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1.  The G Protein–Coupled Receptor Subset of the Chicken Genome 
PLoS Computational Biology  2006;2(6):e54.
G protein–coupled receptors (GPCRs) are one of the largest families of proteins, and here we scan the recently sequenced chicken genome for GPCRs. We use a homology-based approach, utilizing comparisons with all human GPCRs, to detect and verify chicken GPCRs from translated genomic alignments and Genscan predictions. We present 557 manually curated sequences for GPCRs from the chicken genome, of which 455 were previously not annotated. More than 60% of the chicken Genscan gene predictions with a human ortholog needed curation, which drastically changed the average percentage identity between the human–chicken orthologous pairs (from 56.3% to 72.9%). Of the non-olfactory chicken GPCRs, 79% had a one-to-one orthologous relationship to a human GPCR. The Frizzled, Secretin, and subgroups of the Rhodopsin families have high proportions of orthologous pairs, although the percentage of amino acid identity varies. Other groups show large differences, such as the Adhesion family and GPCRs that bind exogenous ligands. The chicken has only three bitter Taste 2 receptors, and it also lacks an ortholog to human TAS1R2 (one of three GPCRs in the human genome in the Taste 1 receptor family [TAS1R]), implying that the chicken's ability and mode of detecting both bitter and sweet taste may differ from the human's. The chicken genome contains at least 229 olfactory receptors, and the majority of these (218) originate from a chicken-specific expansion. To our knowledge, this dataset of chicken GPCRs is the largest curated dataset from a single gene family from a non-mammalian vertebrate. Both the updated human GPCR dataset, as well the chicken GPCR dataset, are available for download.
Synopsis
Man and chicken are very different, but how is that difference related to our respective gene repertoire? The authors studied the family of G protein–coupled receptors (GPCRs), which in man contains about 791 proteins. These are found in the cell membrane, where they recognize substances, thereby functioning as mediators of signals across the cellular membrane. GPCRs respond to physiologically important substances such as hormones and neurotransmitters. In this paper, the publicly available genomic sequence from the domestic chicken is used to identify the entire repertoire of GPCRs in this species. The authors found 557 GPCRs and compared the chicken and human receptors; they concluded that out of the 328 chicken receptors that are not involved in olfaction, more than 250 have a corresponding human receptor. The majority of the differences between the chicken and man are within three groups of GPCRs—the receptors for olfaction, bitter taste, and the receptors involved in the immune system. The chicken GPCR sequences obtained here will be useful for identification of GPCRs in other species that are more distantly related to man, such as fish or insects. The domestic chicken represents the leading experimental model among the avian species and also serves as an important source of food worldwide.
doi:10.1371/journal.pcbi.0020054
PMCID: PMC1472694  PMID: 16741557
2.  Harnessing the genome for characterization of GPCRs in cancer pathogenesis 
The FEBS journal  2013;280(19):4729-4738.
G-protein coupled receptors (GPCRs) mediate numerous physiological processes and represent the targets for a vast array of therapeutics for diseases ranging from depression to hypertension to reflux. Despite the recognition that GPCRs can act as oncogenes and tumor suppressors by regulating oncogenic signaling networks, few drugs targeting GPCRs are utilized in cancer therapy. Recent large-scale genome-wide analyses of multiple human tumors have uncovered novel GPCRs altered in cancer. However, the work of determining which GPCRs from these lists are drivers of tumorigenesis, and hence valid therapeutic targets, remains a formidable challenge. In this review I will highlight recent studies providing evidence that GPCRs are relevant targets for cancer therapy through their effects on known cancer signaling pathways, tumor progression, invasion and metastasis, and the microenvironment. Furthermore, I will explore how genomic analysis is beginning to shine a light on GPCRs as therapeutic targets in the age of personalized medicine.
doi:10.1111/febs.12473
PMCID: PMC4283816  PMID: 23927072
GPCR; cancer; bioinformatics; signal transduction; microenvironment; metastasis; genomics
3.  Large-scale polymorphism discovery in macaque G-protein coupled receptors 
BMC Genomics  2013;14:703.
Background
G-protein coupled receptors (GPCRs) play an inordinately large role in human health. Variation in the genes that encode these receptors is associated with numerous disorders across the entire spectrum of disease. GPCRs also represent the single largest class of drug targets and associated pharmacogenetic effects are modulated, in part, by polymorphisms. Recently, non-human primate models have been developed focusing on naturally-occurring, functionally-parallel polymorphisms in candidate genes. This work aims to extend those studies broadly across the roughly 377 non-olfactory GPCRs. Initial efforts include resequencing 44 Indian-origin rhesus macaques (Macaca mulatta), 20 Chinese-origin rhesus macaques, and 32 cynomolgus macaques (M. fascicularis).
Results
Using the Agilent target enrichment system, capture baits were designed for GPCRs off the human and rhesus exonic sequence. Using next generation sequencing technologies, nearly 25,000 SNPs were identified in coding sequences including over 14,000 non-synonymous and more than 9,500 synonymous protein-coding SNPs. As expected, regions showing the least evolutionary constraint show greater rates of polymorphism and greater numbers of higher frequency polymorphisms. While the vast majority of these SNPs are singletons, roughly 1,750 non-synonymous and 2,900 synonymous SNPs were found in multiple individuals.
Conclusions
In all three populations, polymorphism and divergence is highly concentrated in N-terminal and C-terminal domains and the third intracellular loop region of GPCRs, regions critical to ligand-binding and signaling. SNP frequencies in macaques follow a similar pattern of divergence from humans and new polymorphisms in primates have been identified that may parallel those seen in humans, helping to establish better non-human primate models of disease.
doi:10.1186/1471-2164-14-703
PMCID: PMC3907043  PMID: 24119066
Resequencing; Single-nucleotide polymorphism; Indian-origin rhesus macaques; Chinese-origin rhesus macaques; Cynomolgus macaques
4.  G protein-coupled receptors — recent advances 
Acta biochimica Polonica  2012;59(4):515-529.
The years 2000 and 2007 witnessed milestones in current understanding of G protein-coupled receptor (GPCR) structural biology. In 2000 the first GPCR, bovine rhodopsin, was crystallized and the structure was solved, while in 2007 the structure of β2-adrenergic receptor, the first GPCR with diffusible ligands, was determined owing to advances in microcrystallization and an insertion of the fast-folding lysozyme into the receptor. In parallel with those crystallographic studies, the biological and biochemical characterization of GPCRs has advanced considerably because those receptors are molecular targets for many of currently used drugs. Therefore, the mechanisms of activation and signal transduction to the cell interior deduced from known GPCRs structures are of the highest importance for drug discovery. These proteins are the most diversified membrane receptors encoded by hundreds of genes in our genome. They participate in processes responsible for vision, smell, taste and neuronal transmission in response to photons or binding of ions, hormones, peptides, chemokines and other factors. Although the GPCRs share a common seven-transmembrane α-helical bundle structure their binding sites can accommodate thousands of different ligands. The ligands, including agonists, antagonists or inverse agonists change the structure of the receptor. With bound agonists they can form a complex with a suitable G protein, be phosphorylated by kinases or bind arrestin. The discovered signaling cascades invoked by arrestin independently of G proteins makes the GPCR activating scheme more complex such that a ligand acting as an antagonist for G protein signaling can also act as an agonist in arrestin-dependent signaling. Additionally, the existence of multiple ligand-dependent partial activation states as well as dimerization of GPCRs result in a ‘microprocessor-like’ action of these receptors rather than an ‘on-off’ switch as was commonly believed only a decade ago.
