Distribution analysis of nonsynonymous polymorphisms within the G-protein-coupled receptor gene family

MUG: A mutation overview of GPCR subfamily A17 receptors

G protein-coupled receptors (GPCRs) mediate several signaling pathways through a general mechanism that involves their activation, upholding a chain of events that lead to the release of molecules responsible for cytoplasmic action and further regulation. These physiological functions can be severely altered by mutations in GPCR genes. GPCRs subfamily A17 (dopamine, serotonin, adrenergic and trace amine receptors) are directly related with neurodegenerative diseases, and as such it is crucial to explore known mutations on these systems and their impact in structure and function. A comprehensive and detailed computational framework - MUG (Mutations Understanding GPCRs) - was constructed, illustrating key reported mutations and their effect on receptors of the subfamily A17 of GPCRs. We explored the type of mutations occurring overall and in the different families of subfamily A17, as well their localization within the receptor and potential effects on receptor functionality. The mutated residues were further analyzed considering their pathogenicity. The results reveal a high diversity of mutations in the GPCR subfamily A17 structures, drawing attention to the considerable number of mutations in conserved residues and domains. Mutated residues were typically hydrophobic residues enriched at the ligand binding pocket and known activating microdomains, which may lead to disruption of receptor function. MUG as an interactive web application is available for the management and visualization of this dataset. We expect that this interactive database helps the exploration of GPCR mutations, their influence, and their familywise and receptor-specific effects, constituting the first step in elucidating their structures and molecules at the atomic level.

Synchronous birth is a dominant pattern in receptor-ligand evolution

Background

Interactions between proteins are key components in the chemical and physical processes of living organisms. Among these interactions, membrane receptors and their ligands are particularly important because they are at the interface between extracellular and intracellular environments. Many studies have investigated how binding partners have co-evolved in genomes during the evolution. However, little is known about the establishment of the interaction on a phylogenetic scale.

In this study, we systematically studied the time of birth of genes encoding human membrane receptors and their ligands in the animal tree of life. We examined a total of 553 pairs of ligands/receptors, representing non-redundant interactions.

Results

We found that 41% of the receptors and their respective first ligands appeared in the same branch, representing 2.5-fold more than expected by chance, thus suggesting an evolutionary dynamic of interdependence and conservation between these partners. In contrast, 21% of the receptors appeared after their ligand, i.e. three-fold less often than expected by chance. Most surprisingly, 38% of the receptors appeared before their first ligand, as much as expected by chance.

Conclusions

According to these results, we propose that a selective pressure is exerted on ligands and receptors once they appear, that would remove molecules whose partner does not appear quickly.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-4977-2) contains supplementary material, which is available to authorized users.

Comprehensive Analysis of Non-Synonymous Natural Variants of G Protein-Coupled Receptors

G protein-coupled receptors (GPCRs) are the largest superfamily of transmembrane receptors and have vital signaling functions in various organs. Because of their critical roles in physiology and pathology, GPCRs are the most commonly used therapeutic target. It has been suggested that GPCRs undergo massive genetic variations such as genetic polymorphisms and DNA insertions or deletions. Among these genetic variations, non-synonymous natural variations change the amino acid sequence and could thus alter GPCR functions such as expression, localization, signaling, and ligand binding, which may be involved in disease development and altered responses to GPCR-targeting drugs. Despite the clinical importance of GPCRs, studies on the genotype-phenotype relationship of GPCR natural variants have been limited to a few GPCRs such as β-adrenergic receptors and opioid receptors. Comprehensive understanding of non-synonymous natural variations within GPCRs would help to predict the unknown genotype-phenotype relationship and yet-to-be-discovered natural variants. Here, we analyzed the non-synonymous natural variants of all non-olfactory GPCRs available from a public database, UniProt. The results suggest that non-synonymous natural variations occur extensively within the GPCR superfamily especially in the N-terminus and transmembrane domains. Within the transmembrane domains, natural variations observed more frequently in the conserved residues, which leads to disruption of the receptor function. Our analysis also suggests that only few non-synonymous natural variations have been studied in efforts to link the variations with functional consequences.

