Peptide and non-peptide G-protein coupled receptors (GPCRs) in skeletal muscle

G-protein coupled receptors (GPCRs) represent a large class of cell surface receptors that mediate a multitude of functions. Over the years, a number of GPCRs and ancillary proteins have been shown to be expressed in skeletal muscle. Unlike the case with other muscle tissues like cardiac and vascular smooth muscle cells, there has been little attempt at systematically analyzing GPCRs in skeletal muscle. Here we have compiled all the GPCRs that are expressed in skeletal muscle. In addition, we review the known function of these receptors in both skeletal muscle tissue and in cultured skeletal muscle cells.     

Classifying G-protein coupled receptors with support vector machines

MOTIVATION: The enormous amount of protein sequence data uncovered by genome research has increased the demand for computer software that can automate the recognition of new proteins. We discuss the relative merits of various automated methods for recognizing G-Protein Coupled Receptors (GPCRs), a superfamily of cell membrane proteins. GPCRs are found in a wide range of organisms and are central to a cellular signalling network that regulates many basic physiological processes. They are the focus of a significant amount of current pharmaceutical research because they play a key role in many diseases. However, their tertiary structures remain largely unsolved. The methods described in this paper use only primary sequence information to make their predictions. We compare a simple nearest neighbor approach (BLAST), methods based on multiple alignments generated by a statistical profile Hidden Markov Model (HMM), and methods, including Support Vector Machines (SVMs), that transform protein sequences into fixed-length feature vectors. RESULTS: The last is the most computationally expensive method, but our experiments show that, for those interested in annotation-quality classification, the results are worth the effort. In two-fold cross-validation experiments testing recognition of GPCR subfamilies that bind a specific ligand (such as a histamine molecule), the errors per sequence at the Minimum Error Point (MEP) were 13.7% for multi-class SVMs, 17.1% for our SVMtree method of hierarchical multi-class SVM classification, 25.5% for BLAST, 30% for profile HMMs, and 49% for classification based on nearest neighbor feature vector Kernel Nearest Neighbor (kernNN). The percentage of true positives recognized before the first false positive was 65% for both SVM methods, 13% for BLAST, 5% for profile HMMs and 4% for kernNN.     

Evidence for kinship between diverse G-protein coupled receptors.

In an earlier publication we described similarities at the primary sequence level between the first probable plant G-protein coupled receptor (GPCR) and three GPCR families (families A, B and F according to Kolakowski's classification) that were previously considered evolutionarily unrelated. Here we analyze further the relatedness among different GPCR families.By using PSI-BLAST, which is a search algorithm that is more potent in detecting weak similarities, one finds additional similarities between GPCR families that have not previously been described. Based on these comparisons, it is possible to divide all the GPCR families into one large clade and two smaller ones. The large clade includes the rhodopsin family (family A), the glucagon receptor family (family B), cyclic AMP receptors (family F), an Arabidopsis thaliana receptor, the Frizzled family and probably also the STE3 pheromone receptors (family E) and vomeronasal receptors type 1. The smaller clades consist of, in one case, BOSS and the GABA-B family of receptors (family C), and in the other the STE2 pheromone receptors (family D) alone. Although our findings are likely to reflect a common ancestry within each of these clades, whether or not two or all three of the clades also share an even more ancient ancestor between them remains an open question that cannot be answered from our present data.     

Functional membrane diffusion of G-protein coupled receptors

G-protein-coupled receptor function involves interactions between the receptor, G-proteins and effectors in the cell plasma membrane. The main biochemical processes have been individually identified but the mechanisms governing the successive protein–protein interactions of this complex multi-molecular machinery have yet to be established. We discuss advances in understanding the functional dynamics of the receptor resulting from diffusion measurements, and in the context of the plasma membrane organization. Aurélie Baker and Aude Saulière contributed equally to this work. Presented at the joint biannual meeting of the SFB-GEIMM-GRIP, Anglet France, 14–19 October, 2006.     

Lipid-facing correlated mutations and dimerization in G-protein coupled receptors.

