Status of GPCR Modeling and Docking as Reflected by Community-wide GPCR Dock 2010 Assessment

Kufareva, Irina; Rueda, Manuel; Katritch, Vsevolod; Stevens, Raymond C.; Abagyan, Ruben

doi:10.1016/j.str.2011.05.012

Cited by 278 publications

(354 citation statements)

References 57 publications

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“…2015). This conclusion fits to the results of community-wide GPCR homology modelling assessments conducted by the Abagyan and Stevens labs (Michino et al 2009;Kufareva et al 2011;Kufareva et al 2014). According to GPCR homology modeling assessments, templates with a sequence identity of at least 30-35 % allow building accurate homology models (Michino et al 2009;Kufareva et al 2011;Kufareva et al 2014).…”

Section: Molecular Modelling Of Ffa1supporting

confidence: 87%

Application of GPCR Structures for Modelling of Free Fatty Acid Receptors

Tikhonova

2016

Free Fatty Acid Receptors

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Five G protein-coupled receptors (GPCRs) have been identified to be activated by free fatty acids (FFA). Among them, FFA1 (GPR40) and FFA4 (GPR120) bind long-chain fatty acids, FFA2 (GPR43) and FFA3 (GPR41) bind short-chain fatty acids and GPR84 binds medium-chain fatty acids. Free fatty acid receptors have now emerged as potential targets for the treatment of diabetes, obesity and immune diseases. The recent progress in crystallography of GPCRs has now enabled the elucidation of the structure of FFA1 and provided reliable templates for homology modelling of other FFA receptors. Analysis of the crystal structure and improved homology models, along with mutagenesis data and structure activity, highlighted an unusual arginine charge pairing interaction in FFA1-3 for receptor modulation, distinct structural features for ligand binding to FFA1 and FFA4 and an arginine of the second extracellular loop as a possible anchoring point for FFA at GPR84. Structural data will be helpful for searching novel small molecule modulators at the FFA receptors.

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Section: Molecular Modelling Of Ffa1supporting

confidence: 87%

Application of GPCR Structures for Modelling of Free Fatty Acid Receptors

Tikhonova

2016

Free Fatty Acid Receptors

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“…Similarly, A 2A adenosine crystal helices in the β 2 -adrenergic template have a 2.1-Å homology model rmsd, which SuperBiHelix improves to 1.4 Å. In community-wide assessments of structure prediction methods (31,32) aimed at GPCRs, the SuperBiHelix method has performed well at predicting the receptor structures. Prediction of ligand binding sites (without using prior mutagenesis data on the ligand or similar ligands) has not performed as well because docking of ligands to predicted protein structures depends highly on the accuracy of the protein structure.…”

Section: Discussionmentioning

confidence: 99%

“…Homology-based methods have not led to the prediction of multiple receptor conformations like that possible with the SuperBiHelix method. Only a handful of methods (18,32) have been able to predict multiple conformations based on some level of rigorous conformational sampling.…”

Section: Discussionmentioning

confidence: 99%

SuperBiHelix method for predicting the pleiotropic ensemble of G-protein–coupled receptor conformations

Bray

Abrol

Goddard

et al. 2013

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

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There is overwhelming evidence that G-protein-coupled receptors (GPCRs) exhibit several distinct low-energy conformations, each of which might favor binding to different ligands and/or lead to different downstream functions. Understanding the function of such proteins requires knowledge of the ensemble of low-energy configurations that might play a role in this pleiotropic functionality. We earlier reported the BiHelix method for efficiently sampling the (12) 7 = 35 million conformations resulting from 30°rotations about the axis (η) of all seven transmembrane helices (TMHs), showing that the experimental structure is reliably selected as the best conformation from this ensemble. However, various GPCRs differ sufficiently in the tilts of the TMHs that this method need not predict the optimum conformation starting from any other template. In this paper, we introduce the SuperBiHelix method in which the tilt angles (θ, φ) are optimized simultaneously with rotations (η) efficiently enough that it is practical and sufficient to sample (5 × 3 × 5) 7 = 13 trillion configurations. This method can correctly identify the optimum structure of a GPCR starting with the template from a different GPCR. We have validated this method by predicting known crystal structure conformations starting from the template of a different protein structure. We find that the SuperBiHelix conformational ensemble includes the higher energy conformations associated with the active protein in addition to those associated with the more stable inactive protein. This methodology was then applied to design and experimentally confirm structures of three mutants of the CB1 cannabinoid receptor associated with different functions.protein structure prediction | A 2A adenosine receptor | β 2 -adrenergic receptor | constitutive activity | functional selectivity

