17 resultados para Gpcr

em QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast


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Despite tremendous successes of GPCR crystallography, the receptors with available structures represent only a small fraction of human GPCRs. An important role of the modeling community is to maximize structural insights for the remaining receptors and complexes. The community-wide GPCR Dock assessment was established to stimulate and monitor the progress in molecular modeling and ligand docking for GPCRs. The four targets in the present third assessment round presented new and diverse challenges for modelers, including prediction of allosteric ligand interaction and activation states in 5-hydroxytryptamine receptors 1B and 2B, and modeling by extremely distant homology for smoothened receptor. Forty-four modeling groups participated in the assessment. State-of-the-art modeling approaches achieved close-to-experimental accuracy for small rigid orthosteric ligands and models built by close homology, and they correctly predicted protein fold for distant homology targets. Predictions of long loops and GPCR activation states remain unsolved problems.

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The community-wide GPCR Dock assessment is conducted to evaluate the status of molecular modeling and ligand docking for human G protein-coupled receptors. The present round of the assessment was based on the recent structures of dopamine D3 and CXCR4 chemokine receptors bound to small molecule antagonists and CXCR4 with a synthetic cyclopeptide. Thirty-five groups submitted their receptor-ligand complex structure predictions prior to the release of the crystallographic coordinates. With closely related homology modeling templates, as for dopamine D3 receptor, and with incorporation of biochemical and QSAR data, modern computational techniques predicted complex details with accuracy approaching experimental. In contrast, CXCR4 complexes that had less-characterized interactions and only distant homology to the known GPCR structures still remained very challenging. The assessment results provide guidance for modeling and crystallographic communities in method development and target selection for further expansion of the structural coverage of the GPCR universe.

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G-protein coupled receptors (GPCRs) are the targets of over half of all prescribed drugs today. The UniProt database has records for about 800 proteins classified as GPCRs, but drugs have only been developed against 50 of these. Thus, there is huge potential in terms of the number of targets for new therapies to be designed. Several breakthroughs in GPCRs biased pharmacology, structural biology, modelling and scoring have resulted in a resurgence of interest in GPCRs as drug targets. Therefore, an international conference, sponsored by the Royal Society, with world-renowned researchers from industry and academia was recently held to discuss recent progress and highlight key areas of future research needed to accelerate GPCR drug discovery. Several key points emerged. Firstly, structures for all three major classes of GPCRs have now been solved and there is increasing coverage across the GPCR phylogenetic tree. This is likely to be substantially enhanced with data from x-ray free electron sources as they move beyond proof of concept. Secondly, the concept of biased signalling or functional selectivity is likely to be prevalent in many GPCRs, and this presents exciting new opportunities for selectivity and the control of side effects, especially when combined with increasing data regarding allosteric modulation. Thirdly, there will almost certainly be some GPCRs that will remain difficult targets because they exhibit complex ligand dependencies and have many metastable states rendering them difficult to resolve by crystallographic methods. Subtle effects within the packing of the transmembrane helices are likely to mask and contribute to this aspect, which may play a role in species dependent behaviour. This is particularly important because it has ramifications for how we interpret pre-clinical data. In summary, collaborative efforts between industry and academia have delivered significant progress in terms of structure and understanding of GPCRs and will be essential for resolving problems associated with the more difficult targets in the future.

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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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The role of rhodopsin as a structural prototype for the study of the whole superfamily of G protein-coupled receptors (GPCRs) is reviewed in an historical perspective. Discovered at the end of the nineteenth century, fully sequenced since the early 1980s, and with direct three-dimensional information available since the 1990s, rhodopsin has served as a platform to gather indirect information on the structure of the other superfamily members. Recent breakthroughs have elicited the solution of the structures of additional receptors, namely the beta 1- and beta 2-adrenergic receptors and the A(2A) adenosine receptor, now providing an opportunity to gauge the accuracy of homology modeling and molecular docking techniques and to perfect the computational protocol. Notably, in coordination with the solution of the structure of the A(2A) adenosine receptor, the first "critical assessment of GPCR structural modeling and docking" has been organized, the results of which highlighted that the construction of accurate models, although challenging, is certainly achievable. The docking of the ligands and the scoring of the poses clearly emerged as the most difficult components. A further goal in the field is certainly to derive the structure of receptors in their signaling state, possibly in complex with agonists. These advances, coupled with the introduction of more sophisticated modeling algorithms and the increase in computer power, raise the expectation for a substantial boost of the robustness and accuracy of computer-aided drug discovery techniques in the coming years.

