The endocannabinoidomes: Pharmacological redundancy and promiscuity, and multi-kingdom variety of sources and molecular targets
Bibliographic record
Abstract
The endocannabinoid system (eCB) is a complex signaling network discovered in mammals during the 1980s-1990s. It conventionally revolves around two arachidonic acid-derived mediators, N-arachidonoyl-ethanolamine (anandamide) and 2-arachidonoyl-glycerol; their main receptors, the cannabinoid receptors of type 1 (CB1) and type 2 (CB2), and the transient receptor potential vanilloid-1 channels; and the enzymes responsible for their biosynthesis and degradation. However, drawing on these discoveries, numerous eCB-like signaling lipids beyond the classical eCBs, have been unveiled, together with their receptors and metabolic enzymes, thus forming a more complex signaling network known as the endocannabinoidome (eCBome). This review explores the physiology, pharmacological complexity, and molecular targets of the mammalian eCBome, highlighting its versatility and redundancy in the context of global health. Emerging mediators, metabolic pathways and mechanisms, receptors, and their implications in human physiology and pathology are described, particularly concerning metabolic disorders, pain, inflammation, neurodegenerative diseases, and cancer. The importance of other "eCBomes" in nonmammalian forms of life that constitute the external and internal environments of mammals is also discussed for the first time in this context. The overarching objective of this article is to gain insights into the potential of eCBome-based therapeutic strategies aimed at enhancing both human and environmental well-being. SIGNIFICANCE STATEMENT: Lipid-based signaling molecules are ubiquitous in nature, yet their study remains challenging due to intricate regulatory mechanisms. Among lipid signaling pathways, the endocannabinoid (eCB) system and its extended version, the endocannabinoidome (eCBome), are particularly remarkable. Comprising hundreds of mediators, and dozens of receptors and metabolic enzymes, the eCBome regulates critical physiological processes not only in mammals but also across diverse organisms, including plants, fungi, and bacteria. This article examines the evolutionary and functional diversity of eCBomes and highlights their untapped potential as multikingdom therapeutic targets to address pressing challenges in global health.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".