Membrane Proteins Are Dramatically Less Conserved than Water-Soluble Proteins across the Tree of Life

Membrane proteins are crucial in transport, signaling, bioenergetics, catalysis, and as drug targets. Here, we show that membrane proteins have dramatically fewer detectable orthologs than water-soluble proteins, less than half in most species analyzed. This sparse distribution could reflect rapid divergence or gene loss. We find that both mechanisms operate. First, membrane proteins evolve faster than water-soluble proteins, particularly in their exterior-facing portions. Second, we demonstrate that predicted ancestral membrane proteins are preferentially lost compared with water-soluble proteins in closely related species of archaea and bacteria. These patterns are consistent across the whole tree of life, and in each of the three domains of archaea, bacteria, and eukaryotes. Our findings point to a fundamental evolutionary principle: membrane proteins evolve faster due to stronger adaptive selection in changing environments, whereas cytosolic proteins are under more stringent purifying selection in the homeostatic interior of the cell. This effect should be strongest in prokaryotes, weaker in unicellular eukaryotes (with intracellular membranes), and weakest in multicellular eukaryotes (with extracellular homeostasis). We demonstrate that this is indeed the case. Similarly, we show that extracellular water-soluble proteins exhibit an even stronger pattern of low homology than membrane proteins. These striking differences in conservation of membrane proteins versus water-soluble proteins have important implications for evolution and medicine.

Minireview: Toward the establishment of a link between melatonin and glucose homeostasis: association of melatonin MT2 receptor variants with type 2 diabetes

The existence of interindividual variations in G protein-coupled receptor sequences has been recognized early on. Recent advances in large-scale exon sequencing techniques are expected to dramatically increase the number of variants identified in G protein-coupled receptors, giving rise to new challenges regarding their functional characterization. The current minireview will illustrate these challenges based on the MTNR1B gene, which encodes the melatonin MT2 receptor, for which exon sequencing revealed 40 rare nonsynonymous variants in the general population and in type 2 diabetes (T2D) cohorts. Functional characterization of these MT2 mutants revealed 14 mutants with loss of Gi protein activation that associate with increased risk of T2D development. This repertoire of disease-associated mutants is a rich source for structure-activity studies and will help to define the still poorly understood role of melatonin in glucose homeostasis and T2D development in humans. Defining the functional defects in carriers of rare MT2 mutations will help to provide personalized therapies to these patients in the future.

The (non)malignancy of cancerous amino acidic substitutions

The process of natural selection acts both on individual organisms within a population and on individual cells within an organism as they develop into cancer. In this work, we have taken a first step toward understanding the differences in selection pressures exerted on the human genome under these disparate circumstances. Focusing on single amino acid substitutions, we have found that cancer-related mutations (CRMs) are frequent in evolutionarily conserved sites, whereas single amino acid polymorphisms (SAPs) tend to appear in sites having a more relaxed evolutionary pressure. Those CRMs classed as cancer driver mutations show greater enrichment for conserved sites than passenger mutations. Consistent with this, driver mutations are enriched for sites annotated as key functional residues and their neighbors, and are more likely to be located on the surface of proteins than expected by chance. Overall the pattern of CRM and polymorphism is remarkably similar, but we do see a clear signal indicative of diversifying selection for disruptive amino acid substitutions in the cancer driver mutations. The ultimate consequence of the appearance of those mutations must be advantageous for the tumor cell, leading to cell population-growth and migration events similar to those seen in natural ecosystems.

Structural imperatives impose diverse evolutionary constraints on helical membrane proteins

The amino acid sequences of transmembrane regions of helical membrane proteins are highly constrained, diverging at slower rates than their extramembrane regions and than water-soluble proteins. Moreover, helical membrane proteins seem to fall into fewer families than water-soluble proteins. The reason for the differential restrictions on sequence remains unexplained. Here, we show that the evolution of transmembrane regions is slowed by a previously unrecognized structural constraint: Transmembrane regions bury more residues than extramembrane regions and soluble proteins. This fundamental feature of membrane protein structure is an important contributor to the differences in evolutionary rate and to an increased susceptibility of the transmembrane regions to disease-causing single-nucleotide polymorphisms.

New insights into GPCR function: implications for HTS

G protein-coupled receptors (GPCRs) are a large family of proteins that represent targets for approximately 40% of all approved drugs. They possess unique structural motifs that allow them to interact with a diverse series of extracellular ligands, as well as intracellular signaling proteins, such as G proteins, RAMPs, arrestins, and indeed other receptors. Extensive efforts are under way to discover new generations of drugs against GPCRs with unique targeted therapeutic uses, including "designer" drugs such as allosteric regulators, inverse agonists, and drugs targeting hetero-oligomeric complexes. This has been facilitated by the development of new screening technologies to identify novel drugs against both known and orphan GPCRs.

