TY - JOUR
T1 - Prediction of the Binding Affinities and Selectivity for CB1 and CB2 Ligands Using Homology Modeling, Molecular Docking, Molecular Dynamics Simulations, and MM-PBSA Binding Free Energy Calculations
AU - Ji, Beihong
AU - Liu, Shuhan
AU - He, Xibing
AU - Man, Viet Hoang
AU - Xie, Xiang Qun
AU - Wang, Junmei
N1 - Funding Information:
This work was supported by Grants R01-GM079383, R21-GM097617, and P30-DA035778 from the National Institutes of Health. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health or other funding organizations. Computational support from the Center for Research Computing of University of Pittsburgh and Pittsburgh Supercomputing Center (CHE180028P) is acknowledged.
Publisher Copyright:
© 2020 American Chemical Society.
PY - 2020/4/15
Y1 - 2020/4/15
N2 - Cannabinoids are a group of chemical compounds that have been used for thousands of years due to their psychoactive function and systemic physiological effects. There are at least two types of cannabinoid receptors, CB1 and CB2, which belong to the G protein-coupled receptor superfamily and can trigger different signaling pathways to exert their physiological functions. In this study, several representative agonists and antagonists of both CB1 and CB2 were systematically studied to predict their binding affinities and selectivity against both cannabinoid receptors using a set of hierarchical molecular modeling and simulation techniques, including homology modeling, molecular docking, molecular dynamics (MD) simulations and end point binding free energy calculations using the molecular mechanics/Poisson-Boltzmann surface area-WSAS (MM-PBSA-WSAS) method, and molecular mechanics/generalized Born surface area (MM-GBSA) free energy decomposition. Encouragingly, the calculated binding free energies correlated very well with the experimental values and the correlation coefficient square (R2), 0.60, was much higher than that of an efficient but less accurate docking scoring function (R2 = 0.37). The hotspot residues for CB1 and CB2 in both active and inactive conformations were identified via MM-GBSA free energy decomposition analysis. The comparisons of binding free energies, ligand-receptor interaction patterns, and hotspot residues among the four systems, namely, agonist-bound CB1, agonist-bound CB2, antagonist-bound CB1, and antagonist-bound CB2, enabled us to investigate and identify distinct binding features of these four systems, with which one can rationally design potent, selective, and function-specific modulators for the cannabinoid receptors.
AB - Cannabinoids are a group of chemical compounds that have been used for thousands of years due to their psychoactive function and systemic physiological effects. There are at least two types of cannabinoid receptors, CB1 and CB2, which belong to the G protein-coupled receptor superfamily and can trigger different signaling pathways to exert their physiological functions. In this study, several representative agonists and antagonists of both CB1 and CB2 were systematically studied to predict their binding affinities and selectivity against both cannabinoid receptors using a set of hierarchical molecular modeling and simulation techniques, including homology modeling, molecular docking, molecular dynamics (MD) simulations and end point binding free energy calculations using the molecular mechanics/Poisson-Boltzmann surface area-WSAS (MM-PBSA-WSAS) method, and molecular mechanics/generalized Born surface area (MM-GBSA) free energy decomposition. Encouragingly, the calculated binding free energies correlated very well with the experimental values and the correlation coefficient square (R2), 0.60, was much higher than that of an efficient but less accurate docking scoring function (R2 = 0.37). The hotspot residues for CB1 and CB2 in both active and inactive conformations were identified via MM-GBSA free energy decomposition analysis. The comparisons of binding free energies, ligand-receptor interaction patterns, and hotspot residues among the four systems, namely, agonist-bound CB1, agonist-bound CB2, antagonist-bound CB1, and antagonist-bound CB2, enabled us to investigate and identify distinct binding features of these four systems, with which one can rationally design potent, selective, and function-specific modulators for the cannabinoid receptors.
KW - Cannabinoid receptors
KW - binding free energy
KW - free energy decomposition
KW - molecular dynamics simulations
KW - molecular mechanisms
KW - multiscale molecular modeling
KW - rational drug design
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U2 - 10.1021/acschemneuro.9b00696
DO - 10.1021/acschemneuro.9b00696
M3 - Article
C2 - 32196303
AN - SCOPUS:85083545722
SN - 1948-7193
VL - 11
SP - 1139
EP - 1158
JO - ACS Chemical Neuroscience
JF - ACS Chemical Neuroscience
IS - 8
ER -