PMCID: PMC4322417  PMID: 23251911
G protein-coupled receptors; rhodopsin; β-adrenergic receptors; chemokine receptors; G protein; arrestin
5.  A Genetic RNAi Screen for IP3/Ca2+ Coupled GPCRs in Drosophila Identifies the PdfR as a Regulator of Insect Flight 
PLoS Genetics  2013;9(10):e1003849.
Insect flight is regulated by various sensory inputs and neuromodulatory circuits which function in synchrony to control and fine-tune the final behavioral outcome. The cellular and molecular bases of flight neuromodulatory circuits are not well defined. In Drosophila melanogaster, it is known that neuronal IP3 receptor mediated Ca2+ signaling and store-operated Ca2+ entry (SOCE) are required for air-puff stimulated adult flight. However, G-protein coupled receptors (GPCRs) that activate intracellular Ca2+ signaling in the context of flight are unknown in Drosophila. We performed a genetic RNAi screen to identify GPCRs that regulate flight by activating the IP3 receptor. Among the 108 GPCRs screened, we discovered 5 IP3/Ca2+ linked GPCRs that are necessary for maintenance of air-puff stimulated flight. Analysis of their temporal requirement established that while some GPCRs are required only during flight circuit development, others are required both in pupal development as well as during adult flight. Interestingly, our study identified the Pigment Dispersing Factor Receptor (PdfR) as a regulator of flight circuit development and as a modulator of acute flight. From the analysis of PdfR expressing neurons relevant for flight and its well-defined roles in other behavioral paradigms, we propose that PdfR signaling functions systemically to integrate multiple sensory inputs and modulate downstream motor behavior.
Author Summary
A majority of behavioral patterns in flying insects depend upon their ability to modulate flight. In Drosophila melanogaster, mutations in the IP3 receptor gene lead to loss of voluntary flight in response to a natural stimulus like a gentle air-puff. From previous genetic and cellular studies it is known that the IP3R in Drosophila is activated by G-protein coupled receptors (GPCRs). However, GPCRs that act upstream of the IP3R in the context of flight are not known. Therefore, we performed a genetic RNAi screen to identify GPCRs which regulate flight. This screen was followed by a secondary suppressor screen that assessed the role of each identified GPCR in activating IP3/Ca2+ signaling. We found 5 such GPCRs. Our results demonstrate that these GPCRs are required during flight circuit development and during adult flight. One flight-regulating receptor identified was the Pigment Dispersing Factor Receptor (PdfR). This receptor is known to regulate behaviors such as circadian rhythms, geotaxis and reproduction. A spatio-temporal analysis of PdfR flight function indicates that it regulates both flight circuit development and acute flight through multiple neurons. We postulate that PdfR signaling could modulate and integrate multiple behavioral inputs in Drosophila and other flying insects.
doi:10.1371/journal.pgen.1003849
PMCID: PMC3789835  PMID: 24098151
6.  Sulfotyrosines of the Kaposi's Sarcoma-Associated Herpesvirus G Protein-Coupled Receptor Promote Tumorigenesis through Autocrine Activation▿  
Journal of Virology  2010;84(7):3351-3361.
The Kaposi's sarcoma-associated herpesvirus (KSHV) G protein-coupled receptor (vGPCR) is a bona fide signaling molecule that is implicated in KSHV-associated malignancies. Whereas vGPCR activates specific cellular signaling pathways in a chemokine-independent fashion, vGPCR binds a broad spectrum of CC and CXC chemokines, and the roles of chemokines in vGPCR tumorigenesis remain poorly understood. We report here that vGPCR is posttranslationally modified by sulfate groups at tyrosine residues within its N-terminal extracellular domain. A chemokine-binding assay demonstrated that the tyrosine sulfate moieties were critical for vGPCR association with GRO-α (an agonist) but not with IP-10 (an inverse agonist). A sulfated peptide corresponding to residues 12 through 33 of vGPCR, but not the unsulfated equivalent, partially inhibited vGPCR association with GRO-α. Although the vGPCR variant lacking sulfotyrosines activated downstream signaling pathways, the ability of the unsulfated vGPCR variant to induce tumor growth in nude mice was significantly diminished. Furthermore, the unsulfated vGPCR variant was unable to induce the secretion of proliferative cytokines, some of which serve as vGPCR agonists. This implies that autocrine activation by agonist chemokines is critical for vGPCR tumorigenesis. Indeed, GRO-α increased vGPCR-mediated AKT phosphorylation and vGPCR tumorigenesis in a sulfotyrosine-dependent manner. Our findings support the conclusion that autocrine activation triggered by chemokine agonists via sulfotyrosines is necessary for vGPCR tumorigenesis, thereby providing a rationale for future therapeutic design targeting the tumorigenic vGPCR.
doi:10.1128/JVI.01939-09
PMCID: PMC2838108  PMID: 20106924
7.  Impact of GPCRs in clinical medicine: genetic variants and drug targets 
Biochimica et biophysica acta  2006;1768(4):994-1005.
Summary
By virtue of their large number, widespread distribution and important roles in cell physiology and biochemistry, G-protein-coupled receptors (GPCR) play multiple important roles in clinical medicine. Here, we focus on 3 areas that subsume much of the recent work in this aspect of GPCR biology: 1) Monogenic diseases of GPCR; 2) Genetic variants of GPCR; and 3) Clinically useful pharmacological agonists and antagonists of GPCR. Diseases involving mutations of GPCR are rare, occurring in <1/1000 people, but disorders in which antibodies are directed against GPCR are more common. Genetic variants, especially single nucleotide polymorphisms (SNP), show substantial heterogeneity in frequency among different GPCRs but have not been evaluated for some GPCR. Many therapeutic agonists and antagonists target GPCR and show inter-subject variability in terms of efficacy and toxicity. For most of those agents, it remains an open question whether genetic variation in primary sequence of the GPCR is an important contributor to such inter-subject variability, although this is an active area of investigation.
doi:10.1016/j.bbamem.2006.09.029
PMCID: PMC2169201  PMID: 17081496
GPCR mutations; human disease; nephrogenic diabetes insipidus; retinitis pigmentosa
8.  G Protein βγ Subunits as Targets for Small Molecule Therapeutic Development 
G proteins mediate the action of G protein coupled receptors (GPCRs), a major target of current pharmaceuticals and a major target of interest in future drug development. Most pharmaceutical interest has been in the development of selective GPCR agonists and antagonists that activate or inhibit specific GPCRs. Some recent thinking has focused on the idea that some pathologies are the result of the actions of an array of GPCRs suggesting that targeting single receptors may have limited efficacy. Thus, targeting pathways common to multiple GPCRs that control critical pathways involved in disease has potential therapeutic relevance. G protein βγ subunits released from some GPCRs upon receptor activation regulate a variety of downstream pathways to control various aspects of mammalian physiology. There is evidence from cell-based and animal models that excess Gβγ signaling can be detrimental and blocking Gβγ signaling has salutary effects in a number of pathological models. Gβγ regulates downstream pathways through modulation of enzymes that produce cellular second messengers or through regulation of ion channels by direct protein-protein interactions. Thus, blocking Gβγ functions requires development of small molecule agents that disrupt Gβγ protein interactions with downstream partners. Here we discuss evidence that small molecule targeting Gβγ could be of therapeutic value. The concept of disruption of protein-protein interactions by targeting a “hot spot” on Gβγ is delineated and the biochemical and virtual screening strategies for identification of small molecules that selectively target Gβγ functions are outlined. Evaluation of the effectiveness of virtual screening indicates that computational screening enhanced identification of true Gβγ binding molecules. However, further refinement of the approach could significantly improve the yield of Gβγ binding molecules from this screen that could result in multiple candidate leads for future drug development.