A correlated mutation analysis has been performed on the aligned protein sequences of a number of class A G-protein coupled receptor families, including the chemokine, neurokinin, opioid, somatostatin, thyrotrophin and the whole biogenic amine family. Many of the correlated mutations are observed flanking or neighbouring conserved residues. The correlated residues have been plotted onto the transmembrane portion of the rhodopsin crystal structure. The structure shows that a significant proportion of the correlated mutations are located on the external (lipid-facing) region of the helices. The occurrence of these highly correlated patterns of change amongst the external residues suggest that they are sites for protein-protein interactions. In particular, it is suggested that the correlated residues may be involved in either large conformational changes, the formation of heterodimers or homodimers (which may be domain swapped) or oligomers required for activation or internalization. The results are discussed in the light of the subtype-specific heterodimerization observed for the chemokine, opioid and somatostatin receptors.     

孤儿G蛋白偶联受体研究进展

孤儿G蛋白偶联受体的研究意味着发现其尚未了解的内源性配体,是后基因组时代功能基因组学研究的热点之一,对生命科学的发展具有深 影响。本文介绍孤儿G蛋白偶联受体的概念、研究策略及其应用。     

Classification of amine type G-protein coupled receptors with feature selection

G-protein coupled receptors (GPCRs) are involved in various physiological processes. Therefore, classification of amine type GPCRs is important for proper understanding of their functions. Though some effective methods have been developed, it still remains unknown how many and which features are essential for this task. Empirical studies show that feature selection might address this problem and provide us with some biologically useful knowledge. In this paper, a feature selection technique is introduced to identify those relevant features of proteins which are potentially important for the prediction of amine type GPCRs. The selected features are finally accepted to characterize proteins in a more compact form. High prediction accuracy is observed on two data sets with different sequence similarity by 5-fold cross-validation test. The comparison with a previous method demonstrates the efficiency and effectiveness of the proposed method.     

The activation mechanism of class-C G-protein coupled receptors

Class-C G-protein coupled receptors (GPCRs) represent a distant group among the large family of GPCRs. This class includes the receptors for the main neurotransmitters, glutamate and gamma-aminobutyric acid (GABA), and the receptors for Ca(2+), some taste and pheromone molecules, as well as some orphan receptors. Like any other GPCRs, class-C receptors possess a heptahelical domain (HD) involved in heterotrimeric G-protein activation, but most of them also have a large extracellular domain (ECD) responsible for agonist recognition and binding. In addition, it is now well accepted that these receptors are dimers, either homo or heterodimers. This complex architecture raises a number of important questions. Here we will discuss our view of how agonist binding within the large ECD triggers the necessary change of conformation, or stabilize a specific conformation, of the heptahelical domain leading to G-protein activation. How ligands acting within the heptahelical domain can change the properties of these complex macromolecules.     

Bound conformations for ligands for G-protein coupled receptors

The conformation of the C-terminus of the -subunit of transducin, the G-protein of vision, has been determined by transfer NOE when bound to activated (MII) rhodopsin. One hundred three new NOE constraints are apparent when light is shown on a mixture of rhodopsin bilayers and the undecapeptide. Analogs of the -peptide with covalent constraints were designed restricting the bound conformation; they stabilize MII thus supporting the deduced structure. The NMR structure of a complex of the intracellular loops of rhodopsin facilitates docking of the -peptide and also shows proximity of residues known by mutational analysis to interact to generate the activated rhodopsin-transducin interface. This constrains the location of transmembrane helices in the structure of activated rhodopsin. Methods for the prediction of affinity have been used to estimate the relative binding constants of peptide analogs with the loop complex and show strong correlation with experimental data. Various models of the rhodopsin-transmembrane helical segments have been computationally fused with distance geometry to determine the overall model which best fits the experimental data on the rhodopsin-transducin interface.     

Signaling and regulation of G-protein coupled receptors encoded by cytomegaloviruses.

Cytomegaloviruses (CMVs) are species-specific beta-herpesviruses whose replicative success is largely due to establishment of novel mechanisms for altering the host immune response. CMV encodes 3 families of putative G-protein coupled receptors (GPCRs) likely pirated from the host cell. While the functions of these virally encoded GPCRs remain unclear, the receptors possess potent signaling abilities. Understanding the molecular regulation of these GPCRs will provide important insight into CMV pathogenesis.     

