Activation of protein kinase B by adenosine A1 and A3 receptors in newborn rat cardiomyocytes

It is well established that adenosine receptors are involved in cardioprotection and that protein kinase B (PKB) is associated with cell survival. Therefore, in this study we have investigated whether adenosine receptors (A1, A2A and A3) activate PKB by Western blotting and determined the involvement of phosphatidylinositol 3-kinase (PI-3K)/PKB in adenosine-induced preconditioning in cultured newborn rat cardiomyocytes. Adenosine (non-selective agonist), CPA (A1 selective agonist) and Cl-IB-MECA (A(3) selective agonist) all increased PKB phosphorylation in a time- and concentration-dependent manner. The combined maximal response to CPA and Cl-IB-MECA was similar to the increase in PKB phosphorylation induced by adenosine alone. CGS 21680 (A2A selective agonist) did not stimulate an increase in PKB phosphorylation. Adenosine, CPA and Cl-IB-MECA-mediated PKB phosphorylation were inhibited by pertussis toxin (PTX blocks G(i)/G(o)-protein), genistein (tyrosine kinase inhibitor), PP2 (Src tyrosine kinase inhibitor) and by the epidermal growth factor (EGF) receptor tyrosine kinase inhibitor AG 1478. The PI-3K inhibitors wortmannin and LY 294002 blocked A(1) and A(3) receptor-mediated PKB phosphorylation. The role of PI-3K/PKB in adenosine-induced preconditioning was assessed by monitoring Caspase 3 activity and lactate dehydrogenase (LDH) release induced by exposure of cardiomyocytes to 4 h hypoxia (0.5% O2) followed by 18 h reoxygenation (HX4/R). Pre-treatment with wortmannin had no significant effect on the ability of adenosine-induced preconditioning to reduce the release of LDH or Caspase 3 activation following HX4/R. In conclusion, we have shown for the first time that adenosine A1 and A3 receptors trigger increases in PKB phosphorylation in rat cardiomyocytes via a G1/G0-protein and tyrosine kinase-dependent pathway. However, the PI-3K/PKB pathway does not appear to be involved in adenosine-induced cardioprotection by preconditioning Adenosine A1 receptor .

CGRP receptors:A headache to study, but will antagonists prove therapeutic in migraine?

The 4th International Symposium on CGRP was expertly organized, at a difficult time, by Inger Jansen-Olesen and Lars Edvinsson and held on 28-30 September 2001 at the Royal Danish School of Pharmacy, Copenhagen, Denmark.

A multigene family encoding R-SNAREs in the ciliate Paramecium tetraurelia

SNARE proteins (soluble N-ethylmaleimide-sensitive factor attachment protein receptors) mediate membrane interactions and are conventionally divided into Q-SNAREs and R-SNAREs according to the possession of a glutamine or arginine residue at the core of their SNARE domain. Here, we describe a set of R-SNAREs from the ciliate Paramecium tetraurelia consisting of seven families encoded by 12 genes that are expressed simultaneously. The complexity of the endomembrane system in Paramecium can explain this high number of genes. All P. tetraurelia synaptobrevins (PtSybs) possess a SNARE domain and show homology to the Longin family of R-SNAREs such as Ykt6, Sec22 and tetanus toxin-insensitive VAMP (TI-VAMP). We localized four exemplary PtSyb subfamilies with GFP constructs and antibodies on the light and electron microscopic level. PtSyb1-1, PtSyb1-2 and PtSyb3-1 were found in the endoplasmic reticulum, whereas PtSyb2 is localized exclusively in the contractile vacuole complex. PtSyb6 was found cytosolic but also resides in regularly arranged structures at the cell cortex (parasomal sacs), the cytoproct and oral apparatus, probably representing endocytotic compartments. With gene silencing, we showed that the R-SNARE of the contractile vacuole complex, PtSyb2, functions to maintain structural integrity as well as functionality of the osmoregulatory system but also affects cell division.

