Multiscale Molecular Modeling in G Protein-Coupled Receptor (GPCR)-Ligand Studies

Abstract

G protein-coupled receptors (GPCRs) are major drug targets due to their ability to facilitate signal transduction across cell membranes, a process that is vital for many physiological functions to occur. The development of computational technology provides modern tools that permit accurate studies of the structures and properties of large chemical systems, such as enzymes and GPCRs, at the molecular level. The advent of multiscale molecular modeling permits the implementation of multiple levels of theories on a system of interest, for instance, assigning chemically relevant regions to high quantum mechanics (QM) level of theory while treating the rest of the system using classical force field (molecular mechanics (MM) potential). Multiscale QM/MM molecular modeling have far-reaching applications in the rational design of GPCR drugs/ligands by affording precise ligand binding configurations through the consideration of conformational plasticity. This enables the identification of key binding site residues that could be targeted to manipulate GPCR function. This review will focus on recent applications of multiscale QM/MM molecular simulations in GPCR studies that could boost the efficiency of future structure-based drug design (SBDD) strategies.

G-Protein coupled receptors: structure and function in drug discovery

“…84,85 The milestones achieved in GPCR structural studies have provided insights on the arrangements of the transmembrane domains, [1][2][3][4][5]11,12 the location of the orthosteric, 12,31,41 allosteric, 12,31,41 bitopic, 12 as well as biased ligand binding sites, 12 the homo-or hetero-oligomerization of receptors 12 and the structural rearrangements associated with conformational changes upon GPCR activation and inactivation. 12 This base of structural information on GPCRs is vital for SBDD, 12,86 ligandbased drug design (LBDD), 12 and integrated models which complement drug discovery efforts. 12 In 2012, Sosei Heptares published a detailed account on the use of A 2A R structure in identifying series of agents as potential antagonists, this became the rst published GPCR SBDD discovery.…”

Application of Computational Biology and Artificial Intelligence in Drug Design

“…QM is considered the potential solution for the aforementioned concerns, which can explore drug target details at the electronic level [ 52 , 123 , 128 ]. At present, QM is increasingly applied to enzymes or metal-containing proteins that are considered drug targets, such as HIV-1 protease [ 129 ], human DHFR [ 130 ], and GPCR [ 131 ], and clarify the molecular mechanism for drug design [ 132 , 133 , 134 , 135 ]. QM is also used for designing novel drugs, including the high-affinity ligands of FKBP12 [ 136 ] and novel inhibitors of human DHFR [ 137 ].…”

L-DOPA and Droxidopa: From Force Field Development to Molecular Docking into Human β2-Adrenergic Receptor

“…At the same time, homology models of GPCRs have provided a molecular representation of more than 10% of the GPCR superfamily. Structure-based drug discovery (SBDD) relies on understanding receptor-drug interactions at the atomic level, so molecular docking and molecular dynamics simulations have become widespread tools for drug design, measuring binding affinity, revealing reaction mechanisms and protein-ligand interactions, in addition to understand the GPCR structure and dynamics [17][18][19][20][21][22].…”