Bound conformations for ligands for G-protein coupled receptors

Summary The conformation of the C-terminus of the α-subunit of transducin, the G-protein of vision, has been determined by transfer NOE when bound to activated (MII) rhodopsin. One hundred three new NOE constraints are apparent when light is shown on a mixture of rhodopsin bilayers and the undecapeptide. Analogs of the α-peptide with covalent constraints were designed restricting the bound conformation; they stabilize MII thus supporting the deduced structure. The NMR structure of a complex of the intracellular loops of rhodopsin facilitates docking of the α-peptide and also shows proximity of residues known by mutational analysis to interact to generate the activated rhodopsin-transducin interface. This constrains the location of transmembrane helices in the structure of activated rhodopsin. Methods for the prediction of affinity have been used to estimate the relative binding constants of peptide analogs with the loop complex and show strong correlation with experimental data. Various models of the rhodopsin-transmembrane helical segments have been computationally fused with distance geometry to determine the overall model which best fits the experimental data on the rhodopsin-transducin interface.     

Calmodulin interaction with peptides from G-protein coupled receptors measured with S-Tag labeling

We have developed a quantitative assay of calmodulin (CaM) binding to S-Tag labeled peptides derived from G-protein coupled receptor (GPCR) sequences. CaM binding of peptides derived from the third intracellular loop (i3) of mu opioid receptor (MOR) was confirmed and the CaM-binding motif refined. A MORi3 peptide with a Lys > Ala substitution--shown to reduce CaM-binding of intact MOR--bound fivefold less avidly than the wild-type peptide. Screening peptides derived from i3 loops of other GPCR families confirmed 5HT1A, and identified muscarinic receptor 3, and melanocortin receptor 1, as proteins carrying CaM-binding domains. The use of S-Tag labeling can serve for rapid screening of putative CaM-binding domains in GPCRs.     

Prediction of interfaces for oligomerizations of G-protein coupled receptors

Several lines of biochemical and pharmacological evidence have suggested that some G-protein-coupled receptors (GPCRs) form homo oligomers, hetero oligomers or both. The GPCRs oligomerizations are considered to be related to signal transduction and some diseases. Therefore, an accurate prediction of the residues that interact upon oligomerization interface would further our understanding of signal transduction and the diseases in which GPCRs are involved. One of the complications for such a prediction is that the interfaces differ with the subtypes, even within the same GPCR family. Focusing on the distribution of residues conserved on the molecular surface in a particular subtype, we developed a new method to predict the interface for the GPCR oligomers, and applied it to several subtypes of known GPCRs to check the sensitivity. Subsequently, we found that predicted interfaces of rhodopsin, D(2) dopamine receptor and beta(2) adrenergic receptor agreed with the experimentally suggested interfaces, despite difference in the interface region among the three subtypes. Moreover, a highly conserved residue detected from the D(2) dopamine receptor corresponded to a residue involved in a missense change found in the large family of myoclonus dystonia. Our observation suggests the possibility that the disease is caused by the disorder of the oligomerization, although the molecular mechanism of the disease has not been revealed yet. The benefits and the pitfalls of the new method will be discussed, based on the results of the applications.     

PREDICT modeling and in-silico screening for G-protein coupled receptors

G-protein coupled receptors (GPCRs) are a major group of drug targets for which only one x-ray structure is known (the nondrugable rhodopsin), limiting the application of structure-based drug discovery to GPCRs. In this paper we present the details of PREDICT, a new algorithmic approach for modeling the 3D structure of GPCRs without relying on homology to rhodopsin. PREDICT, which focuses on the transmembrane domain of GPCRs, starts from the primary sequence of the receptor, simultaneously optimizing multiple 'decoy' conformations of the protein in order to find its most stable structure, culminating in a virtual receptor-ligand complex. In this paper we present a comprehensive analysis of three PREDICT models for the dopamine D2, neurokinin NK1, and neuropeptide Y Y1 receptors. A shorter discussion of the CCR3 receptor model is also included. All models were found to be in good agreement with a large body of experimental data. The quality of the PREDICT models, at least for drug discovery purposes, was evaluated by their successful utilization in in-silico screening. Virtual screening using all three PREDICT models yielded enrichment factors 9-fold to 44-fold better than random screening. Namely, the PREDICT models can be used to identify active small-molecule ligands embedded in large compound libraries with an efficiency comparable to that obtained using crystal structures for non-GPCR targets.     