Oxidised LDL-lipids alter redox ratio, lipid raft formation and increase amyloid beta production by SHSY-5Y cells

Elevated cholesterol in mid-life has been associated with increased risk of dementia in later life. We have previously shown that low density lipoprotein (LDL) is more oxidised in the plasma of dementia patients although total cholesterol levels remained unchanged [1]. We have investigated the hypothesis that amyloid beta production and neurodegeneration can be driven by oxidised lipids derived from LDL following the loss of blood brain barrier integrity with ageing. Therefore, we have investigated amyloid beta formation in SHSY5Y cells treated with LDL, minimally modified (ox) LDL, and lipids extracted from both forms of LDL. LDL-treated SHSY-5Y cell viability was not significantly decreased with up to 8 μg LDL/2 × 104 cells compared to untreated cells. However, 8 μg oxLDL protein/2 × 104 cells decreased the cell viability significantly by 33.7% (P < 0.05). A more significant decrease in cell viability was observed when treating cells with extracted lipids from 8 μg of LDL (by 32.7%; P < 0.01) and oxLDL (by 41%; P < 0.01). In parallel, the ratio of reduced to oxidised GSH was decreased; GSH concentrations were significantly decreased following treatment with 0.8 μg/ml oxLD-L (7.35 ± 0.58;P < 0.01), 1.6 μg/ml (5.27 ± 0.23; P < 0.001) and 4 μg/ml (5.31 ± 0.31; P < 0.001). This decrease in redox potential was associated with an increase acid sphingomyelinase activity and lipid raft formation which could be inhibited by desipramine; SHSY5Y cells treated with oxLDL, and lipids from LDL and oxLDL for 16 h showed significantly increased acid sphingomyelinase activity (5.32 ± 0.35; P < 0.05, 5.21 ± 0.6; P < 0.05, and 5.58 ± 0.44; P < 0.01, respectively) compared to control cells (2.96 ± 0.34). As amyloid beta production is driven by the activity of beta secretase and its association with lipid rafts, we investigated whether lipids from ox-LDL can influence amyloid beta by SHSY-5Y cells in the presence of oxLDL. Using ELISA and Western blot, we confirmed that secretion of amyloid beta oligomers is increased by SHSY-5Y cells in the presence of oxLDL lipids. These data suggest a mechanism whereby LDL, and more significantly oxLDL lipids, can drive amyloid beta production and cytotoxicity in neuronal cells. [1] Li L, Willets RS, Polidori MC, Stahl W, Nelles G, Sies H, Griffiths HR. Oxidative LDL modification is increased in vascular dementia and is inversely associated with cognitive performance. Free Radic Res. 2010 Mar; 44(3): 241–8.

Family resemblances? Ligand binding and activation of family A and B G-protein-coupled receptors

In April 2007, the Biochemical Society held a meeting to compare and contrast ligand binding and activation of Family A and B GPCRs (G-protein-coupled receptors). Being the largest class, Family A GPCRs usually receive the most attention, although a previous Biochemical Society meeting has focused on Family B GPCRs. The aim of the present meeting was to bring researchers of both families together in order to identify commonalities between the two. The present article introduces the proceedings of the meeting, briefly commenting on the focus of each of the following articles. ©The Authors.

A key role for transmembrane prolines in calcitonin receptor-like receptor agonist binding and signalling:implications for family B G-protein-coupled receptors

