State-dependent cannabidiol interactions with fentanyl-bound mouse μ-opioid receptor conformations: a three-state molecular dynamics study

We published recently that one of the main constituents of cannabis products, cannabidiol (CBD), is an efficacious negative allosteric modulator (NAM) of the mu opioid receptor (MOR1) (Bosquez-Berger et al., 2023). Here, we investigated how the presence of cannabidiol (CBD) is associated with fentanyl (FEN) binding across MOR1 conformations. We performed molecular dynamics simulations of systems containing FEN alone or FEN+CBD in three mouse MOR1 conformational backgrounds: active-like 5C1M, inactive-like 4DKL, and a modeled Morph50 intermediate between the 5C1M and 4DKL conformations. Three independently seeded 200 ns trajectories were analyzed per model and condition (18 trajectories total), with the trajectory treated as the independent unit. Across the matched 0-200 ns window, consensus CBD contacts and CBD-associated changes in FEN contacts were strongly state dependent. Corrected intracellular TM3 to TM6 analyses separated the expected active-like, intermediate, and inactive-like backgrounds but did not identify a CBD-associated shift that was consistent across both geometric definitions and all three replicates. Equal-weight replicate-composite density maps preserved both the shared ligand distributions and this between-trajectory variability. These descriptive results support receptor-state-dependent CBD, FEN, MOR1 interactions while emphasizing the limited inferential power of three trajectories per condition.

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Publication Details

Journal
bioRxiv (Cold Spring Harbor Laboratory)
Published
2026-08-27
DOI
https://doi.org/10.64898/2026.08.24.746804
Primary Topic
Cannabis and Cannabinoid Research
Type
preprint
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preprint

State-dependent cannabidiol interactions with fentanyl-bound mouse μ-opioid receptor conformations: a three-state molecular dynamics study

Jim Wager‐Miller, Alex Straiker, Gergő Szanda, Kimberley Bosire et al.
bioRxiv (Cold Spring Harbor Laboratory)
Cannabis and Cannabinoid Research
preprint

State-dependent cannabidiol interactions with fentanyl-bound mouse μ-opioid receptor conformations: a three-state molecular dynamics study

Jim Wager‐Miller, Alex Straiker, Gergő Szanda, Kimberley Bosire, Kenneth Mackie
preprint en

Abstract

We published recently that one of the main constituents of cannabis products, cannabidiol (CBD), is an efficacious negative allosteric modulator (NAM) of the mu opioid receptor (MOR1) (Bosquez-Berger et al., 2023). Here, we investigated how the presence of cannabidiol (CBD) is associated with fentanyl (FEN) binding across MOR1 conformations. We performed molecular dynamics simulations of systems containing FEN alone or FEN+CBD in three mouse MOR1 conformational backgrounds: active-like 5C1M, inactive-like 4DKL, and a modeled Morph50 intermediate between the 5C1M and 4DKL conformations. Three independently seeded 200 ns trajectories were analyzed per model and condition (18 trajectories total), with the trajectory treated as the independent unit. Across the matched 0-200 ns window, consensus CBD contacts and CBD-associated changes in FEN contacts were strongly state dependent. Corrected intracellular TM3 to TM6 analyses separated the expected active-like, intermediate, and inactive-like backgrounds but did not identify a CBD-associated shift that was consistent across both geometric definitions and all three replicates. Equal-weight replicate-composite density maps preserved both the shared ligand distributions and this between-trajectory variability. These descriptive results support receptor-state-dependent CBD, FEN, MOR1 interactions while emphasizing the limited inferential power of three trajectories per condition.

bioRxiv (Cold Spring Harbor Laboratory)
Indiana University Bloomington (US)
Cannabis and Cannabinoid Research
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State-dependent cannabidiol interactions with fentanyl-bound mouse μ-opioid receptor conformations: a three-state molecular dynamics study — Jim Wager‐Miller, Alex Straiker, et al. · bioRxiv (Cold Spring Harbor Laboratory) (2026) | TGRS Research Map | TGRS