On the role of G-protein coupled receptors in cell volume regulation.

Cell volume is determined genetically for each cell lineage, but it is not a static feature of the cell. Intracellular volume is continuously challenged by metabolic reactions, uptake of nutrients, intracellular displacement of molecules and organelles and generation of ionic gradients. Moreover, recent evidence raises the intriguing possibility that changes in cell volume act as signals for basic cell functions such as proliferation, migration, secretion and apoptosis. Cells adapt to volume increase by a complex, dynamic process resulting from the concerted action of volume sensing mechanisms and intricate signaling chains, directed to initiate the multiple adaptations demanded by a change in cell volume, among others adhesion reactions, membrane and cytoskeleton remodeling, and activation of the osmolyte pathways leading to reestablish the water balance between extracellular/intracellular or intracellular/intracellular compartments. In multicellular organisms, a continuous interaction with the external milieu is fundamental for the dynamics of the cell. It is in this sense that the recent surge of interest about the influence on cell volume control by the most extended family of signaling elements, the G proteins, acquires particular importance. As here reviewed, a large variety of G-protein coupled receptors (GPCRs) are involved in this interplay with cell volume regulatory mechanisms, which amplifies and diversifies the volume-elicited signaling chains, providing a variety of routes towards the multiple effectors related to cell volume changes.     

The relaxin peptide family and their novel G-protein coupled receptors

Relaxin-1 is a heterodimeric peptide hormone primarily produced by the pregnant corpus luteum and/or placenta and is involved in many essential physiological processes centered on its action as a potent extracellular matrix (ECM) remodeling agent. Insulin-like peptide 3 (INSL3), also known as relaxin-like factor, is predominantly expressed in the Leydig cells of the testes and is an important mediator of testicular descent. The relaxin-1 equivalent peptide in humans is actually the product of the human RLN2 gene, human 2 (H2) relaxin. Recently identified and thought to be the ancestral relaxin, relaxin-3 is specifically expressed in the nucleus incertus of the mouse and rat brain and is most likely an important neuropeptide. Each of the hormones above act on cell membrane G-protein coupled receptors (GPCRs). The relaxin-1 receptor is leucine-rich repeat-containing GPCR 7 (LGR7) whereas INSL3 acts on the closely related LGR8. These receptors have large extra-cellular domains containing multiple leucine-rich repeats (LRRs) and a unique LDL receptor-like cysteine-rich motif (LDLR-domain). Relaxin-3 will bind and activate LGR7 with 50-fold lower activity than H2 relaxin. Two relaxin-3 selective GPCRs; somatostatin and angiotensin like peptide receptor (SALPR) and GPCR 142 were recently identified, these type I GPCRs are unrelated to LGR7 and LGR8. The discovery and characterisation of these receptors is greatly aiding the quest to unravel the mechanics of these important hormones, however with three other family members, insulin-like peptides 4–6 (INSL4, INSL5 and INSL6) with unknown functions and unidentified receptors, there is still much to be learnt about this hormone family.     

Uncovering biases in high throughput screens of G-protein coupled receptors

The ability of high throughput membrane binding assays to detect ligands for G-protein coupled receptors was examined using mathematical models. Membrane assay models were developed using the extended ternary complex model (Samama et al., 1993) as a basis. Ligand binding to whole cells was modeled by adding a G-protein activation step. Results show that inverse agonists bind more slowly and with a lower affinity to receptors in the membrane binding assay than to receptors in whole cells, causing the membrane assay to miss pharmaceutically important inverse agonists. Assay modifications to allow detection of inverse agonists are discussed. Finally, kinetic binding data are shown to provide information about ligand efficacy. This work demonstrates the utility of mathematical modeling in detecting biases in drug-screening assay, and also in suggesting techniques to correct those biases.