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Rhodopsin, the light sensitive receptor responsible for blue-green vision, serves as a prototypical G protein-coupled receptor (GPCR). Upon light absorption, it undergoes a series of conformational changes that lead to the active form, metarhodopsin II (META II), initiating a signaling cascade through binding to the G protein transducin (G(t)). Here, we first develop a structural model of META II by applying experimental distance restraints to the structure of lumi-rhodopsin (LUMI), an earlier intermediate. The restraints are imposed by using a combination of biased molecular dynamics simulations and perturbations to an elastic network model. We characterize the motions of the transmembrane helices in the LUMI-to-META II transition and the rearrangement of interhelical hydrogen bonds. We then simulate rhodopsin activation in a dynamic model to study the path leading from LUMI to our META II model for wild-type rhodopsin and a series of mutants. The simulations show a strong correlation between the transition dynamics and the pharmacological phenotypes of the mutants. These results help identify the molecular mechanisms of activation in both wild type and mutant rhodopsin. While static models can provide insights into the mechanisms of ligand recognition and predict ligand affinity, a dynamic model of activation could be applicable to study the pharmacology of other GPCRs and their ligands, offering a key to predictions of basal activity and ligand efficacy.

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Accurate 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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G protein-coupled receptors (GPCRs) are a large superfamily of signaling proteins expressed on the plasma membrane. They are involved in a wide range of physiological processes and, therefore, are exploited as drug targets in a multitude of therapeutic areas. In this extent, knowledge of structural and functional properties of GPCRs may greatly facilitate rational design of modulator compounds. Solution and solid-state nuclear magnetic resonance (NMR) spectroscopy represents a powerful method to gather atomistic insights into protein structure and dynamics. In spite of the difficulties inherent the solution of the structure of membrane proteins through NMR, these methods have been successfully applied, sometimes in combination with molecular modeling, to the determination of the structure of GPCR fragments, the mapping of receptor-ligand interactions, and the study of the conformational changes associated with the activation of the receptors. In this review, we provide a summary of the NMR contributions to the study of the structure and function of GPCRs, also in light of the published crystal structures.

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GPR40, free fatty acid receptor 1 (FFAR1), is a member of the GPCR superfamily and a possible target for the treatment of type 2 diabetes. In this work, we conducted a bidirectional iterative investigation, including computational modeling and site-directed mutagenesis, aimed at delineating amino acid residues forming the functional "chemoprint" of GPR40 for agonist recognition. The computational and experimental studies revolved around the recognition of the potent synthetic agonist GW9508. Our experimentally supported model suggested that H137(4.56), R183(5.39), N244(6.55), and R258(7.35) are directly involved in interactions with the ligand. We have proposed a polarized NH-pi interaction between H137(4.56) and GW9508 as one of the contributing forces leading to the high potency of GW9508. The modeling approach presented in this work provides a general strategy for the exploration of receptor-ligand interactions in G-protein coupled receptors beginning prior to acquisition of experimental data.

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P2Y(1) is an ADP-activated G protein-coupled receptor (GPCR). Its antagonists impede platelet aggregation in vivo and are potential antithrombotic agents. Combining ligand and structure-based modeling we generated a consensus model (LIST-CM) correlating antagonist structures with their potencies. We docked 45 antagonists into our rhodopsin-based human P2Y(1) homology model and calculated docking scores and free binding energies with the Linear Interaction Energy (LIE) method in continuum-solvent. The resulting alignment was also used to build QSAR based on CoMFA, CoMSIA, and molecular descriptors. To benefit from the strength of each technique and compensate for their limitations, we generated our LIST-CM with a PLS regression based on the predictions of each methodology. A test set featuring untested substituents was synthesized and assayed in inhibition of 2-MeSADP-stimulated PLC activity and in radioligand binding. LIST-CM outperformed internal and external predictivity of any individual model to predict accurately the potency of 75% of the test set.

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Computer-aided drug design becomes an important part of G-protein coupled receptors (GPCR) drug discovery process that is applied for improving the efficiency of derivation and optimization of novel ligands. It represents the combination of methods that-use-structural information of a receptor binding site of known ligands to design new ligands. In this report, we give a brief description of ligand binding sites in cholecystokinin and gastrin receptors (CK1R and CCK2R) which were delineated using experimental and computational methods, and then, we show how the validated ligand binding sites can be used to design and improve novel ligands. The translation of the knowledge of ligand-binding sites of different GPCRs to computer-aided design of novel ligands is summarized.

