Data from: Characterization of binding kinetics and intracellular signaling of new psychoactive substances targeting cannabinoid receptor using transition-based reweighting method

New psychoactive substances (NPS) targeting cannabinoid receptor 1 pose a
significant threat to society as recreational abusive drugs that have
pronounced physiological side effects. These greater adverse effects
compared to classical cannabinoids have been linked to the higher
downstream β-arrestin signaling. Thus, understanding the mechanism of
differential signaling will reveal important structure-activity
relationships essential for identifying and potentially regulating NPS
molecules. In this study, we simulate the slow (un)binding process of NPS
MDMB-Fubinaca and classical cannabinoid HU-210 from CB1 using
multi-ensemble simulation to decipher the effects of ligand binding
dynamics on downstream signaling. The transition-based reweighing method
is used for the estimation of transition rates and underlying
thermodynamics of (un)binding processes of ligands with nanomolar
affinities. Our analyses reveal major interaction differences with
transmembrane TM7 between NPS and classical cannabinoids. A variational
autoencoder-based approach, neural relational inference (NRI), is applied
to assess the allosteric effects on intracellular regions attributable to
variations in binding pocket interactions. NRI analysis indicates a
heightened level of allosteric control of NPxxY motif for NPS-bound
receptors, which contributes to the higher probability of formation of a
crucial triad interaction (Y7.53-Y5.58-T3.46) necessary for stronger
β-arrestin signaling. Hence, in this work, MD simulation, data-driven
statistical methods, and deep learning point out the structural basis for
the heightened physiological side effects associated with NPS,
contributing to efforts aimed at mitigating their public health impact.