi:10.1016/S0960-894X(01)80143-1
  9. Tait RJ, Caldicott D, Mountain D, Hill SL, Lenton S (2016). A systematic review of adverse events arising from the use of synthetic cannabinoids and their associated treatment. Clinical Toxicology. doi:10.3109/15563650.2015.1110590
  10. Tung C-W, Fung K-M, Hsu C-C, Tseng T-S (2021). Discovery of 8-prenylnaringenin from hop (Humulus lupulus L.) as a potent monoacylglycerol lipase inhibitor for treatments of neuroinflammation and Alzheimer's disease. RSC Advances. doi:10.1039/d1ra05311f
  11. Alasmari M, Bӧhlke M, Kelley C, Maher T, Pino-Figueroa A (2018). Inhibition of Fatty Acid Amide Hydrolase (FAAH) by Macamides. Molecular Neurobiology. doi:10.1007/s12035-018-1115-8
  12. Thors L, Belghiti M, Fowler CJ (2008). Inhibition of fatty acid amide hydrolase by kaempferol and related naturally occurring flavonoids. British Journal of Pharmacology. doi:10.1038/bjp.2008.237
  13. Thors L, Eriksson J, Fowler CJ (2007). Inhibition of the cellular uptake of anandamide by genistein and its analogue daidzein in cells with different levels of fatty acid amide hydrolase-driven uptake. British Journal of Pharmacology. doi:10.1038/sj.bjp.0707401
  14. Raduner S, Majewska A, Chen JZ, et al. (2006). Alkylamides from Echinacea are a new class of cannabinomimetics: cannabinoid type 2 receptor-dependent and -independent immunomodulatory effects. Journal of Biological Chemistry. doi:10.1074/jbc.M601074200

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.

Last reviewed . All interaction pages.