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Search Results: 1 - 10 of 77 matches for " GPCR "
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A brief review on the evolution of GPCR: conservation and diversification  [PDF]
Zaichao Zhang, Jiayan Wu, Jun Yu, Jingfa Xiao
Open Journal of Genetics (OJGen) , 2012, DOI: 10.4236/ojgen.2012.24B003
Abstract: G-protein couple receptors (GPCR) possess diversified functions and they comprise a large protein superfamily in cellular signaling. Numerous identification methods for GPCR have been employed and versatile GPCR types are discussed. Although they share conserved transmembrane structural topology, alignment results of all GPCR show no significant sequence similarities. Each GPCR type distributes diversely in different evolutionary hierarchies of eukaryotes, but it has a distinctive boundary in the era of metazoan. The common ancestor of GPCR metabotropic glutamate receptor includes 7-transmembrane structure and venus flytrap module, which is probably evolved from a compound of bacteriorhodopsin and periplasmic binding protein. Many investigations focus on fine structure shaping and GPCR classification. Here, we briefly discuss evolutionary dynamic mechanism of GPCR from the perspective of classification, diversification and conservation.
Dual-Color Bioluminescence Analysis for Quantitatively Monitoring G-Protein-Coupled Receptor and β-Arrestin Interactions
A.K.M. Kafi,Mitsuru Hattori,Naomi Misawa,Takeaki Ozawa
Pharmaceuticals , 2011, DOI: 10.3390/ph4030457
Abstract: G protein-coupled receptors (GPCRs) are crucial elements in mammalian signal transduction, and are considered to represent potent drug targets. We have previously developed a GPCR assay system in cultured cells based on complementation of split fragments of click beetle ( Pyrearinus termitilluminans) luciferase. The interaction of GPCRs with its target, β-arrestin, resulted in strong emission of bioluminescence upon stimulation with its specific ligand. In this study, we improved precision of the GPCR assay system by using railroad worm ( Phrixothrix hirtus) luciferase as an internal control. We generated stable cell lines harboring the railroad worm luciferase and quantitatively evaluate the extent of GPCR-β-arrestin interactions. We showed concentration-dependent bioluminescence responses for four GPCRs: β2-adrenoceptor, endothelin receptor type A, α2-adrenoceptor and human μ-opioid receptor. We also demonstrated that the variation of responses was reduced significantly by normalizing the data with bioluminescence from railroad worm luciferase. This assay system represents a simple and reliable approach for screening drug candidates in a high throughput manner.
Expanding the Concept of G Protein-Coupled Receptor (GPCR) Dimer Asymmetry towards GPCR-Interacting Proteins
Maud Kamal,Pascal Maurice,Ralf Jockers
Pharmaceuticals , 2011, DOI: 10.3390/ph4020273
Abstract: G protein-coupled receptors (GPCRs), major targets of drug discovery, are organized in dimeric and/or oligomeric clusters. The minimal oligomeric unit, the dimer, is composed of two protomers, which can behave differently within the dimer. Several examples of GPCR asymmetry within dimers at the level of ligand binding, ligand-promoted conformational changes, conformational changes within transmembrane domains, G protein coupling, and most recently GPCR-interacting proteins (GIPs), have been reported in the literature. Asymmetric organization of GPCR dimers has important implications on GPCR function and drug design. Indeed, the extension of the “asymmetry concept” to GIPs adds a new level of specific therapeutic intervention.
Functional Consequences of GPCR Heterodimerization: GPCRs as Allosteric Modulators
Karla K.V. Haack,Nael A. McCarty
Pharmaceuticals , 2011, DOI: 10.3390/ph4030509
Abstract: G Protein Coupled Receptors (GPCRs) represent the largest family of membrane proteins in the human genome, are the targets of approximately 25% of all marketed pharmaceuticals, and the focus of intensive research worldwide given that this superfamily of receptors is as varied in function as it is ubiquitously expressed among all cell types. Increasing evidence has shown that the classical two part model of GPCR signaling (one GPCR, one type of heterotrimeric G protein) is grossly oversimplified as many GPCRs can couple to more than one type of G protein, each subunit of the heterotrimeric G protein can activate different downstream effectors, and, surprisingly, other GPCRs can affect receptor behavior in G protein-independent ways. The concept of GPCR heterodimerization, or the physical association of two different types of GPCRs, presents an unexpected mechanism for GPCR regulation and function, and provides a novel target for pharmaceuticals. Here we present a synopsis of the functional consequences of GPCR heterodimerization in both in vitro and in vivo studies, focusing on the concept of GPCRs as allosteric modulators. Typically, an allosteric modulator is a ligand or molecule that alters a receptor’s innate functional properties, but here we propose that in the case of GPCR heterodimers, it is the physical coupling of two receptors that leads to changes in cognate receptor signaling.
