Recent progress in the study of G protein-coupled receptors with molecular dynamics computer simulations. Biochim Biophys Acta

Department of Biochemistry and Biophysics, University of Rochester Medical Center, Rochester, NY, USA.
Biochimica et Biophysica Acta (Impact Factor: 4.66). 03/2011; 1808(7):1868-78. DOI: 10.1016/j.bbamem.2011.03.010
Source: PubMed


G protein-coupled receptors (GPCRs) are a large, biomedically important family of proteins, and the recent explosion of new high-resolution structural information about them has provided an enormous opportunity for computational modeling to make major contributions. In particular, molecular dynamics simulations have become a driving factor in many areas of GPCR biophysics, improving our understanding of lipid-protein interaction, activation mechanisms, and internal hydration. Given that computers will continue to get faster and more structures will be solved, the importance of computational methods will only continue to grow, particularly as simulation research is more closely coupled to experiment.

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    • "GPCRs, like other integral membrane proteins, require a lipid membrane environment to remain folded. Thus, it is challenging to find conditions to over express and purify them [5]. The Beta 3-adrenergic receptor (b3-AR) belongs to the beta adrenergic receptor subfamily Class A GPCR. "
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    ABSTRACT: Beta 3-Adrenergic receptors (β3-AR), belonging to the G-protein coupled receptor family, are known to be involved in important physiological functions as intestinal smooth muscle relaxation, glucose homeostasis etc. Detailed insight into the mechanistic mode of β3-AR is not known. Molecular dynamic simulations (100ns) were performed on the 3-D molecular model of β3-AR and complexes of β3-AR with potential agonists embedded in 2-dipalmitoyl-sn-phosphocholine (DPPC) bilayer - water system using OPLS (Optimized Potentials for Liquid Simulations) force field to gain structural insight into β3-AR. The detailed structural analysis of the molecular dynamic trajectories reveal that the helical bundle conformations remain well preserved to maintain a conformation similar to the other X-ray solved G-protein coupled receptors, whereas significant flexibility is observed in intracellular and the extracellular loops region. The formation of extensive intra helical and water mediated H-bonds, and aromatic stacking interactions play a key role in stabilizing the transmembrane helical bundles. These interactions might be specific to the functional motifs such as D(E)RY, CWxP, S(N)LAxAD, SxxxS and NPxxY motifs which provide structural constraints on the β3-AR. The compound 3, 4 and 6 are proposed to act as scaffolds for potential agonists for β3-AR based on stereochemical and energetic considerations. In lieu of the lack of the crystal structure available, the findings of the simulation study provides more comprehensive picture of the functional properties of the β3-AR.
    Biochimie 06/2014; 101(1). DOI:10.1016/j.biochi.2014.01.016 · 2.96 Impact Factor
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    • "This is broken on activation, and there has been some discussion on whether a proton moves from Glu181 in ECL2 to Glu113 3.28 . However, most theoretical studies imply that both glutamates retain the normal deprotonated ionization state during activation (Grossfield, 2011; Mertz et al., 2012). By default, most modeling programs protonate histidine at the delta position rather than the epsilon position, but see Neri et al. (2010) "
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    ABSTRACT: The most significant advance in modeling GPCR active states has been the β(2)-adrenergic receptor-Gs complex as this essentially transforms active-state modeling into homology modeling. Various different molecular dynamics-based approaches for modeling active states are presented, and a number of key applications discussed. These simulations have given insights into the activation pathway, conformational changes, dimerization, hydration, the ionic lock, ligand binding, protonation, and sodium binding. Crystallography and simulations have shown that the presence of agonist alone is unlikely to be sufficient to form the active state and that restraints applied to the G protein-binding region are required. The role of various microswitches in activation is discussed, including the controversial rotamer toggle switch. The importance of explicitly simulating experimental molecular probes to understand activation is highlighted, along with the need to ensure that such molecules are well parameterized. Approaches to loop modeling are discussed. We argue that the role of successful virtual screening against active models should not be overestimated as the main conformational changes on activation occur in the intracellular region.
    Methods in enzymology 02/2013; 522:21-35. DOI:10.1016/B978-0-12-407865-9.00002-9 · 2.09 Impact Factor
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    • "Computer simulations can sometimes overcome these difficulties . They have been shown to provide insight into molecular level details that were otherwise difficult to obtain [19] [20] [21] [22] [23]. Here we use a simple computational model [24] to study membrane incorporation of AQPs in different geometric arrangements. "
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    ABSTRACT: A limited class of aquaporins has been described to form regular arrays and junctions in membranes. The biological significance of these structures, however, remains uncertain. Here we analyze the underlying physical principles with the help of a computational procedure that takes into account protein-protein as well as protein-membrane interactions. Experimentally observed array/junction structures are systematically (dis)assembled and major driving forces identified. Aquaporin 4 was found to be markedly different from the non-junction forming aquaporin 1. The environmental stabilization resulting from embedding into the biomembrane was identified as the main driving force. This highlights the role of protein-membrane interactions in aquaporin 4. Analysis of the type presented here can help to decipher the biological role of membrane arrays and junctions formed by aquaporin.
    Biochimica et Biophysica Acta 04/2012; 1818(9):2234-43. DOI:10.1016/j.bbamem.2012.04.009 · 4.66 Impact Factor
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