Pathway and Mechanism of Drug Binding to G-Protein-Coupled Receptors

Dror, Ron O.; Pan, Albert C.; Arlow, Daniel H.; Borhani, David W.; Maragakis, Paul; Shan, Yibing; Xu, Huafeng; Shaw, David E.

doi:10.1016/j.bpj.2011.11.2241

Cited by 194 publications

(379 citation statements)

References 35 publications

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“…30, p. 6). Although free energy profiles were obtained from the steered MD simulations, the ligand was constrained to predetermined CAVER channels, which may not reflect the real pathways as observed in cMD simulations (28). In comparison, GaMD provides unconstrained enhanced sampling and allows for free ligand diffusion.…”

Section: Discussionmentioning

confidence: 99%

Graded activation and free energy landscapes of a muscarinic G-protein–coupled receptor

Miao

McCammon

2016

Proc. Natl. Acad. Sci. U.S.A.

149

170

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G-protein-coupled receptors (GPCRs) recognize ligands of widely different efficacies, from inverse to partial and full agonists, which transduce cellular signals at differentiated levels. However, the mechanism of such graded activation remains unclear. Using the Gaussian accelerated molecular dynamics (GaMD) method that enables both unconstrained enhanced sampling and free energy calculation, we have performed extensive GaMD simulations (∼19 μs in total) to investigate structural dynamics of the M 2 muscarinic GPCR that is bound by the full agonist iperoxo (IXO), the partial agonist arecoline (ARC), and the inverse agonist 3-quinuclidinyl-benzilate (QNB), in the presence or absence of the G-protein mimetic nanobody. In the receptornanobody complex, IXO binding leads to higher fluctuations in the protein-coupling interface than ARC, especially in the receptor transmembrane helix 5 (TM5), TM6, and TM7 intracellular domains that are essential elements for GPCR activation, but less flexibility in the receptor extracellular region due to stronger binding compared with ARC. Two different binding poses are revealed for ARC in the orthosteric pocket. Removal of the nanobody leads to GPCR deactivation that is characterized by inward movement of the TM6 intracellular end. Distinct low-energy intermediate conformational states are identified for the IXO-and ARC-bound M 2 receptor. Both dissociation and binding of an orthosteric ligand are observed in a single all-atom GPCR simulation in the case of partial agonist ARC binding to the M 2 receptor. This study demonstrates the applicability of GaMD for exploring free energy landscapes of large biomolecules and the simulations provide important insights into the GPCR functional mechanism. cellular signaling | ligand recognition | protein-protein interactions | allostery | drug discovery G -protein-coupled receptors (GPCRs) are primary targets of about one-third of currently marketed drugs. They recognize ligands of widely different efficacies, from inverse to partial and full agonists, which transduce cellular signals at differentiated levels. Increasing experimental and computational evidence suggests that GPCRs exist in an ensemble of different conformations that interconvert dynamically during activation and ligand recognition (1-3). The structure, dynamics, and function of GPCRs result from underlying free energy landscapes (4). However, quantitative characterization of the GPCR activation and ligand-dependent free energy profiles has proved challenging (4-12).The M 2 muscarinic GPCR is widely distributed in mammalian tissues. It plays a key role in regulating the human heart rate and heart contraction forces. The M 2 receptor has been crystallized in both an inactive state bound by the inverse agonist 3-quinuclidinylbenzilate (QNB) (13) and an active state bound by the full agonist iperoxo (IXO) and a G-protein mimetic nanobody (14). The receptor activation is characterized by rearrangements of the transmembrane (TM) helices 5, 6, and 7, particularly closing of the ligan...

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Section: Discussionmentioning

confidence: 99%

Graded activation and free energy landscapes of a muscarinic G-protein–coupled receptor

Miao

McCammon

2016

Proc. Natl. Acad. Sci. U.S.A.

149

170

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“…Although these crystal structures provided enormously important insights into different specific conformational states, as well as atomistic protein-ligand interactions of GPCRs, they nonetheless represent snapshots of the highly dynamic nature of GPCRs (20). To address the above issue, extensive computational simulations have been performed to characterize the structural dynamics of GPCRs (20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30)(31)(32)(33). All-atom molecular dynamics (MD) simulations are capable of exploring large-scale conformational changes during both receptor activation (23) and deactivation (20) by using fast supercomputers.…”