Hydrophobicity profiles in G protein-coupled receptor transmembrane helical domains
Chiquito J Crasto
Journal of Receptor, Ligand and Channel Research , 2010, DOI: http://dx.doi.org/10.2147/JRLCR.S14437
Abstract: rophobicity profiles in G protein-coupled receptor transmembrane helical domains Original Research (2436) Total Article Views Authors: Chiquito J Crasto Published Date December 2010 Volume 2010:3 Pages 123 - 133 DOI: http://dx.doi.org/10.2147/JRLCR.S14437 Chiquito J Crasto Division of Research, Department of Genetics, University of Alabama at Birmingham, Alabama, USA Abstract: The lack of a crystallographically derived structure for all but three G (TP [guanosine triphosphate]-binding) protein-coupled receptor (GPCRs) proteins necessitates the use of computationally derived methods to determine their structures. Computational methodologies allow a mechanistic glimpse into GPCR–ligand interactions at a molecular level to better understand the initial steps leading to a protein's biologic functions, ie, protecting the ligands that activate, deactivate, or inhibit the protein, stabilizing protein structure in the membrane's lipid bilayer, and ensuring that the hydrophilic environment within the GPCR-binding pocket is maintained. Described here is a formalism that quantifies the amphiphilic nature of a helix, by determining the effective hydrophobicity (or hydrophilicity) at specific positions around it. This formalism will enable computational protein modelers to position helices so that the functional aspects of GPCRs are adequately represented in the model. Hydro-Eff , an online tool, allows users to calculate effective helical hydrophobicities.
Interaction between Peptide Pheromone or Its Truncated Derivatives and Pheromone Receptor of the Fission Yeast Schizosaccharomyces pombe Examined by a Force Spectroscopy Study and a GFP Reporter Assay  [PDF]
Sho Hidaka, Osamu Nikaido, Shoichi Kiyosaki, Atsushi Ikai, Toshiya Osada
Journal of Surface Engineered Materials and Advanced Technology (JSEMAT) , 2013, DOI: 10.4236/jsemat.2013.34A1005
Abstract:

In our previous study, the specific interaction between P-factor, a peptide pheromone and its receptor, Mam2, on the cell surface of the fission yeast Schizosaccharomyces pombe was investigated by two methods, an atomic force microscope (AFM) and a GFP reporter assay. The removal of Leu at C-terminal of P-factor resulted in an inactivation of P-factor function to bind Mam2 and induce the signal transduction pathway. Here, we used truncated P-factor derivatives lacking N-terminal of P-factor (P12 ~ P22: 12 ~ 22 amino acid residues from C-terminal) as ligands for Mam2. From the dose-dependent analysis of the GFP reporter assay ranging from 1 nM to 100 μM of the peptide concentration, the peptides can be classified into three groups based on EC50 and maximal GFP production level, group1 (P-factor), group2 (P17 ~ 22), and group3 (P12 ~ P16). At 0.1 μM, only P-factor induced the signal transduction pathway. At 1 μM, peptides from group2 partially induced the pathway and peptides from group3 induced the pathway a little. At 10 μM, all peptides induced the pathway mostly depending on the length of peptides. We also performed AFM experiments using P-factor and peptides from group3 to investigate the interaction between the peptides and Mam2 for comparison between the two methods.

Contribution of PGE2 EP1 receptor in hemin-induced neurotoxicity
Shekher Mohan,Alexander V. Glushakov,Alexander deCurnou,Sylvain Doré
Frontiers in Molecular Neuroscience , 2013, DOI: 10.3389/fnmol.2013.00031
Abstract: Although hemin-mediated neurotoxicity has been linked to the production of free radicals and glutamate excitotoxicity, the role of the prostaglandin E2 (PGE2)-EP1 receptor remains unclear. Activation of the EP1 receptor in neurons results in increased intracellular calcium levels; therefore, we hypothesize that the blockade of the EP1 receptor reduces hemin neurotoxicity. Using postnatal primary cortical neurons cultured from wild-type (WT) and EP1?/? mice, we investigated the EP1 receptor role in hemin neurotoxicity measured by lactate dehydrogenase (LDH) cell survival assay. Hemin (75 μM) induced greater release of LDH in WT (34.7 ± 4.5%) than in EP1?/? (27.6 ± 3.3%) neurons. In the presence of the EP1 receptor antagonist SC-51089, the hemin-induced release of LDH decreased. To further investigate potential mechanisms of action, we measured changes in the intracellular calcium level [Ca2+]i following treatment with 17-phenyl trinor PGE2 (17-pt-PGE2) a selective EP1 agonist. In the WT neurons, 17-pt-PGE2 dose-dependently increased [Ca2+]i. However, in EP1?/? neurons, [Ca2+]i was significantly attenuated. We also revealed that hemin dose-dependently increased [Ca2+]i in WT neurons, with a significant decrease in EP1?/? neurons. Both 17-pt-PGE2 and hemin-induced [Ca2+]i were abolished by N-methyl-D-aspartic (NMDA) acid receptor and ryanodine receptor blockers. These results suggest that blockade of the EP1 receptor may be protective against hemin neurotoxicity in vitro. We speculate that the mechanism of hemin neuronal death involves [Ca2+]i mediated by NMDA acid receptor-mediated extracellular Ca2+ influx and EP1 receptor-mediated intracellular release from ryanodine receptor-operated Ca2+ stores. Therefore, blockade of the EP1 receptor could be used to minimize neuronal damage following exposure to supraphysiological levels of hemin.