PMCID: PMC2688719  PMID: 18537559
G protein βγ subunits; GRK2ct; computational screening; G protein-coupled receptor; small molecule targeting; protein-protein interactions; G protein signaling
9.  Identification of G protein-coupled receptor signaling pathway proteins in marine diatoms using comparative genomics 
BMC Genomics  2013;14:503.
Background
The G protein-coupled receptor (GPCR) signaling pathway plays an essential role in signal transmission and response to external stimuli in mammalian cells. Protein components of this pathway have been characterized in plants and simpler eukaryotes such as yeast, but their presence and role in unicellular photosynthetic eukaryotes have not been determined. We use a comparative genomics approach using whole genome sequences and gene expression libraries of four diatoms (Pseudo-nitzschia multiseries, Thalassiosira pseudonana, Phaeodactylum tricornutum and Fragilariopsis cylindrus) to search for evidence of GPCR signaling pathway proteins that share sequence conservation to known GPCR pathway proteins.
Results
The majority of the core components of GPCR signaling were well conserved in all four diatoms, with protein sequence similarity to GPCRs, human G protein α- and β-subunits and downstream effectors. There was evidence for the Gγ-subunit and thus a full heterotrimeric G protein only in T. pseudonana. Phylogenetic analysis of putative diatom GPCRs indicated similarity but deep divergence to the class C GPCRs, with branches basal to the GABAB receptor subfamily. The extracellular and intracellular regions of these putative diatom GPCR sequences exhibited large variation in sequence length, and seven of these sequences contained the necessary ligand binding domain for class C GPCR activation. Transcriptional data indicated that a number of the putative GPCR sequences are expressed in diatoms under various stress conditions in culture, and that many of the GPCR-activated signaling proteins, including the G protein, are also expressed.
Conclusions
The presence of sequences in all four diatoms that code for the proteins required for a functional mammalian GPCR pathway highlights the highly conserved nature of this pathway and suggests a complex signaling machinery related to environmental perception and response in these unicellular organisms. The lack of evidence for some GPCR pathway proteins in one or more of the diatoms, such as the Gγ-subunit, may be due to differences in genome completeness and genome coverage for the four diatoms. The high divergence of putative diatom GPCR sequences to known class C GPCRs suggests these sequences may represent another, potentially ancestral, subfamily of class C GPCRs.
doi:10.1186/1471-2164-14-503
PMCID: PMC3727952  PMID: 23883327
Cell signaling; Diatom; Environment; G protein-coupled receptor; Human health; Ocean
10.  Cardiovascular Pharmacogenomics of Adrenergic Receptor Signaling: Clinical Implications and Future Directions 
G-protein-coupled receptors (GPCRs) are the targets for many drugs, and genetic variation in coding and noncoding regions is apparent in many such receptors. In this superfamily, adrenergic receptors (ARs) were among the first in which single-nucleotide polymorphisms (SNPs) were discovered, and studies including in vitro mutagenesis, genetically modified mouse models, human ex vivo and in vitro studies and pharmacogenetic association studies were conducted. The signal transduction in these receptors includes amplification steps, desensitization, crosstalk, and redundancies, enabling potential mitigation of the size of the clinical effect for a single variant in a single gene. Nevertheless, convincing evidence has emerged that several variants have an impact on therapy, with certain caveats as to how the results are to be interpreted. Here we review these results for selected ARs and associated regulatory kinases relative to the pharmacogenomics of β-blocker treatment for hypertension and heart failure. We emphasize the linking of clinical results to molecular mechanisms, discuss study design limitations, and offer some recommendations for future directions.
doi:10.1038/clpt.2010.315
PMCID: PMC3110683  PMID: 21289619
11.  Structure Modeling of All Identified G Protein–Coupled Receptors in the Human Genome 
PLoS Computational Biology  2006;2(2):e13.
G protein–coupled receptors (GPCRs), encoded by about 5% of human genes, comprise the largest family of integral membrane proteins and act as cell surface receptors responsible for the transduction of endogenous signal into a cellular response. Although tertiary structural information is crucial for function annotation and drug design, there are few experimentally determined GPCR structures. To address this issue, we employ the recently developed threading assembly refinement (TASSER) method to generate structure predictions for all 907 putative GPCRs in the human genome. Unlike traditional homology modeling approaches, TASSER modeling does not require solved homologous template structures; moreover, it often refines the structures closer to native. These features are essential for the comprehensive modeling of all human GPCRs when close homologous templates are absent. Based on a benchmarked confidence score, approximately 820 predicted models should have the correct folds. The majority of GPCR models share the characteristic seven-transmembrane helix topology, but 45 ORFs are predicted to have different structures. This is due to GPCR fragments that are predominantly from extracellular or intracellular domains as well as database annotation errors. Our preliminary validation includes the automated modeling of bovine rhodopsin, the only solved GPCR in the Protein Data Bank. With homologous templates excluded, the final model built by TASSER has a global Cα root-mean-squared deviation from native of 4.6 Å, with a root-mean-squared deviation in the transmembrane helix region of 2.1 Å. Models of several representative GPCRs are compared with mutagenesis and affinity labeling data, and consistent agreement is demonstrated. Structure clustering of the predicted models shows that GPCRs with similar structures tend to belong to a similar functional class even when their sequences are diverse. These results demonstrate the usefulness and robustness of the in silico models for GPCR functional analysis. All predicted GPCR models are freely available for noncommercial users on our Web site (http://www.bioinformatics.buffalo.edu/GPCR).