Calcitonin receptor like-receptor is a family B G-protein coupled receptor (GPCR). It requires receptor activity modifying protein (RAMP) 1 to give a calcitonin gene-related peptide (CGRP) receptor. Little is known of how members of this receptor family function. Proline residues often form important kinks in alpha-helices. Therefore, all proline residues within the transmembrane helices of the receptor (Pro241, Pro244 in helix 4, Pro275 in helix 5, Pro321 and Pro331 in helix 6) were mutated to alanine. Pro241 Pro275, and Pro321 are highly conserved throughout all family B GPCRs. The binding of CGRP and its ability to stimulate cAMP production were investigated in mutant and wild-type receptors after transient transfection into COS-7 cells with RAMP1. The P321A mutation significantly decreased the pEC(50) for CGRP and reduced its affinity but did not change cell-surface expression. Antagonist binding [CGRP(8-37) and 1-piperidinecarboxamide N-[2-[[5amino-1-[[4-(4-pyridinyl)-1-piperazinyl]carbonyl]pentyl]amino]-1-[(3 5-dibromo-4-hydroxyphenyl)methyl]-2-oxoethyl]-4-(1,4-dihydro-2-oxo-3(2H)-quina zolinyl) (BIBN4096BS)] was little altered by the mutation. Adrenomedullin-mediated signaling was disrupted when P321A was coexpressed with RAMP1, RAMP2, or RAMP3. The P331A mutant produced a moderate reduction in CGRP binding and receptor activation. Mutation of the other residues had no effect on receptor function. Thus, Pro321 and Pro331 are required for agonist binding and receptor activation. Modeling suggested that Pro321 induces a bend in helix 6, bringing its C terminus near that of helix 3, as seen in many family A GPCRs. This is abolished in P321A. P321A-I325P predicted to restore this conformation, showed wild-type activation. Modeling can also rationalize the effects of transmembrane proline mutants previously reported for another family B GPCR, the VPAC(1) receptor.

RAMPs and the modulation of G-protein coupled receptors

Receptor activity modifying proteins (RAMPs) are a family of three proteins that can interact with G-protein coupled receptors (GPCRs) to create new receptors and also alter the signalling and trafficing of existing receptors. There are frequently changes in RAMP expression in cardiovascular disease RAMPs represent important drug targets.

Present perspectives on the automated classification of the G-protein coupled receptors (GPCRs) at the protein sequence level

The G-protein coupled receptors--or GPCRs--comprise simultaneously one of the largest and one of the most multi-functional protein families known to modern-day molecular bioscience. From a drug discovery and pharmaceutical industry perspective, the GPCRs constitute one of the most commercially and economically important groups of proteins known. The GPCRs undertake numerous vital metabolic functions and interact with a hugely diverse range of small and large ligands. Many different methodologies have been developed to efficiently and accurately classify the GPCRs. These range from motif-based techniques to machine learning as well as a variety of alignment-free techniques based on the physiochemical properties of sequences. We review here the available methodologies for the classification of GPCRs. Part of this work focuses on how we have tried to build the intrinsically hierarchical nature of sequence relations, implicit within the family, into an adaptive approach to classification. Importantly, we also allude to some of the key innate problems in developing an effective approach to classifying the GPCRs: the lack of sequence similarity between the six classes that comprise the GPCR family and the low sequence similarity to other family members evinced by many newly revealed members of the family.

Secretin family (Class B) G protein-coupled receptors - from molecular to clinical perspectives

Family B G protein-coupled receptors represent an important but under-researched group of receptors. This edition of the British Journal of Pharmacology considers the roles and pharmacology of a number of these receptors. Whilst common themes emerge, it is clear that more work is needed to understand the details of each receptor in order to properly exploit them therapeutically.

Hierarchical classification of G-protein-coupled receptors with data-driven selection of attributes and classifiers

We address the important bioinformatics problem of predicting protein function from a protein's primary sequence. We consider the functional classification of G-Protein-Coupled Receptors (GPCRs), whose functions are specified in a class hierarchy. We tackle this task using a novel top-down hierarchical classification system where, for each node in the class hierarchy, the predictor attributes to be used in that node and the classifier to be applied to the selected attributes are chosen in a data-driven manner. Compared with a previous hierarchical classification system selecting classifiers only, our new system significantly reduced processing time without significantly sacrificing predictive accuracy.

