Distinct Activation Mechanisms Regulate Subtype Selectivity of Cannabinoid Receptors

Abstract

Cannabinoid receptors (CB1 and CB2) are important drug targets for inflammation, obesity, and other central nervous system disorders. However, due to sequence and structural similarities of the ligand binding pockets of these receptors, most of the ligands lack subtype selectivity and cause off-target side effects. CB2 selective agonists can potentially treat pain and inflammation without the psychoactive effects of CB1 agonism. We hypothesize that the subtype selectivity of designed selective ligands can be explained by ligand binding to the conformationally distinct states between CB1 and CB2. To find these conformationally distinct states, we perform 700 μs of unbiased simulations to study the activation mechanism of both the receptors in absence of ligands. The simulation datasets of two receptors were analyzed using Markov state models to identify similarities and distinctions of the major conformational changes associated with activation and allosteric communication between them. Specifically, toggle switch residue movement and its effect on receptor activation differ greatly between CB1 and CB2. Upon further analysis, we discretize the conformational ensembles of both receptors into metastable states using the neural network-based VAMPnets. Structural and dynamic comparisons of these metastable states allow us to decipher a coarse-grained view of protein activation by revealing sequential conversion between these states. Specifically, we observe the difference in the binding pocket volume of different metastable states of CB1, whereas there are minimal changes observed in the CB2. Docking analysis reveals that differential binding pocket volume leads to distinct binding poses and docking affinities of CB2 selective agonists in CB1. Only a few of the intermediate metastable states of CB1 shows high affinity towards CB2 selective agonists. On the other hand, all the CB2 metastable states show a similar affinity for CB2 selective agonists, explaining these ligands overall higher affinity towards CB2. Overall, this computational study mechanistically explains the subtype selectivity of CB2 selective ligands by deciphering the activation mechanism of cannabinoid receptors.

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

“…53 The following steps are taken for the practical implementation of the MSM from the MD data. 4,17,95–97…”

“…The following steps are taken for the practical implementation of the MSM from the MD data. 4,17,[95][96][97] 1. Each frame obtained from the MD simulation was featurized using features important for capturing the conformational ensemble.…”

“…KullbackLeibler divergence (K-L divergence) analysis was performed to show the structural differences in protein conformations in different macrostates 4,111 . In this study, this tech-nique was used in this work to calculate the difference in the pairwise inverse distance distribution in macrostates.…”

“…Quantitative values of the activation metrics for both active structures are compared as scatter points on 1-D line with the CB 1 inactive structure (PDB ID: 5TGZ, 1 color: orange). These quantitative measurements were discussed in Dutta and Shukla 4 .…”

“…Cannabinoid receptor 1 (CB 1 ), which is majorly expressed in the central nervous system (CNS) belongs to the class A G-protein coupled receptor (GPCR) family proteins. [1][2][3][4] GPCRs are expressed in the cellular membrane and help transduce chemical signals from the extracellular to the intracellular direction with the help of the downstream signaling proteins (G-proteins and β-arrestin). [5][6][7] In addition, GPCRs are the largest family of drug targets due to their substantial involvement in human pathophysiology and druggability.…”