Synopsis
G protein–coupled receptors (GPCRs) are a large superfamily of integral membrane proteins that transduce signals across the cell membrane. Because of the breadth and importance of the physiological roles undertaken by the GPCR family, many of its members are important pharmacological targets. Although the knowledge of a protein's native structure can provide important insight into understanding its function and for the design of new drugs, the experimental determination of the three-dimensional structure of GPCR membrane proteins has proved to be very difficult. This is demonstrated by the fact that there is only one solved GPCR structure (from bovine rhodopsin) deposited in the Protein Data Bank library. In contrast, there are no human GPCR structures in the Protein Data Bank. To address the need for the tertiary structures of human GPCRs, using just sequence information, the authors use a newly developed threading-assembly-refinement method to generate models for all 907 registered GPCRs in the human genome. About 820 GPCRs are anticipated to have correct topology and transmembrane helix arrangement. A subset of the resulting models is validated by comparison with mutagenesis experimental data, and consistent agreement is demonstrated.
doi:10.1371/journal.pcbi.0020013
PMCID: PMC1364505  PMID: 16485037
12.  The Origins of Diversity and Specificity in G Protein-Coupled Receptor Signaling 
The modulation of transmembrane signaling by G protein-coupled receptors (GPCRs) constitutes the single most important therapeutic target in medicine. Drugs acting on GPCRs have traditionally been classified as agonists, partial agonists, or antagonists based on a two-state model of receptor function embodied in the ternary complex model. Over the past decade, however, many lines of investigation have shown that GPCR signaling exhibits greater diversity and “texture” than previously appreciated. Signal diversity arises from numerous factors, among which are the ability of receptors to adopt multiple “active” states with different effector-coupling profiles; the formation of receptor dimers that exhibit unique pharmacology, signaling, and trafficking; the dissociation of receptor “activation” from desensitization and internalization; and the discovery that non-G protein effectors mediate some aspects of GPCR signaling. At the same time, clustering of GPCRs with their downstream effectors in membrane microdomains and interactions between receptors and a plethora of multidomain scaffolding proteins and accessory/chaperone molecules confer signal preorganization, efficiency, and specificity. In this context, the concept of agonist-selective trafficking of receptor signaling, which recognizes that a bound ligand may select between a menu of active receptor conformations and induce only a subset of the possible response profile, presents the opportunity to develop drugs that change the quality as well as the quantity of efficacy. As a more comprehensive understanding of the complexity of GPCR signaling is developed, the rational design of ligands possessing increased specific efficacy and attenuated side effects may become the standard mode of drug development.
doi:10.1124/jpet.105.083121
PMCID: PMC2656918  PMID: 15805429
13.  Ubiquitin-dependent regulation of G protein-coupled receptor trafficking and signaling 
Cellular signalling  2012;25(3):707-716.
G protein-coupled receptors (GPCRs) belong to one of the largest family of signaling receptors in the mammalian genome [1]. GPCRs elicit cellular responses to multiple diverse stimuli and play essential roles in human health and disease. GPCRs have important clinical implications in various diseases and are the targets of approximately 25–50% of all marketed drugs [2, 3]. Understanding how GPCRs are regulated is essential to delineating their role in normal physiology and in the pathophysiology of several diseases. Given the vast number and diversity of GPCRs, it is likely that multiple mechanisms exist to regulate GPCR function. While GPCR signaling is typically regulated by desensitization and endocytosis mediated by phosphorylation and β-arrestins, it can also be modulated by ubiquitination. Ubiquitination is emerging an important regulatory process that may have unique roles in governing GPCR trafficking and signaling. Recent studies have revealed a mechanistic link between GPCR phosphorylation, β-arrestins and ubiquitination that may be applicable to some GPCRs but not others. While the function of ubiquitination is generally thought to promote receptor endocytosis and endosomal sorting, recent studies have revealed that ubiquitination also plays an important role in positive regulation of GPCR signaling. Here, we will review recent developments in our understanding of how ubiquitin regulates GPCR endocytic trafficking and how it contributes to signal transduction induced by GPCR activation.
doi:10.1016/j.cellsig.2012.11.024
PMCID: PMC3593103  PMID: 23201781
G protein-coupled receptor; beta-arrestin; endocytosis; ubiquitination; ligase; sorting; lysosome; downregulation
14.  Human 5–HT4 and 5–HT7 Receptor Splice Variants: Are they Important? 
Current Neuropharmacology  2007;5(4):224-231.
G-protein-coupled receptors (GPCRs), which are encoded by >300 genes in the human genome, are by far the largest class of targets for modern drugs. These macromolecules display inherent adaptability of function, which is partly due to the production of different forms of the receptor protein. These are commonly called ‘isoforms’ or ‘splice variants’ denoting the molecular process of their production/assembly. Not all GPCRs are expressed as splice variants, but certain subclasses of 5–HT receptors are for example, the 5–HT4 and 5–HT7 receptors. There are at least 11 human 5–HT4 and three h5–HT7 receptor splice variants. This review describestheir discoveries, nomenclature and structures. The discovery that particular splice variants are tissue specific (or prominent) has highlighted their potential as future drug targets. In particular, this review examines the functional relevance of different 5–HT4 and 5–HT7 receptor splice variants. Examples are given to illustrate that splice variants have differential modulatory influences on signalling processes. Differences in agonist potency and efficacies and also differences in desensitisation rates to 5–HT occur with both 5–HT4 and 5–HT7 receptor splice variants. The known and candidate signalling systems that allow for splice variant specific responses include GPCR interacting proteins (GIPs) and GPCR receptor kinases (GRKs) which are examined.Finally, the relevance of 5–HT receptor splice variants to clinical medicine and to the pharmaceutical industry is discussed.
doi:10.2174/157015907782793621
PMCID: PMC2644495  PMID: 19305739
Serotonin receptors; GPCR receptor isoforms; GPCR receptor splice variants; GPCR interacting proteins; desensitisation; functional intestinal disorders; irritable bowel syndrome.
15.  Increasingly accurate dynamic molecular models of G-protein coupled receptor oligomers: Panacea or Pandora's box for novel drug discovery? 
Life sciences  2009;86(15-16):590-597.
For years conventional drug design at G-protein coupled receptors (GPCRs) has mainly focused on the inhibition of a single receptor at a usually well-defined ligand-binding site. The recent discovery of more and more physiologically relevant GPCR dimers/oligomers suggests that selectively targeting these complexes or designing small molecules that inhibit receptor-receptor interactions might provide new opportunities for novel drug discovery. To uncover the fundamental mechanisms and dynamics governing GPCR dimerization/oligomerization, it is crucial to understand the dynamic process of receptor-receptor association, and to identify regions that are suitable for selective drug binding. This minireview highlights current progress in the development of increasingly accurate dynamic molecular models of GPCR oligomers based on structural, biochemical, and biophysical information that has recently appeared in the literature. In view of this new information, there has never been a more exciting time for computational research into GPCRs than at present. Information-driven modern molecular models of GPCR complexes are expected to efficiently guide the rational design of GPCR oligomer-specific drugs, possibly allowing researchers to reach for the high-hanging fruits in GPCR drug discovery, i.e. more potent and selective drugs for efficient therapeutic interventions.
doi:10.1016/j.lfs.2009.05.004
PMCID: PMC2848910  PMID: 19465029
GPCRs; dimers; computational methods; molecular modeling; rational drug design
16.  Analysis of multiple compound–protein interactions reveals novel bioactive molecules 
The authors use machine learning of compound-protein interactions to explore drug polypharmacology and to efficiently identify bioactive ligands, including novel scaffold-hopping compounds for two pharmaceutically important protein families: G-protein coupled receptors and protein kinases.
We have demonstrated that machine learning of multiple compound–protein interactions is useful for efficient ligand screening and for assessing drug polypharmacology.This approach successfully identified novel scaffold-hopping compounds for two pharmaceutically important protein families: G-protein-coupled receptors and protein kinases.These bioactive compounds were not detected by existing computational ligand-screening methods in comparative studies.The results of this study indicate that data derived from chemical genomics can be highly useful for exploring chemical space, and this systems biology perspective could accelerate drug discovery processes.
