Integrative Network Analysis Reveals Organizational Principles of the Endocannabinoid System
BackgroundThe endocannabinoid system (ECS) is a complex signaling network that regulates diverse physiological processes, including pain, mood, metabolism, and immune response, through coordinated interactions among receptors, enzymes, and lipid-derived ligands. Despite extensive research on individual ECS components, the systems-level organization and network resilience of the ECS remain underexplored. Here, we present a systems-level analysis of the ECS that integrates protein-protein and protein-chemical interactions into a unified network framework. MethodsWe constructed integrated ECS networks that combine protein-protein and protein-chemical interactions, utilizing data from multiple public databases. Network analyses were performed in Python using NetworkX to assess molecular connectivity and interaction topology. We utilized centrality measures to identify major hubs, employed community detection algorithms to examine the clustering of nodes, and performed targeted perturbations by sequentially removing the top-ranked nodes based on degree and betweenness centrality to assess network robustness. ResultsCentrality analyses identified the primary cannabinoid receptors, cannabinoid receptor 1 (CNR1) and cannabinoid receptor 2 (CNR2), as major hubs with extensive connectivity to endogenous and exogenous ligands. Non-canonical receptors, including transient receptor potential vanilloid 1 (TRPV1) and G-protein coupled receptor 55 (GPR55), also emerged as highly ranked nodes across multiple centrality measures, underscoring their integrative roles within the ECS signaling pathway. Community detection revealed biologically meaningful modules centered around receptor and metabolic clusters, with CNR1, CNR2, anandamide (AEA), 2-arachidonoylglycerol (2-AG), and major phytocannabinoids maintaining key network connectivity. Perturbation analyses demonstrated that removal of top hubs, particularly CNR1, caused pronounced losses in edge connectivity and disrupted signaling pathways among cannabinoids. However, the redistribution of influence toward CNR2 and GPR55 under multi-node removal conditions revealed compensatory plasticity and resilience within the ECS network. ConclusionThis systems-level study highlights the hierarchical and robust architecture of the ECS. The identification of hub nodes, functional communities, and compensatory mechanisms provides insight into how the ECS maintains signaling integrity in the face of perturbation. These findings establish a network-based framework for studying cannabinoid biology and may inform future therapeutic strategies targeting the ECS and its interacting molecular pathways.