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      Structure and Dynamics of the M 3 Muscarinic Acetylcholine Receptor

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          Abstract

          Acetylcholine (ACh), the first neurotransmitter to be identified 1 , exerts many of its physiological actions via activation of a family of G protein-coupled receptors (GPCRs) known as muscarinic ACh receptors (mAChRs). Although the five mAChR subtypes (M 1-M 5) share a high degree of sequence homology, they show pronounced differences in G protein coupling preference and the physiological responses they mediate. 24 Unfortunately, despite decades of effort, no therapeutic agents endowed with clear mAChR subtype selectivity have been developed to exploit these differences. 56 We describe here the structure of the G q/11-coupled M 3 mAChR bound to the bronchodilator drug tiotropium and identify the binding mode for this clinically important drug. This structure, together with that of the G i/o-coupled M 2 receptor, offers new possibilities for the design of mAChR subtype-selective ligands. Importantly, the M 3 receptor structure allows the first structural comparison between two members of a mammalian GPCR subfamily displaying different G-protein coupling selectivities. Furthermore, molecular dynamics simulations suggest that tiotropium binds transiently to an allosteric site en route to the binding pocket of both receptors. These simulations offer a structural view of an allosteric binding mode for an orthosteric GPCR ligand and raise additional opportunities for the design of ligands with different affinities or binding kinetics for different mAChR subtypes. Our findings not only offer new insights into the structure and function of one of the most important GPCR families, but may also facilitate the design of improved therapeutics targeting these critical receptors.

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          Most cited references49

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          GPCR engineering yields high-resolution structural insights into beta2-adrenergic receptor function.

          The beta2-adrenergic receptor (beta2AR) is a well-studied prototype for heterotrimeric guanine nucleotide-binding protein (G protein)-coupled receptors (GPCRs) that respond to diffusible hormones and neurotransmitters. To overcome the structural flexibility of the beta2AR and to facilitate its crystallization, we engineered a beta2AR fusion protein in which T4 lysozyme (T4L) replaces most of the third intracellular loop of the GPCR ("beta2AR-T4L") and showed that this protein retains near-native pharmacologic properties. Analysis of adrenergic receptor ligand-binding mutants within the context of the reported high-resolution structure of beta2AR-T4L provides insights into inverse-agonist binding and the structural changes required to accommodate catecholamine agonists. Amino acids known to regulate receptor function are linked through packing interactions and a network of hydrogen bonds, suggesting a conformational pathway from the ligand-binding pocket to regions that interact with G proteins.
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            Crystallizing membrane proteins using lipidic mesophases.

            A detailed protocol for crystallizing membrane proteins that makes use of lipidic mesophases is described. This has variously been referred to as the lipid cubic phase or in meso method. The method has been shown to be quite general in that it has been used to solve X-ray crystallographic structures of prokaryotic and eukaryotic proteins, proteins that are monomeric, homo- and hetero-multimeric, chromophore-containing and chromophore-free, and alpha-helical and beta-barrel proteins. Its most recent successes are the human-engineered beta(2)-adrenergic and adenosine A(2A) G protein-coupled receptors. Protocols are provided for preparing and characterizing the lipidic mesophase, for reconstituting the protein into the monoolein-based mesophase, for functional assay of the protein in the mesophase and for setting up crystallizations in manual mode. Methods for harvesting microcrystals are also described. The time required to prepare the protein-loaded mesophase and to set up a crystallization plate manually is about 1 h.
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              How robust are protein folding simulations with respect to force field parameterization?

              Molecular dynamics simulations hold the promise of providing an atomic-level description of protein folding that cannot easily be obtained from experiments. Here, we examine the extent to which the molecular mechanics force field used in such simulations might influence the observed folding pathways. To that end, we performed equilibrium simulations of a fast-folding variant of the villin headpiece using four different force fields. In each simulation, we observed a large number of transitions between the unfolded and folded states, and in all four cases, both the rate of folding and the structure of the native state were in good agreement with experiments. We found, however, that the folding mechanism and the properties of the unfolded state depend substantially on the choice of force field. We thus conclude that although it is important to match a single, experimentally determined structure and folding rate, this does not ensure that a given simulation will provide a unique and correct description of the full free-energy surface and the mechanism of folding. Copyright © 2011 Biophysical Society. Published by Elsevier Inc. All rights reserved.
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                Author and article information

                Journal
                0410462
                6011
                Nature
                Nature
                Nature
                0028-0836
                1476-4687
                8 May 2012
                22 February 2012
                25 December 2012
                : 482
                : 7386
                : 552-556
                Affiliations
                [1 ]Department of Molecular and Cellular Physiology, Stanford University School of Medicine, Stanford, California 94305, USA
                [2 ]Molecular Signaling Section, Laboratory of Bioorganic Chemistry, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, Maryland 20892, USA
                [3 ]D. E. Shaw Research, New York, New York 10036, USA
                [4 ]Department of Biochemistry, University of Texas Southwestern Medical Center, Dallas, Texas 75390, USA
                [5 ]Department of Bionano Engineering, Hanyang University, Ansan 426-791, Korea
                [6 ]Department of Structural Biology, Stanford University School of Medicine, 299 Campus Drive, Stanford, California 94305, USA
                Author notes
                [* ]Correspondence and requests for materials should be addressed to B.K.K. ( kobilka@ 123456stanford.edu ) or J.W. ( jwess@ 123456helix.nih.gov )
                Article
                NIHMS351110
                10.1038/nature10867
                3529910
                22358844
                7e9c6e19-509f-4a70-b19e-8c36c74cf9eb

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                History
                Funding
                Funded by: National Institute of Neurological Disorders and Stroke : NINDS
                Award ID: R01 NS028471 || NS
                Funded by: National Institute of General Medical Sciences : NIGMS
                Award ID: R01 GM083118 || GM
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