The discovery of novel bioactive molecules advances our systems-level understanding of biological processes and is crucial for innovation in drug development. Perturbations of biological systems by chemical probes provide broader applications not only for analysis of complex systems but also for intentional manipulations of these systems. Nevertheless, the lack of well-characterized chemical modulators has limited their use. Recently, chemical genomics has emerged as a promising area of research applicable to the exploration of novel bioactive molecules, and researchers are currently striving toward the identification of all possible ligands for all target protein families (Wang et al, 2009). Chemical genomics studies have shown that patterns of compound–protein interactions (CPIs) are too diverse to be understood as simple one-to-one events. There is an urgent need to develop appropriate data mining methods for characterizing and visualizing the full complexity of interactions between chemical space and biological systems. However, no existing screening approach has so far succeeded in identifying novel bioactive compounds using multiple interactions among compounds and target proteins.
High-throughput screening (HTS) and computational screening have greatly aided in the identification of early lead compounds for drug discovery. However, the large number of assays required for HTS to identify drugs that target multiple proteins render this process very costly and time-consuming. Therefore, interest in using in silico strategies for screening has increased. The most common computational approaches, ligand-based virtual screening (LBVS) and structure-based virtual screening (SBVS; Oprea and Matter, 2004; Muegge and Oloff, 2006; McInnes, 2007; Figure 1A), have been used for practical drug development. LBVS aims to identify molecules that are very similar to known active molecules and generally has difficulty identifying compounds with novel structural scaffolds that differ from reference molecules. The other popular strategy, SBVS, is constrained by the number of three-dimensional crystallographic structures available. To circumvent these limitations, we have shown that a new computational screening strategy, chemical genomics-based virtual screening (CGBVS), has the potential to identify novel, scaffold-hopping compounds and assess their polypharmacology by using a machine-learning method to recognize conserved molecular patterns in comprehensive CPI data sets.
The CGBVS strategy used in this study was made up of five steps: CPI data collection, descriptor calculation, representation of interaction vectors, predictive model construction using training data sets, and predictions from test data (Figure 1A). Importantly, step 1, the construction of a data set of chemical structures and protein sequences for known CPIs, did not require the three-dimensional protein structures needed for SBVS. In step 2, compound structures and protein sequences were converted into numerical descriptors. These descriptors were used to construct chemical or biological spaces in which decreasing distance between vectors corresponded to increasing similarity of compound structures or protein sequences. In step 3, we represented multiple CPI patterns by concatenating these chemical and protein descriptors. Using these interaction vectors, we could quantify the similarity of molecular interactions for compound–protein pairs, despite the fact that the ligand and protein similarity maps differed substantially. In step 4, concatenated vectors for CPI pairs (positive samples) and non-interacting pairs (negative samples) were input into an established machine-learning method. In the final step, the classifier constructed using training sets was applied to test data.
To evaluate the predictive value of CGBVS, we first compared its performance with that of LBVS by fivefold cross-validation. CGBVS performed with considerably higher accuracy (91.9%) than did LBVS (84.4%; Figure 1B). We next compared CGBVS and SBVS in a retrospective virtual screening based on the human β2-adrenergic receptor (ADRB2). Figure 1C shows that CGBVS provided higher hit rates than did SBVS. These results suggest that CGBVS is more successful than conventional approaches for prediction of CPIs.
We then evaluated the ability of the CGBVS method to predict the polypharmacology of ADRB2 by attempting to identify novel ADRB2 ligands from a group of G-protein-coupled receptor (GPCR) ligands. We ranked the prediction scores for the interactions of 826 reported GPCR ligands with ADRB2 and then analyzed the 50 highest-ranked compounds in greater detail. Of 21 commercially available compounds, 11 showed ADRB2-binding activity and were not previously reported to be ADRB2 ligands. These compounds included ligands not only for aminergic receptors but also for neuropeptide Y-type 1 receptors (NPY1R), which have low protein homology to ADRB2. Most ligands we identified were not detected by LBVS and SBVS, which suggests that only CGBVS could identify this unexpected cross-reaction for a ligand developed as a target to a peptidergic receptor.
The true value of CGBVS in drug discovery must be tested by assessing whether this method can identify scaffold-hopping lead compounds from a set of compounds that is structurally more diverse. To assess this ability, we analyzed 11 500 commercially available compounds to predict compounds likely to bind to two GPCRs and two protein kinases. Functional assays revealed that nine ADRB2 ligands, three NPY1R ligands, five epidermal growth factor receptor (EGFR) inhibitors, and two cyclin-dependent kinase 2 (CDK2) inhibitors were concentrated in the top-ranked compounds (hit rate=30, 15, 25, and 10%, respectively). We also evaluated the extent of scaffold hopping achieved in the identification of these novel ligands. One ADRB2 ligand, two NPY1R ligands, and one CDK2 inhibitor exhibited scaffold hopping (Figure 4), indicating that CGBVS can use this characteristic to rationally predict novel lead compounds, a crucial and very difficult step in drug discovery. This feature of CGBVS is critically different from existing predictive methods, such as LBVS, which depend on similarities between test and reference ligands, and focus on a single protein or highly homologous proteins. In particular, CGBVS is useful for targets with undefined ligands because this method can use CPIs with target proteins that exhibit lower levels of homology.
In summary, we have demonstrated that data mining of multiple CPIs is of great practical value for exploration of chemical space. As a predictive model, CGBVS could provide an important step in the discovery of such multi-target drugs by identifying the group of proteins targeted by a particular ligand, leading to innovation in pharmaceutical research.
The discovery of novel bioactive molecules advances our systems-level understanding of biological processes and is crucial for innovation in drug development. For this purpose, the emerging field of chemical genomics is currently focused on accumulating large assay data sets describing compound–protein interactions (CPIs). Although new target proteins for known drugs have recently been identified through mining of CPI databases, using these resources to identify novel ligands remains unexplored. Herein, we demonstrate that machine learning of multiple CPIs can not only assess drug polypharmacology but can also efficiently identify novel bioactive scaffold-hopping compounds. Through a machine-learning technique that uses multiple CPIs, we have successfully identified novel lead compounds for two pharmaceutically important protein families, G-protein-coupled receptors and protein kinases. These novel compounds were not identified by existing computational ligand-screening methods in comparative studies. The results of this study indicate that data derived from chemical genomics can be highly useful for exploring chemical space, and this systems biology perspective could accelerate drug discovery processes.
doi:10.1038/msb.2011.5
PMCID: PMC3094066  PMID: 21364574
chemical genomics; data mining; drug discovery; ligand screening; systems chemical biology
17.  Large-scale RNAi screen of G protein-coupled receptors involved in larval growth, molting and metamorphosis in the red flour beetle 
BMC Genomics  2011;12:388.
Background
The G protein-coupled receptors (GPCRs) belong to the largest superfamily of integral cell membrane proteins and play crucial roles in physiological processes including behavior, development and reproduction. Because of their broad and diverse roles in cellular signaling, GPCRs are the therapeutic targets for many prescription drugs. However, there is no commercial pesticide targeting insect GPCRs. In this study, we employed functional genomics methods and used the red flour beetle, Tribolium castaneum, as a model system to study the physiological roles of GPCRs during the larval growth, molting and metamorphosis.