Functional and Structural Overview of G-Protein-Coupled Receptors Comprehensively Obtained from Genome Sequences
Makiko Suwa,Minoru Sugihara,Yukiteru Ono
Pharmaceuticals , 2011, DOI: 10.3390/ph4040652
Abstract: An understanding of the functional mechanisms of G-protein-coupled receptors (GPCRs) is very important for GPCR-related drug design. We have developed an integrated GPCR database (SEVENS http://sevens.cbrc.jp/) that includes 64,090 reliable GPCR genes comprehensively identified from 56 eukaryote genome sequences, and overviewed the sequences and structure spaces of the GPCRs. In vertebrates, the number of receptors for biological amines, peptides, etc. is conserved in most species, whereas the number of chemosensory receptors for odorant, pheromone, etc. significantly differs among species. The latter receptors tend to be single exon type or a few exon type and show a high ratio in the numbers of GPCRs, whereas some families, such as Class B and Class C receptors, have long lengths due to the presence of many exons. Statistical analyses of amino acid residues reveal that most of the conserved residues in Class A GPCRs are found in the cytoplasmic half regions of transmembrane (TM) helices, while residues characteristic to each subfamily found on the extracellular half regions. The 69 of Protein Data Bank (PDB) entries of complete or fragmentary structures could be mapped on the TM/loop regions of Class A GPCRs covering 14 subfamilies.
Advances in G-protein coupled receptor research and related bioinformatics study
Yanbin Yin,Jingchu Luo,Ying Jiang
Chinese Science Bulletin , 2003, DOI: 10.1360/03tb9108
Abstract: G-protein coupled receptor (GPCR) is one of the most important protein families for drug target. GPCR agonists and antagonists occupy approximately one third of the world small molecule drug market. Much effort has been invested in GPCR study by both academic institutions and pharmaceutical industries. With seven-transmembrane domains, GPCR plays significant roles in intercellular signal transduction and is involved in a variety of biological pathways. With the availability of sequence data of human and other mammalian genomes, as well as their expressed sequence tag (EST) data, the bioinformatics and genomics approaches can be applied to identifying novel GPCR in the post genomic era. Deorphanizing GPCR or matching ligands with GPCR greatly facilitates target validation process and automatically provides a possible compound screening assay. Similarly, bioinformatics data mining approach could also be applied to the identification of GPCR peptide or protein ligands. Here we give a general review of recent advances in the study of GPCR structure, function, as well as GPCR and ligand identification with the emphasis on the bioinformatics database mining of GPCR and their peptide or protein ligands.
A model for the evaluation of domain based classification of GPCR
Tannu Kumari,Bhaskar Pant,Kamalraj R. Pardasani
Bioinformation , 2009,
Abstract: G-Protein Coupled Receptors (GPCR) are the largest family of membrane bound receptor and plays a vital role in various biological processes with their amenability to drug intervention. They are the spotlight for the pharmaceutical industry. Experimental methods are both time consuming and expensive so there is need to develop a computational approach for classification to expedite the drug discovery process. In the present study domain based classification model has been developed by employing and evaluating various machine learning approaches like Bagging, J48, Bayes net, and Naive Bayes. Various softwares are available for predicting domains. The result and accuracy of output for the same input varies for these software’s. Thus, there is dilemma in choosing any one of it. To address this problem, a simulation model has been developed using well known five softwares for domain prediction to explore the best predicted result with maximum accuracy. The classifier is developed for classification up to 3 levels for class A. An accuracy of 98.59% by Na ve Bayes for level I, 92.07% by J48 for level II and 82.14% by Bagging for level III has been achieved.
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