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Restrictions on nematicide usage underscore the need for novel control strategies for plant pathogenic nematodes such as Globodera pallida (potato cyst nematode) that impose a significant economic burden on plant cultivation activities. The nematode neuropeptide signalling system is an attractive resource for novel control targets as it plays a critical role in sensory and motor functions. The FMRFamide-like peptides (FLPs) form the largest and most diverse family of neuropeptides in invertebrates, and are structurally conserved across nematode species, highlighting the utility of the FLPergic system as a broad-spectrum control target. flp-32 is expressed widely across nematode species. This study investigates the role of flp-32 in G. pallida and shows that: (i) Gp-flp-32 encodes the peptide AMRNALVRFamide; (ii) Gp-flp-32 is expressed in the brain and ventral nerve cord of G. pallida; (iii) migration rate increases in Gp-flp-32-silenced worms; (iv) the ability of G. pallida to infect potato plant root systems is enhanced in Gp-flp-32-silenced worms; (v) a novel putative Gp-flp-32 receptor (Gp-flp-32R) is expressed in G. pallida; and, (vi) Gp-flp-32R silenced worms also display an increase in migration rate. This work demonstrates that Gp30 flp-32 plays an intrinsic role in the modulation of locomotory behaviour in G. pallida, and putatively interacts with at least one novel G-protein coupled receptor (Gp-flp-32R). This is the first functional characterisation of a parasitic nematode FLP-GPCR. © 2013 Atkinson et al.

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The biased agonism of the G protein-coupled receptors (GPCRs), where in addition to a traditional G protein-signalling pathway a GPCR promotes intracellular signals though ß-arrestin, is a novel paradigm in pharmacology. Biochemical and biophysical studies have suggested that a GPCR forms a distinct ensemble of conformations signalling through the G protein and ß-arrestin. Here we report on the dynamics of the ß2 adrenergic receptor bound to the ß-arrestin and G protein biased agonists and the empty receptor to further characterize the receptor conformational changes caused by biased agonists. We use conventional and accelerated molecular dynamics (aMD) simulations to explore the conformational transitions of the GPCR from the active state to the inactive state. We found that aMD simulations enable monitoring the transition within the nanosecond timescale while capturing the known microscopic characteristics of the inactive states, such as the ionic lock, the inward position of F6.44, and water clusters. Distinct conformational states are shown to be stabilized by each biased agonist. In particular, in simulations of the receptor with the ß-arrestin biased agonist, N-cyclopentylbutanepherine we observe a different pattern of motions in helix 7 when compared to simulations with the G protein biased agonist, Salbutamol that involves perturbations of the network of interactions within the NPxxY motif. Understanding the network of interactions induced by biased ligands and the subsequent receptor conformational shifts will lead to development of more efficient drugs. © 2013 American Chemical Society

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BACKGROUND: The free fatty acid receptors (FFAs), including FFA1 (orphan name: GPR40), FFA2 (GPR43) and FFA3 (GPR41) are G protein-coupled receptors (GPCRs) involved in energy and metabolic homeostasis. Understanding the structural basis of ligand binding at FFAs is an essential step toward designing potent and selective small molecule modulators.

RESULTS: We analyse earlier homology models of FFAs in light of the newly published FFA1 crystal structure co-crystallized with TAK-875, an ago-allosteric ligand, focusing on the architecture of the extracellular binding cavity and agonist-receptor interactions. The previous low-resolution homology models of FFAs were helpful in highlighting the location of the ligand binding site and the key residues for ligand anchoring. However, homology models were not accurate in establishing the nature of all ligand-receptor contacts and the precise ligand-binding mode. From analysis of structural models and mutagenesis, it appears that the position of helices 3, 4 and 5 is crucial in ligand docking. The FFA1-based homology models of FFA2 and FFA3 were constructed and used to compare the FFA subtypes. From docking studies we propose an alternative binding mode for orthosteric agonists at FFA1 and FFA2, involving the interhelical space between helices 4 and 5. This binding mode can explain mutagenesis results for residues at positions 4.56 and 5.42. The novel FFAs structural models highlight higher aromaticity of the FFA2 binding cavity and higher hydrophilicity of the FFA3 binding cavity. The role of the residues at the second extracellular loop used in mutagenesis is reanalysed. The third positively-charged residue in the binding cavity of FFAs, located in helix 2, is identified and predicted to coordinate allosteric modulators.

CONCLUSIONS: The novel structural models of FFAs provide information on specific modes of ligand binding at FFA subtypes and new suggestions for mutagenesis and ligand modification, guiding the development of novel orthosteric and allosteric chemical probes to validate the importance of FFAs in metabolic and inflammatory conditions. Using our FFA homology modelling experience, a strategy to model a GPCR, which is phylogenetically distant from GPCRs with the available crystal structures, is discussed.

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FMRFamide-like peptide (FLP) receptors are appealing as putative anthelmintic targets. To date, 31 flp-encoding genes have been identified in Caenorhabditis elegans and thirteen FLP-activated G-protein coupled receptors (FLP-GPCRs) have been reported. The lack of knowledge on FLPs and FLP-GPCRs in parasites impedes their functional characterisation and chemotherapeutic exploitation. Using homology-based BLAST searches and phylogenetic analyses this study describes the identification of putative flp and flp-GPCR gene homologues in 17 nematode parasites providing the first pan-phylum genome-based overview of the FLPergic complement. These data will facilitate FLP-receptor deorphanisation efforts in the quest for novel control targets for nematode parasites.