Results
A total of 111 non-sensory GPCRs were identified in the T. castaneum genome. Thirty-nine of them were not reported previously. Large-scale RNA interference (RNAi) screen was used to study the function of all these GPCRs during immature stages. Double-stranded RNA (dsRNA)-mediated knockdown in the expression of genes coding for eight GPCRs caused severe developmental arrest and ecdysis failure (with more than 90% mortality after dsRNA injection). These GPCRs include dopamine-2 like receptor (TC007490/D2R) and latrophilin receptor (TC001872/Cirl). The majority of larvae injected with TC007490/D2R dsRNA died during larval stage prior to entering pupal stage, suggesting that this GPCR is essential for larval growth and development.
Conclusions
The results from our study revealed the physiological roles of some GPCRs in T. castaneum. These findings could help in development of novel pesticides targeting these GPCRs.
doi:10.1186/1471-2164-12-388
PMCID: PMC3163568  PMID: 21806814
18.  G protein-coupled receptor kinases: more than just kinases and not only for GPCRs 
Pharmacology & therapeutics  2011;133(1):40-69.
G protein-coupled receptor (GPCR) kinases (GRKs) are best known for their role in homologous desensitization of GPCRs. GRKs phosphorylate activated receptors and promote high affinity binding of arrestins, which precludes G protein coupling. GRKs have a multidomain structure, with the kinase domain inserted into a loop of a regulator of G protein signaling homology domain. Unlike many other kinases, GRKs do not need to be phosphorylated in their activation loop to achieve an activated state. Instead, they are directly activated by docking with active GPCRs. In this manner they are able to selectively phosphorylate Ser/Thr residues on only the activated form of the receptor, unlike related kinases such as protein kinase A. GRKs also phosphorylate a variety of non-GPCR substrates and regulate several signaling pathways via direct interactions with other proteins in a phosphorylation-independent manner. Multiple GRK subtypes are present in virtually every animal cell, with the highest expression levels found in neurons, with their extensive and complex signal regulation. Insufficient or excessive GRK activity was implicated in a variety of human disorders, ranging from heart failure to depression to Parkinson’s disease. As key regulators of GPCR-dependent and -independent signaling pathways, GRKs are emerging drug targets and promising molecular tools for therapy. Targeted modulation of expression and/or of activity of several GRK isoforms for therapeutic purposes was recently validated in cardiac disorders and Parkinson’s disease.
doi:10.1016/j.pharmthera.2011.08.001
PMCID: PMC3241883  PMID: 21903131
G protein-coupled receptors; G protein-coupled receptor kinases; signaling; regulation; phosphorylation; G proteins; regulator of G protein signaling
19.  Receptor Oligomerization in Family B1 of G-Protein-Coupled Receptors: Focus on BRET Investigations and the Link between GPCR Oligomerization and Binding Cooperativity 
The superfamily of the seven transmembrane G-protein-coupled receptors (7TM/GPCRs) is the largest family of membrane-associated receptors. GPCRs are involved in the pathophysiology of numerous human diseases, and they constitute an estimated 30–40% of all drug targets. During the last two decades, GPCR oligomerization has been extensively studied using methods like bioluminescence resonance energy transfer (BRET) and today, receptor–receptor interactions within the GPCR superfamily is a well-established phenomenon. Evidence of the impact of GPCR oligomerization on, e.g., ligand binding, receptor expression, and signal transduction indicates the physiological and pharmacological importance of these receptor interactions. In contrast to the larger and more thoroughly studied GPCR subfamilies A and C, the B1 subfamily is small and comprises only 15 members, including, e.g., the secretin receptor, the glucagon receptor, and the receptors for parathyroid hormone (PTHR1 and PTHR2). The dysregulation of several family B1 receptors is involved in diseases, such as diabetes, chronic inflammation, and osteoporosis which underlines the pathophysiological importance of this GPCR subfamily. In spite of this, investigation of family B1 receptor oligomerization and especially its pharmacological importance is still at an early stage. Even though GPCR oligomerization is a well-established phenomenon, there is a need for more investigations providing a direct link between these interactions and receptor functionality in family B1 GPCRs. One example of the functional effects of GPCR oligomerization is the facilitation of allosterism including cooperativity in ligand binding to GPCRs. Here, we review the currently available data on family B1 GPCR homo- and heteromerization, mainly based on BRET investigations. Furthermore, we cover the functional influence of oligomerization on ligand binding as well as the link between oligomerization and binding cooperativity.
doi:10.3389/fendo.2012.00062
PMCID: PMC3355942  PMID: 22649424
GPCRs; family B1; oligomerization; BRET; binding cooperativity
20.  G-protein coupled receptor expression patterns delineate medulloblastoma subgroups 
Background
Medulloblastoma is the most common malignant brain tumor in children. Genetic profiling has identified four principle tumor subgroups; each subgroup is characterized by different initiating mutations, genetic and clinical profiles, and prognoses. The two most well-defined subgroups are caused by overactive signaling in the WNT and SHH mitogenic pathways; less is understood about Groups 3 and 4 medulloblastoma. Identification of tumor subgroup using molecular classification is set to become an important component of medulloblastoma diagnosis and staging, and will likely guide therapeutic options. However, thus far, few druggable targets have emerged. G-protein coupled receptors (GPCRs) possess characteristics that make them ideal targets for molecular imaging and therapeutics; drugs targeting GPCRs account for 30-40% of all current pharmaceuticals. While expression patterns of many proteins in human medulloblastoma subgroups have been discerned, the expression pattern of GPCRs in medulloblastoma has not been investigated. We hypothesized that analysis of GPCR expression would identify clear subsets of medulloblastoma and suggest distinct GPCRs that might serve as molecular targets for both imaging and therapy.
Results
Our study found that medulloblastoma tumors fall into distinct clusters based solely on GPCR expression patterns. Normal cerebellum clustered separately from the tumor samples. Further, two of the tumor clusters correspond with high fidelity to the WNT and SHH subgroups of medulloblastoma. Distinct over-expressed GPCRs emerge; for example, LGR5 and GPR64 are significantly and uniquely over-expressed in the WNT subgroup of tumors, while PTGER4 is over-expressed in the SHH subgroup. Uniquely under-expressed GPCRs were also observed. Our key findings were independently validated using a large international dataset.
Conclusions
Our results identify GPCRs with potential to act as imaging and therapeutic targets. Elucidating tumorigenic pathways is a secondary benefit to identifying differential GPCR expression patterns in medulloblastoma tumors.
doi:10.1186/2051-5960-1-66
PMCID: PMC3893540  PMID: 24252460
Medulloblastoma subgroups; G-protein coupled receptors; Therapeutic targets; Imaging targets
21.  Boolean modeling of transcriptome data reveals novel modes of heterotrimeric G-protein action 
Classical mechanisms of heterotrimeric G-protein signaling are observed to function in regulation of the transcriptome. Conversely, many theoretical regulatory modes of the G-protein are not manifested in the transcriptomes we investigate.A new mechanism of G-protein signaling is revealed, in which the β subunit regulates gene expression identically in the presence or absence of the α subunit.We find evidence of cross-talk between G-protein-mediated and hormone-mediated transcriptional regulation.We find evidence of system specificity in G-protein signaling.
