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      Characterizing Interhelical Interactions of G-Protein Coupled Receptors with the Fragment Molecular Orbital Method

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          Abstract

          G-protein coupled receptors (GPCRs) are the largest superfamily of membrane proteins, regulating almost every aspect of cellular activity and serving as key targets for drug discovery. We have identified an accurate and reliable computational method to characterize the strength and chemical nature of the interhelical interactions between the residues of transmembrane (TM) domains during different receptor activation states, something that cannot be characterized solely by visual inspection of structural information. Using the fragment molecular orbital (FMO) quantum mechanics method to analyze 35 crystal structures representing different branches of the class A GPCR family, we have identified 69 topologically equivalent TM residues that form a consensus network of 51 inter-TM interactions, providing novel results that are consistent with and help to rationalize experimental data. This discovery establishes a comprehensive picture of how defined molecular forces govern specific interhelical interactions which, in turn, support the structural stability, ligand binding, and activation of GPCRs.

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          Most cited references51

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          Cation-pi interactions in structural biology.

          Cation-pi interactions in protein structures are identified and evaluated by using an energy-based criterion for selecting significant sidechain pairs. Cation-pi interactions are found to be common among structures in the Protein Data Bank, and it is clearly demonstrated that, when a cationic sidechain (Lys or Arg) is near an aromatic sidechain (Phe, Tyr, or Trp), the geometry is biased toward one that would experience a favorable cation-pi interaction. The sidechain of Arg is more likely than that of Lys to be in a cation-pi interaction. Among the aromatics, a strong bias toward Trp is clear, such that over one-fourth of all tryptophans in the data bank experience an energetically significant cation-pi interaction.
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            Allosteric sodium in class A GPCR signaling.

            Despite their functional and structural diversity, G-protein-coupled receptors (GPCRs) share a common mechanism of signal transduction via conformational changes in the seven-transmembrane (7TM) helical domain. New major insights into this mechanism come from the recent crystallographic discoveries of a partially hydrated sodium ion that is specifically bound in the middle of the 7TM bundle of multiple class A GPCRs. This review discusses the remarkable structural conservation and distinct features of the Na(+) pocket in this most populous GPCR class, as well as the conformational collapse of the pocket upon receptor activation. New insights help to explain allosteric effects of sodium on GPCR agonist binding and activation, and sodium's role as a potential co-factor in class A GPCR function. Copyright © 2014 Elsevier Ltd. All rights reserved.
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              G protein coupled receptor structure and activation.

              G protein coupled receptors (GPCRs) are remarkably versatile signaling molecules. The members of this large family of membrane proteins are activated by a spectrum of structurally diverse ligands, and have been shown to modulate the activity of different signaling pathways in a ligand specific manner. In this manuscript I will review what is known about the structure and mechanism of activation of GPCRs focusing primarily on two model systems, rhodopsin and the beta(2) adrenoceptor.
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                Author and article information

                Journal
                J Chem Theory Comput
                J Chem Theory Comput
                ct
                jctcce
                Journal of Chemical Theory and Computation
                American Chemical Society
                1549-9618
                1549-9626
                25 February 2020
                14 April 2020
                : 16
                : 4
                : 2814-2824
                Affiliations
                []Evotec (U.K.) Ltd. , 114 Milton Park, Abingdon, Oxfordshire OX14 4SA, United Kingdom
                []Institute of Structural & Molecular Biology, Research Department of Structural & Molecular Biology, Division of Biosciences, University College London , London, WC1E 6BT, United Kingdom
                [§ ]MRC Laboratory of Molecular Biology , Francis Crick Avenue, Cambridge CB2 0QH, United Kingdom
                []CD-FMat, National Institute of Advanced Industrial Science and Technology (AIST) , 1-1-1 Umezono, Tsukuba, Ibaraki 305-8568, Japan
                []Department of Theoretical and Computational Biophysics, Max Planck Institute for Biophysical Chemistry , 37077 Göttingen, Germany
                Author notes
                Article
                10.1021/acs.jctc.9b01136
                7161079
                32096994
                64876c11-7d96-4ed2-85cf-f06ada20e66d
                Copyright © 2020 American Chemical Society

                This is an open access article published under a Creative Commons Attribution (CC-BY) License, which permits unrestricted use, distribution and reproduction in any medium, provided the author and source are cited.

                History
                : 14 November 2019
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                ct9b01136
                ct9b01136

                Computational chemistry & Modeling
                Computational chemistry & Modeling

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