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“…Many applications such as the design of receptors with reprogrammed signaling properties, the thermostabilization of membrane-embedded scaffolds or molecular sensors will benefit from our rational design technique. As the success of structure-based design approaches partly relies on the accuracy of starting structural models, combining novel improved homology modeling techniques of membrane protein structures (51,52) and design techniques may allow for rationally engineering stabilized variants of many uncharacterized receptors.…”

Section: Discussionmentioning

confidence: 99%

Naturally evolved G protein-coupled receptors adopt metastable conformations

Chen

Zhou

Fryszczyn

et al. 2012

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

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A wide range of membrane receptors signal through conformational changes, and the resulting protein conformational flexibility often hinders their structural studies. Because the determinants of membrane receptor conformational stability are still poorly understood, identifying a minimal set of perturbations stabilizing a membrane protein in a given conformation remains a major challenge in membrane protein structure determination. We present a novel approach integrating bioinformatics, computational design and experimental techniques that identifies and stabilizes metastable receptor regions. When applied to the beta1-adrenergic receptor, the method generated 13 novel receptor variants stabilized in the intended inactive state among which two exhibit an apparent thermostability higher than WT and M23 (a receptor variant previously stabilized by extensive scanning mutagenesis) by more than 30°C and 11°C, respectively. Targeted regions involve nonconserved unsatisfied polar residues or exhibit significant packing defects, features found in all class A G protein-coupled receptor structures. These findings suggest that natural G protein-coupled receptor sequences have evolved to be conformationally metastable through the design of suboptimal polar and van der Waals tertiary interactions. Given sufficiently accurate structural models, our approach should prove useful for designing stabilized variants of many uncharacterized membrane receptors.computational protein design | protein conformational stability | membrane protein modeling | signal transduction | synthetic biology M embrane proteins represent around 30% of currently sequenced genomes and are critical in the regulation of cell signaling and cell-cell communication (1, 2). When dysfunctional, however, these proteins can be responsible for serious diseases and constitute more than 60% of current drug targets. Despite their abundance and functional importance, membrane proteins are largely underrepresented in the Protein Data Bank, mainly due to technical difficulties in studying these proteins. A large fraction of these proteins such as G protein-coupled receptors (GPCRs) transduces signals across membranes through conformational changes (3-6). The resulting protein conformational heterogeneity and flexibility is a major factor hindering crystallization. An additional obstacle to structural determination is the poor stability of membrane proteins in detergent solution required by traditional crystallization approaches (7,8).In recent years, several approaches to stabilize membrane proteins have been explored (9). These methods include development and optimization of solubilizing detergents (10), reconstitution of proteins into lipidic bicelles (11, 12), cleavage of flexible protein regions (13-18), co-crystallization with stabilizing ligands, antibodies, and fusion with soluble proteins (e.g., T4 lysozyme) (13-15, 17, 19-23). Several of these modifications, however, disrupt important functional regions and interactions with either natural ligands or downstre...

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Status of GPCR Modeling and Docking as Reflected by Community-wide GPCR Dock 2010 Assessment

Cited by 278 publications

References 57 publications

Application of GPCR Structures for Modelling of Free Fatty Acid Receptors

Application of GPCR Structures for Modelling of Free Fatty Acid Receptors

SuperBiHelix method for predicting the pleiotropic ensemble of G-protein–coupled receptor conformations

Naturally evolved G protein-coupled receptors adopt metastable conformations

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