Heterotrimeric G-proteins, composed of α, β, and γ subunits, participate in a wide range of signaling pathways in eukaryotes (Morris and Malbon, 1999). According to the typical, mammalian paradigm, in its inactive state, the G-protein exists as an associated heterotrimer. G-protein signaling begins with ligand binding that results in a conformational change in a G-protein-coupled receptor (GPCR). Once activated by the GPCR, the Gα separates from the associated Gβγ dimer and the freed Gα and Gβγ proteins can then interact with downstream effector molecules, alone or in combination, to transduce the signal. Subsequent to signal propagation, Gα re-associates with the Gβγ dimer to reform the G-protein complex.
There are several classical routes for signal propagation through heterotrimeric G-proteins that have been categorized in mammalian systems (Marrari et al, 2007; Dupre et al, 2009). One route, which we designate classical I, requires the presence of both subunits, and can invoke one of two distinct mechanisms. In one mechanism, on GPCR activation, freed Gα and Gβγ each interact with downstream effectors to elicit the downstream response. In a related mechanism, Gα but not Gβγ interacts with downstream effectors, but the Gβγ dimer is nevertheless required to facilitate coupling of Gα with the relevant GPCR (Marrari et al, 2007). In a second route, which we designate classical II, it is solely the Gβγ dimer that interacts with downstream effectors; in this case, sequestration of Gβγ within the heterotrimer prevents signal propagation. In addition, a few non-classical G-protein regulatory modes have also been implicated in some systems, for example signaling by the intact heterotrimer in yeast (Klein et al, 2000; Frank et al, 2005). Observations such as these lead to a fundamental question, namely, which of all the theoretical regulatory modes of G-protein signaling are realized biologically. Our study answers this question in the context of the model plant Arabidopsis thaliana, and in addition analyzes the manner in which G-protein signaling couples with signaling by the plant hormone abscisic acid. The Arabidopsis genome encodes only one canonical Gα subunit, GPA1, and one canonical Gβ subunit, AGB1, and knockout mutants are available for each of these, allowing clear dissection of Gα- and Gβ-related phenotypes.
Abscisic acid (ABA) is a major plant hormone, which inhibits growth and promotes tolerance of abiotic stresses such as drought, salinity, and cold. ABA signaling is known to interact with heterotrimeric G-protein signaling in both developmental and stress responses in a complex manner, causing, for example, ABA hyposensitivity of guard cell stomatal opening in gpa1 and agb1 single mutants as well as agb1 gpa1 double mutants (Fan et al, 2008), but ABA hypersensitivity of the inhibition of seed germination and post-germination seedling development in the same mutants (Pandey et al, 2006). These experimental observations implicate G-proteins as one of the components of ABA signaling, but to date no systematic study has been conducted in either plant or metazoan systems to define the co-regulatory modes of a G-protein and a hormone.
In this study, we conduct genome-wide gene expression profiling in G-protein subunit mutants of A. thaliana guard cells and leaves, with or without treatment with ABA. By introducing one or more mediators acting downstream of the G-protein and ABA to control transcript levels, we propose nine G-protein/ABA signaling pathways including ABA-independent G-protein signaling pathways, G-protein-independent ABA signaling pathways, and seven distinct ABA–G-protein-coupled signaling pathways (Figure 1). We develop a Boolean modeling framework to systematically enumerate 14 possible theoretical regulatory modes of the G-protein and 142 co-regulatory modes of the G-protein and ABA, and then use a pattern matching approach to associate target genes with theoretical regulatory modes.
Our analysis shows that the G-protein regulatory mode that requires the presence of both Gα and Gβγ subunits (consistent with classical I mechanisms), is well represented in both guard cells and leaves. The G-protein regulatory mode that requires a freed Gβγ subunit (classical II G-protein regulatory mechanism) is well supported in guard cells and somewhat less so in leaves. In addition, a G-protein regulatory mode representing a non-classical regulatory mechanism is prevalent in guard cells but less so in leaves (Figure 5). In this regulatory mode, signaling by Gβ(γ) occurs, and this signaling is not regulated in any way by Gα.
By relating the target genes with the nine proposed G-protein/ABA signaling pathways, we are able to gauge the plausibility of regulatory modes of the G-protein and ABA at the pathway level. We find that G-protein-independent ABA signaling pathways are prevalent in both guard cells and leaves. The existence of an ABA-independent regulatory activity of the G-protein is well supported in guard cells, but not supported in leaves. Additive regulation by G-protein signaling plus G-protein-independent ABA signaling is rare in both guard cells and leaves. In addition, combinatorial cross-talk between G-protein signaling and ABA signaling and additive cross-talk between ABA–G-protein signaling and G-protein-independent ABA signaling are observed in both guard cells and leaves. Our transcriptome analysis indicates that in some cases, ABA definitely does not influence G-protein signaling, though it may do so in some other cases.
To investigate whether previously observed hypersensitivity or hyposensitivity of developmental and dynamic transient responses to ABA in G-protein mutants is recapitulated at the level of transcriptional regulation, we compare gene regulation by ABA in guard cells and leaves of the G-protein mutants versus wild type. We find that in guard cells, equal ABA hyposensitivity of all mutants combined is significant, although hyposensitivity in individual mutants is not. There is also a separate group of genes in guard cells that show ABA hypersensitivity in the gpa1 mutant, suggesting complex interactions between ABA and G-protein signaling in gene regulation in this cell type. In leaves, ABA hyposensitivity of gene expression in the three individual mutants and equal hyposensitivity in all mutants are strongly supported. In addition, several of the functional categories identified by our analysis of G-protein regulatory modes have been implicated in previous physiological analyses of G-protein mutants, providing validation to the biological interpretation of our results.
In summary, by conducting a genome-wide gene expression profiling study in G-protein subunit mutants of A. thaliana guard cells and leaves and developing a Boolean modeling framework, we systematically evaluate the biological utilization of mechanisms of G-protein regulatory action and reveal novel regulatory modes of the G-protein. The results generate empirical evidence and insights regarding molecular events of G-protein signaling and response at the physiological level in both plants and mammals.
Heterotrimeric G-proteins mediate crucial and diverse signaling pathways in eukaryotes. Here, we generate and analyze microarray data from guard cells and leaves of G-protein subunit mutants of the model plant Arabidopsis thaliana, with or without treatment with the stress hormone, abscisic acid. Although G-protein control of the transcriptome has received little attention to date in any system, transcriptome analysis allows us to search for potentially uncommon yet significant signaling mechanisms. We describe the theoretical Boolean mechanisms of G-protein × hormone regulation, and then apply a pattern matching approach to associate gene expression profiles with Boolean models. We find that (1) classical mechanisms of G-protein signaling are well represented. Conversely, some theoretical regulatory modes of the G-protein are not supported; (2) a new mechanism of G-protein signaling is revealed, in which Gβ regulates gene expression identically in the presence or absence of Gα; (3) guard cells and leaves favor different G-protein modes in transcriptome regulation, supporting system specificity of G-protein signaling. Our method holds significant promise for analyzing analogous ‘switch-like' signal transduction events in any organism.
doi:10.1038/msb.2010.28
PMCID: PMC2913393  PMID: 20531402
abscisic acid; Arabidopsis thaliana; Boolean modeling; heterotrimeric G-protein; transcriptome
22.  Pharmacogenetics: implementing personalized medicine 
Pharmacogenetics and pharmacogenomics have been widely recognized as fundamental steps toward personalized medicine. They deal with genetically determined variants in how individuals respond to drugs, and hold the promise to revolutionize drug therapy by tailoring it according to individual genotypes.
