Abstract
Understanding how ligands bind to G-protein coupled receptors (GPCRs) provides insights into a myriad of cell processes and is crucial for drug development. Here we extend a hybrid molecular mechanics/coarse-grained (MM/CG) approach applied previously to enzymes to GPCR/ligand complexes. The accuracy of this method for structural predictions is established by comparison with recent atomistic molecular dynamics simulations on the human β2 adrenergic receptor, a member of the GPCRs superfamily. The results obtained with the MM/CG methodology show a good agreement with previous all-atom classical dynamics simulations, in particular in the structural description of the ligand binding site. This approach could be used for high-throughput predictions of ligand poses in a variety of GPCRs.
Highlights
G-protein coupled receptors (GPCRs) are involved in an enormous number of biochemical processes at the cell membrane
Molecular dynamics (MD) simulations, based on structures predicted by bioinformatics methods, are often used to identify ligand poses on GPCRs for which experimental structural information is not available [3]
The accuracy of this method was established by performing MM/CG simulations of the human GPCR b2 adrenergic receptor in complex with its inverse agonist S-Carazolol (S-Car) and its agonist R-Isoprenaline (R-ISO), and by comparing these with a 800 ns all atom simulation of this system embedded in a lipid bilayer [19]
Summary
G-protein coupled receptors (GPCRs) are involved in an enormous number of biochemical processes at the cell membrane. Molecular dynamics (MD) simulations, based on structures predicted by bioinformatics methods, are often used to identify ligand poses on GPCRs for which experimental structural information is not available [3]. This approach can be very CPU intensive [4], especially to characterize large numbers of ligand/receptor complexes. The reduction of the number of degrees of freedom allows a reduction of the simulation time by ,2 to ,3 orders of magnitude compared to full atom force fields [7] These approaches cannot describe the intermolecular ligand/protein interactions at atomic detail as required in ligand pose predictions
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