Section: Significancementioning

confidence: 99%

“…All-atom molecular dynamics (MD) simulations are capable of exploring large-scale conformational changes during both receptor activation (23) and deactivation (20) by using fast supercomputers. Moreover, long-timescale MD simulations captured ligand binding to GPCRs (29), in particular for several prototypical negative allosteric modulators (NAMs) of the M 2 mAChR (30). In recent studies, we have also successfully depicted the activation of both the M 2 and M 3 mAChRs in accelerated MD (aMD) simulations (31)(32)(33).…”

Section: Significancementioning

confidence: 99%

Accelerated structure-based design of chemically diverse allosteric modulators of a muscarinic G protein-coupled receptor

Miao

Goldfeld

Moo

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

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Design of ligands that provide receptor selectivity has emerged as a new paradigm for drug discovery of G protein-coupled receptors, and may, for certain families of receptors, only be achieved via identification of chemically diverse allosteric modulators. Here, the extracellular vestibule of the M 2 muscarinic acetylcholine receptor (mAChR) is targeted for structure-based design of allosteric modulators. Accelerated molecular dynamics (aMD) simulations were performed to construct structural ensembles that account for the receptor flexibility. Compounds obtained from the National Cancer Institute (NCI) were docked to the receptor ensembles. Retrospective docking of known ligands showed that combining aMD simulations with Glide induced fit docking (IFD) provided much-improved enrichment factors, compared with the Glide virtual screening workflow. Glide IFD was thus applied in receptor ensemble docking, and 38 top-ranked NCI compounds were selected for experimental testing. In [ 3 H]Nmethylscopolamine radioligand dissociation assays, approximately half of the 38 lead compounds altered the radioligand dissociation rate, a hallmark of allosteric behavior. In further competition binding experiments, we identified 12 compounds with affinity of ≤30 μM. With final functional experiments on six selected compounds, we confirmed four of them as new negative allosteric modulators (NAMs) and one as positive allosteric modulator of agonist-mediated response at the M 2 mAChR. Two of the NAMs showed subtype selectivity without significant effect at the M 1 and M 3 mAChRs. This study demonstrates an unprecedented successful structure-based approach to identify chemically diverse and selective GPCR allosteric modulators with outstanding potential for further structure-activity relationship studies.GPCR | allosteric modulators | ensemble docking | affinity | cooperativity

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“…State-of-the-art examples are studies of membrane binding and the formation of pores by antimicrobial and cell-penetrating peptides (Berglund et al, 2015;Huang and García, 2013;Moiset et al, 2013;Ulmschneider et al, 2012), of the specific binding of lipids to membrane proteins (Aponte-Santamaria et al, 2012;Contreras et al, 2012;Lee and Lyman, 2012;Pöyry et al, 2013), of the cyclodextrin-mediated extraction of cholesterol from membranes (López et al, 2013a), of the dynamic organization of multi-component membranes (Martinez-Seara et al, 2010;Sodt et al, 2014;Wu et al, 2014b), of lipid-peptide interplay in membrane fusion (Blanchard et al, 2014;Larsson and Kasson, 2013) and of the functioning of membrane proteins (Dror et al, 2011;Kopfer et al, 2014;Maffeo et al, 2012;Marinelli et al, 2014;Moradi et al, 2015;Ostmeyer et al, 2013;Romo et al, 2010).…”

Section: Atomic Resolutionmentioning

confidence: 99%

Computational ‘microscopy’ of cellular membranes

Ingólfsson

Arnarez²,

Periole³

et al. 2016

Journal of Cell Science

136

120

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Computational 'microscopy' refers to the use of computational resources to simulate the dynamics of a molecular system. Tuned to cell membranes, this computational 'microscopy' technique is able to capture the interplay between lipids and proteins at a spatiotemporal resolution that is unmatched by other methods. Recent advances allow us to zoom out from individual atoms and molecules to supramolecular complexes and subcellular compartments that contain tens of millions of particles, and to capture the complexity of the crowded environment of real cell membranes. This Commentary gives an overview of the main concepts of computational 'microscopy' and describes the state-of-the-art methods used to model cell membrane processes. We illustrate the power of computational modelling approaches by providing a few in-depth examples of largescale simulations that move up from molecular descriptions into the subcellular arena. We end with an outlook towards modelling a complete cell in silico.

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Pathway and Mechanism of Drug Binding to G-Protein-Coupled Receptors

Cited by 194 publications

References 35 publications

Graded activation and free energy landscapes of a muscarinic G-protein–coupled receptor

Graded activation and free energy landscapes of a muscarinic G-protein–coupled receptor

Accelerated structure-based design of chemically diverse allosteric modulators of a muscarinic G protein-coupled receptor

Computational ‘microscopy’ of cellular membranes

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