The clinical need for novel approaches to improve drug therapy derives from the high rate of adverse reactions to drugs and their lack of efficacy in many individuals that may be predicted by pharmacogenetic testing.
Significant advances in pharmacogenetic research have been made since inherited differences in response to drugs such as isoniazid and succinylcholine were explored in the 1950s. The clinical utility and applications of pharmacogenetics and pharmacogenomics are at present particularly evident in some therapeutic areas (anticancer, psycotrophic, and anticoagulant drugs).
Recent evidence derived from several studies includes screening for thiopurine methyl transferase or uridine 5'-diphosphoglucuronosyl-transferase 1A1 gene polymorphisms to prevent mercaptopurine and azathioprine or irinotecan induced myelosuppression, respectively. Also there is a large body of information concerning cytochrome P450 gene polymorphisms and their relationship to drug toxicity and response. Further examples include screening the presence of the HLA-B*5701 allele to prevent the hypersensitivity reactions to abacavir and the assessment of the human epidermal growth factor receptor (HER-2) expression for trastuzumab therapy of breast cancer or that of KRAS mutation status for cetuximab or panitumumab therapy in colorectal cancer.
Moreover, the application of pharmacogenetics and pharmacogenomics to therapies used in the treatment of osteoarticular diseases (e.g. rheumatoid arthritis, osteoporosis) holds great promise for tailoring therapy with clinically relevant drugs (e.g. disease-modifying antirheumatic drugs, vitamin D, and estrogens).
Although the classical candidate gene approach has helped unravel genetic variants that influence clinical drug responsiveness, gene-wide association studies have recently gained attention as they enable to associate specific genetic variants or quantitative differences in gene expression with drug response.
Although research findings are accumulating, most of the potential of pharmacogenetics and pharmacogenomics remains to be explored and must be validated in prospective randomized clinical trials.
The genetic and molecular foundations of personalized medicine appear solid and evidence indicates its growing importance in healthcare.
PMCID: PMC2781211  PMID: 22461093
pharmacogenetics, drug effects, drug metabolism, drug therapy, antineoplastic agents.
23.  The G protein-coupled receptor subset of the dog genome is more similar to that in humans than rodents 
BMC Genomics  2009;10:24.
Background
The dog is an important model organism and it is considered to be closer to humans than rodents regarding metabolism and responses to drugs. The close relationship between humans and dogs over many centuries has lead to the diversity of the canine species, important genetic discoveries and an appreciation of the effects of old age in another species. The superfamily of G protein-coupled receptors (GPCRs) is one of the largest gene families in most mammals and the most exploited in terms of drug discovery. An accurate comparison of the GPCR repertoires in dog and human is valuable for the prediction of functional similarities and differences between the species.
Results
We searched the dog genome for non-olfactory GPCRs and obtained 353 full-length GPCR gene sequences, 18 incomplete sequences and 13 pseudogenes. We established relationships between human, dog, rat and mouse GPCRs resolving orthologous pairs and species-specific duplicates. We found that 12 dog GPCR genes are missing in humans while 24 human GPCR genes are not part of the dog GPCR repertoire. There is a higher number of orthologous pairs between dog and human that are conserved as compared with either mouse or rat. In almost all cases the differences observed between the dog and human genomes coincide with other variations in the rodent species. Several GPCR gene expansions characteristic for rodents are not found in dog.
Conclusion
The repertoire of dog non-olfactory GPCRs is more similar to the repertoire in humans as compared with the one in rodents. The comparison of the dog, human and rodent repertoires revealed several examples of species-specific gene duplications and deletions. This information is useful in the selection of model organisms for pharmacological experiments.
doi:10.1186/1471-2164-10-24
PMCID: PMC2651185  PMID: 19146662
24.  Progress in Elucidating the Structural and Dynamic Character of G Protein-Coupled Receptor Oligomers for Use in Drug Discovery 
Current pharmaceutical design  2009;15(35):4017-4025.
G Protein-Coupled Receptors (GPCRs) are the most targeted group of proteins for the development of therapeutic drugs. Until the last decade, structural information about this family of membrane proteins was relatively scarce, and their mechanisms of ligand binding and signal transduction were modeled on the assumption that GPCRs existed and functioned as monomeric entities. New crystal structures of native and engineered GPCRs, together with important biochemical and biophysical data that reveal structural details of the activation mechanism(s) of this receptor family, provide a valuable framework to improve dynamic molecular models of GPCRs with the ultimate goal of elucidating their allostery and functional selectivity. Since the dynamic movements of single GPCR protomers are likely to be affected by the presence of neighboring interacting subunits, oligomeric arrangements should be taken into account to improve the predictive ability of computer-assisted structural models of GPCRs for effective use in drug design.
PMCID: PMC4332530  PMID: 20028319
GPCRs; molecular modeling; dynamics; activation; dimerization; oligomerization
25.  Global Survey of Canonical Aspergillus flavus G Protein-Coupled Receptors 
mBio  2014;5(5):e01501-14.
ABSTRACT
G protein-coupled receptors (GPCRs) are transmembrane receptors that relay signals from the external environment inside the cell, allowing an organism to adapt to its surroundings. They are known to detect a vast array of ligands, including sugars, amino acids, pheromone peptides, nitrogen sources, oxylipins, and light. Despite their prevalence in fungal genomes, very little is known about the functions of filamentous fungal GPCRs. Here we present the first full-genome assessment of fungal GPCRs through characterization of null mutants of all 15 GPCRs encoded by the aflatoxin-producing fungus Aspergillus flavus. All strains were assessed for growth, development, ability to produce aflatoxin, and response to carbon sources, nitrogen sources, stress agents, and lipids. Most GPCR mutants were aberrant in one or more response processes, possibly indicative of cross talk in downstream signaling pathways. Interestingly, the biological defects of the mutants did not correspond with assignment to established GPCR classes; this is likely due to the paucity of data for characterized fungal GPCRs. Many of the GPCR transcripts were differentially regulated under various conditions as well. The data presented here provide an extensive overview of the full set of GPCRs encoded by A. flavus and provide a framework for analysis in other fungal species.
IMPORTANCE
Aspergillus flavus is an opportunistic pathogen of crops and animals, including humans, and it produces a carcinogenic toxin called aflatoxin. Because of this, A. flavus accounts for food shortages and economic losses in addition to sickness and death. Effective means of combating this pathogen are needed to mitigate its deleterious effects. G protein-coupled receptors (GPCRs) are often used as therapeutic targets due to their signal specificity, and it is estimated that half of all drugs target GPCRs. In fungi such as A. flavus, GPCRs are likely necessary for sensing the changes in the environment, including food sources, developmental signals, stress agents, and signals from other organisms. Therefore, elucidating their functions in A. flavus could identify ideal receptors against which to develop antagonists.
doi:10.1128/mBio.01501-14
PMCID: PMC4205791  PMID: 25316696

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