GPCR Engineering Yields High-Resolution Structural Insights into β
            <sub>2</sub>
            -Adrenergic Receptor Function

Rosenbaum, Daniel M.; Cherezov, Vadim; Hanson, Michael A.; Rasmussen, Søren G. F.; Thian, Foon Sun; Kobilka, Tong Sun; Choi, Hee Jung; Yao, Xiao-Jie; Weis, William I.; Stevens, Raymond C.; Kobilka, Brian K.

doi:10.1126/science.1150609

Cited by 1,289 publications

(1,338 citation statements)

References 46 publications

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“…Although high-throughput robotics now makes it possible to screen vast numbers of crystallization conditions, some proteins remain recalcitrant to crystallization. Many approaches have been developed to improve the success rate for crystallization, for example, systematically truncating the target protein, 1,2 methylating the lysine residues, 3,4 removing post-translational modifications, [5][6][7] screening homologues of the target protein for crystallization, 8,9 fusing the target protein to a carrier protein, [10][11][12][13] crystallizing racemic mixtures of the target protein, [14][15][16][17][18][19][20] and cocrystallizing the target protein with antibodies or other binding proteins. [21][22][23] A number of those methods have been reviewed.…”

Section: Introductionmentioning

confidence: 99%

An approach to crystallizing proteins by metal‐mediated synthetic symmetrization

Laganowsky

Zhao²,

Soriaga

et al. 2011

Protein Science

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Combining the concepts of synthetic symmetrization with the approach of engineering metal-binding sites, we have developed a new crystallization methodology termed metal-mediated synthetic symmetrization. In this method, pairs of histidine or cysteine mutations are introduced on the surface of target proteins, generating crystal lattice contacts or oligomeric assemblies upon coordination with metal. Metal-mediated synthetic symmetrization greatly expands the packing and oligomeric assembly possibilities of target proteins, thereby increasing the chances of growing diffraction-quality crystals. To demonstrate this method, we designed various T4 lysozyme (T4L) and maltose-binding protein (MBP) mutants and cocrystallized them with one of three metal ions: copper (Cu 21 ), nickel (Ni 21 ), or zinc (Zn 21 ). The approach resulted in 16 new crystal structures-eight for T4L and eight for MBP-displaying a variety of oligomeric assemblies and packing modes, representing in total 13 new and distinct crystal forms for these proteins. We discuss the potential utility of the method for crystallizing target proteins of unknown structure by engineering in pairs of histidine or cysteine residues. As an alternate strategy, we propose that the varied crystallization-prone forms of T4L or MBP engineered in this work could be used as crystallization chaperones, by fusing them genetically to target proteins of interest.

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Section: Introductionmentioning

confidence: 99%

An approach to crystallizing proteins by metal‐mediated synthetic symmetrization

Laganowsky

Zhao²,

Soriaga

et al. 2011

Protein Science

View full text Add to dashboard Cite

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“…In this context, experimentally validated GPCR homology models have proven to be valuable tools for lead identification, and the scientific literature flourished with successful rational drug design and virtual screening examples [7][8][9][10][11]. In 2007 Kobilka and coworkers unveiled the 3D crystal structure of the human β 2 -adrenergic receptor (β 2 -AR), finally providing the long awaited proof that the structure of GPCRs generally resembles that of rhodopsin [12][13][14][15]. Comparison between rhodopsin-based models of the β 2 -AR in complex with the inverse agonist carazolol and the corresponding crystal structure supports and encourages the applicability of GPCR homology modeling and molecular docking to computer-aided drug discovery, at least for qualitative purposes [16].…”

Section: Introductionmentioning

confidence: 99%

Ligand and structure-based methodologies for the prediction of the activity of G protein-coupled receptor ligands

Costanzi

Tikhonova

Harden

2008

J Comput Aided Mol Des

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SummaryAccurate in silico models for the quantitative prediction of the activity of G protein-coupled receptor (GPCR) ligands would greatly facilitate the process of drug discovery and development. Several methodologies have been developed based on the properties of the ligands, the direct study of the receptor-ligand interactions, or a combination of both approaches. Ligand-based three-dimensional quantitative structure-activity relationships (3D-QSAR) techniques, not requiring knowledge of the receptor structure, have been historically the first to be applied to the prediction of the activity of GPCR ligands. They are generally endowed with robustness and good ranking ability; however they are highly dependent on training sets. Structure-based techniques generally do not provide the level of accuracy necessary to yield meaningful rankings when applied to GPCR homology models. However, they are essentially independent from training sets and have a sufficient level of accuracy to allow an effective discrimination between binders and nonbinders, thus qualifying as viable lead discovery tools. The combination of ligand and structure-based methodologies in the form of receptor-based 3D-QSAR and ligand and structure-based consensus models results in robust and accurate quantitative predictions. The contribution of the structure-based component to these combined approaches is expected to become more substantial and effective in the future, as more sophisticated scoring functions are developed and more detailed structural information on GPCRs is gathered.