In silico identification of novel G protein coupled receptors

G-protein coupled receptors (GPCRs) are a superfamily of membrane integral proteins responsible for a large number of physiological functions. Approximately 50% of marketed drugs are targeted toward a GPCR. Despite showing a high degree of structural homology, there is a large variance in sequence within the GPCR superfamily which has lead to difficulties in identifying and classifying potential new GPCR proteins. Here the various computational techniques that can be used to characterize a novel GPCR protein are discussed, including both alignment-based and alignment-free approaches. In addition, the application of homology modeling to building the three-dimensional structures of GPCRs is described.

Similarity between class A and class B G-protein-coupled receptors exemplified through calcitonin gene-related peptide receptor modelling and mutagenesis studies

Modelling class B G-protein-coupled receptors (GPCRs) using class A GPCR structural templates is difficult due to lack of homology. The plant GPCR, GCR1, has homology to both class A and class B GPCRs. We have used this to generate a class A-class B alignment, and by incorporating maximum lagged correlation of entropy and hydrophobicity into a consensus score, we have been able to align receptor transmembrane regions. We have applied this analysis to generate active and inactive homology models of the class B calcitonin gene-related peptide (CGRP) receptor, and have supported it with site-directed mutagenesis data using 122 CGRP receptor residues and 144 published mutagenesis results on other class B GPCRs. The variation of sequence variability with structure, the analysis of polarity violations, the alignment of group-conserved residues and the mutagenesis results at 27 key positions were particularly informative in distinguishing between the proposed and plausible alternative alignments. Furthermore, we have been able to associate the key molecular features of the class B GPCR signalling machinery with their class A counterparts for the first time. These include the [K/R]KLH motif in intracellular loop 1, [I/L]xxxL and KxxK at the intracellular end of TM5 and TM6, the NPXXY/VAVLY motif on TM7 and small group-conserved residues in TM1, TM2, TM3 and TM7. The equivalent of the class A DRY motif is proposed to involve Arg(2.39), His(2.43) and Glu(3.46), which makes a polar lock with T(6.37). These alignments and models provide useful tools for understanding class B GPCR function.

G-protein-coupled receptors:from structural insights to functional mechanisms

The papers resulting from the recent Biochemical Society Focused Meeting 'G-Protein-Coupled Receptors: from Structural Insights to Functional Mechanisms' held in Prato in September 2012 are introduced in the present overview. A number of future goals for GPCR (G-protein-coupled receptor) research are considered, including the need to develop biophysical and computational methods to explore the full range of GPCR conformations and their dynamics, the need to develop methods to take this into account for drug discovery and the importance of relating observations on isolated receptors or receptors expressed in model systems to receptor function in vivo. © 2013 Biochemical Society.

On the hierarchical classification of G protein-coupled receptors

MOTIVATION: G protein-coupled receptors (GPCRs) play an important role in many physiological systems by transducing an extracellular signal into an intracellular response. Over 50% of all marketed drugs are targeted towards a GPCR. There is considerable interest in developing an algorithm that could effectively predict the function of a GPCR from its primary sequence. Such an algorithm is useful not only in identifying novel GPCR sequences but in characterizing the interrelationships between known GPCRs. RESULTS: An alignment-free approach to GPCR classification has been developed using techniques drawn from data mining and proteochemometrics. A dataset of over 8000 sequences was constructed to train the algorithm. This represents one of the largest GPCR datasets currently available. A predictive algorithm was developed based upon the simplest reasonable numerical representation of the protein's physicochemical properties. A selective top-down approach was developed, which used a hierarchical classifier to assign sequences to subdivisions within the GPCR hierarchy. The predictive performance of the algorithm was assessed against several standard data mining classifiers and further validated against Support Vector Machine-based GPCR prediction servers. The selective top-down approach achieves significantly higher accuracy than standard data mining methods in almost all cases.