Identification and structural characterization of CB1 receptor antagonists: A comprehensive virtual screening and molecular dynamics study of arachidin-2 Academic Article in Scopus uri icon

abstract

  • The cannabinoid receptor 1 (CB1) is an essential component of the endocannabinoid system, responsible for regulating various physiological processes such as pain, mood, and appetite. Despite increasing interest in the therapeutic potential of CB1 modulators, the precise mechanisms by which small molecules modulate receptor activity¿particularly without fully transitioning between active and inactive states¿remain partially understood. In this study, the complexity of CB1¿ligand interactions was evaluated for the inactive CB1 state. A comprehensive pipeline, integrating ligand-based similarity search, 2D fingerprint-based reverse virtual screening and molecular dynamics (MD) simulations, identified compounds with core scaffolds commonly found in bioactive natural products, such as stilbenoids and polyphenolic compounds. Arachidin-2 (AR2) and a polyphenolic derivative were subjected to extended MD simulations, revealing their ability to stabilize the inactive CB1 state across key helices. The distinct stability differences observed in the helices HI, HIV, and HVI of the active CB1 state further highlighted ligand-specific conformational dynamics. A comparative analysis with co-crystallized synthetic ligands AM6538 and AM841 demonstrated the distinct binding behaviors of natural and synthetic ligands. AR2 showed more favorable binding to the inactive form (¿22.0 kcal/mol) than to the active state. Similarly, the polyphenolic compound exhibited a greater binding difference (~6 kcal/mol) between the inactive and active states. Notably, AM6538 and AM841 demonstrated the strongest binding (~30 kcal/mol) to the inactive and active state, respectively. Key residues stabilizing the identified compounds in CB1-inactive state included PHE102, GLY166, PHE170, VAL196, LEU359, SER383, and CIS386. These findings underscore the utility of computational methods in the discovery and development of novel CB1 modulators for potential biomedical applications. © 2024 Elsevier B.V.

publication date

  • March 1, 2025