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“…1 In membrane proteins, the presence of slow motion has been a hurdle for X-ray crystallography, as in the case of the 2 -adrenergic G-protein coupled receptor (GPCR). 2 Also for NMR spectroscopy, intermediate (ns-µs) motion tends to be an obstacle. In many amyloidogenic peptides and proteins, large parts of the primary sequence are often obscured and do not yield detectable resonances in solid-state NMR spectra, presumably due to dynamics.…”

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confidence: 99%

Assignment of Dynamic Regions in Biological Solids Enabled by Spin-State Selective NMR Experiments

2010

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Biological function largely depends on protein dynamics. Protein-protein interactions and ligand recognition have been shown to occur on a µs time scale. 1 In membrane proteins, the presence of slow motion has been a hurdle for X-ray crystallography, as in the case of the 2 -adrenergic G-protein coupled receptor (GPCR). 2 Also for NMR spectroscopy, intermediate (ns-µs) motion tends to be an obstacle. In many amyloidogenic peptides and proteins, large parts of the primary sequence are often obscured and do not yield detectable resonances in solid-state NMR spectra, presumably due to dynamics. 3 In the voltage gated membrane protein VDAC, 4,5 large segments of the constricting N-terminal R-helix, which seems important for the gating process, could not be assigned due to dynamics. 5 Ironically, those parts of a protein undergoing slow motion are particularly interesting for the understanding of its biology. We and others have demonstrated that sparsely protonated proteins can be successfully employed in Magic Angle Spinning (MAS) solid-state NMR for proton detection, 6 INEPT based resonance assignment strategies, 7 and mapping of solvent accessibility. 8 This approach allowed us to show for the first time that mutual cancellation of dipole-dipole and chemical shift anisotropy (CSA) relaxation pathways 9,10 can give rise to differential transverse relaxation times T 2 also in the solid state. While in the solution state, the effect is due to isotropic tumbling of the molecule, differential relaxation in the solid-state was shown to be due to internal mobility. 11,12 We show here that TROSY 10 type scalar coupling based triple resonance experiments in combination with perdeuteration are beneficial for the detection and assignment of those residues in the protein which undergo intermediate (ns-µs) dynamics. Standard (non-spin-state selective) triple resonance experiments, in contrast, perform extremely poorly in these cases. 7 Conventional MAS solidstate NMR experiments that are based on dipolar transfers are shown not to detect these flexible residues at all. Figures 1A and B depict the first 1 H/ 15 N planes of tripleresonance out and back HNCO experiments, in which 1 H magnetization is transferred to C′ and back. For these experiments, a sample of the chicken R-spectrin SH3 is employed which is 100% perdeuterated at nonexchangeable sites and partially back-exchanged with protons at labile sites. 7 Paramagnetic Relaxation Enhancement (PRE) using Cu-edta was employed for accelerated data acquisition. 13 While the spectrum in Figure 1A was recorded using a standard HNCO pulse scheme, 14 the spectrum in Figure 1B was recorded with spin-state selection, 15 using the pulse schemes shown in Supplementary Figure 1E and F, respectively. Even for the temperature which yields the best signal-to-noise ratio, residues located in mobile parts of the protein (labeled in black) have severely reduced intensities in comparison to residues that are situated in immobile -sheet regions (labeled in gray). For those dynamic residues, sel...

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GPCR Engineering Yields High-Resolution Structural Insights into β ₂ -Adrenergic Receptor Function

Cited by 1,289 publications

References 46 publications

An approach to crystallizing proteins by metal‐mediated synthetic symmetrization

An approach to crystallizing proteins by metal‐mediated synthetic symmetrization

Ligand and structure-based methodologies for the prediction of the activity of G protein-coupled receptor ligands

Assignment of Dynamic Regions in Biological Solids Enabled by Spin-State Selective NMR Experiments

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GPCR Engineering Yields High-Resolution Structural Insights into β 2 -Adrenergic Receptor Function

Cited by 1,289 publications

References 46 publications

An approach to crystallizing proteins by metal‐mediated synthetic symmetrization

An approach to crystallizing proteins by metal‐mediated synthetic symmetrization

Ligand and structure-based methodologies for the prediction of the activity of G protein-coupled receptor ligands

Assignment of Dynamic Regions in Biological Solids Enabled by Spin-State Selective NMR Experiments

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Product

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GPCR Engineering Yields High-Resolution Structural Insights into β ₂ -Adrenergic Receptor Function