Polymorphisms in uncoupling protein, melanocortin 3 receptor, melanocortin 4 receptor, and pro-opiomelanocortin genes and association with production traits in a commercial broiler line

Because avian uncoupling protein (avUCP), melanocortin 3 receptor (MC3R), melanocortin 4 receptor (MC4R), and pro-opiomelanocortin (POMC) genes may be associated with production traits [e.g., BW, weight gain (WG), and feed conversion ratio (FCR)], male and female broilers from an elite broiler line were screened for polymorphisms in these genes. The PCR-restriction fragment length polymorphism (RFLP) tests were developed to type the missense polymorphisms UCPAla118Val, MC4RSer76Leu, MC3R-Met54Leu, and Gly104Ser and POMCPro61Leu. Of 39 single nucleotide polymorphisms identified in all 4 genes, 24/39 were transitions with 11 having a C to T change. Of the 23 polymorphisms in UCP, 17 represented at least 7 haplotypes in this pedigreed broiler line. The UCP Ala-118Val allele was associated with a) high feed efficiency (FE; P = 0.03) and WG (P = 0.053) in selected males, and b) high BW in selected females (P = 0.07) and unselected males (P = 0.015). The UCPVal118Val allele was found in approximately 10% of the birds that were screened. Five silent substitutions, 3 in MC3R and 2 in MC4R, were also identified. Thirteen polymorphisms were identified in the POMC gene representing at least 3 different alleles. A missense Pro61Leu heterozygote was associated with greater BW in females. The heterozygote MC3R Gly104Ser polymorphism was associated with greater FE in selected males (P = 0.03) and greater BW in unselected males (P = 0.007). The MC4R Ser76Leu heterozygote polymorphism was associated with greater BW than the Leu76 homozygote in females (P = 0.05). From these findings, we hypothesize that UCP, MC3R, MC4R and POMC genes may play important roles and could be candidate loci for production traits such as feed conversion and BW in commercial broiler breeding stock.

Accurate prediction of deleterious protein kinase polymorphisms

MOTIVATION

Contemporary, high-throughput sequencing efforts have identified a rich source of naturally occurring single nucleotide polymorphisms (SNPs), a subset of which occur in the coding region of genes and result in a change in the encoded amino acid sequence (non-synonymous coding SNPs or 'nsSNPs'). It is hypothesized that a subset of these nsSNPs may underlie common human disease. Testing all these polymorphisms for disease association would be time consuming and expensive. Thus, computational methods have been developed to both prioritize candidate nsSNPs and make sense of their likely molecular physiologic impact.

RESULTS

We have developed a method to prioritize nsSNPs and have applied it to the human protein kinase gene family. The results of our analyses provide high quality predictions and outperform available whole genome prediction methods (74% versus 83% prediction accuracy). Our analyses and methods consider both DNA sequence conservation, which most traditional methods are based on, as well unique structural and functional features of kinases. We provide a ranked list of common kinase nsSNPs that have a higher probability of impacting human disease based on our analyses.

Emerging concepts of guanine nucleotide-binding protein-coupled receptor (GPCR) function and implications for high throughput screening

Guanine nucleotide binding protein (G protein) coupled receptors (GPCRs) comprise one of the largest families of proteins in the human genome and are a target for 40% of all approved drugs. GPCRs have unique structural motifs that allow them to interact with a wide and diverse series of extracellular ligands, as well as intracellular proteins, G proteins, receptor activity-modifying proteins, arrestins, and indeed other receptors. This distinctive structure has led to numerous efforts to discover drugs against GPCRs with targeted therapeutic uses. Such "designer" drugs currently include allosteric regulators, inverse agonists, and drugs targeting hetero-oligomeric complexes. Moreover, the large family of orphan GPCRs provides a rich and novel field of targets to discover drugs with unique therapeutic properties. The numerous technologies to discover GPCR drugs have also greatly advanced over the years, facilitating compound screening against known and orphan GPCRs, as well as in the identification of unique designer GPCR drugs. Indeed, high throughput screening (HTS) technologies employing functional cell-based approaches are now widely used. These include measurement of second messenger accumulation such as cyclic AMP, calcium ions, and inositol phosphates, as well as mitogen-activated protein kinase activation, protein-protein interactions, and GPCR oligomerization. This review focuses on how the improved understanding of the molecular pharmacology of GPCRs, coupled with a plethora of novel HTS technologies, is leading to the discovery and development of an entirely new generation of GPCR-based therapeutics.

Arginine (CGC) codon targeting in the human prostacyclin receptor gene (PTGIR) and G-protein coupled receptors (GPCR)

The human prostacyclin receptor (hIP) has recently been recognized as an important seven transmembrane G-protein coupled receptor that plays critical roles in atheroprevention and cardioprotection. To date, four non-synonymous genetic variants have been identified, two of which occur at the same Arg amino acid position (R212H, R212C). This observation instigated further genetic screening for prostacyclin receptor variants on 1455 human genomic samples. A total of 31 distinct genetic variants were detected, with 6 (19%) involving Arg residues. Distinct differences in location and frequencies of genetic variants were noted between Caucasian, Asian, Hispanic and African Americans, with the most changes noted in the Asian cohort. From the sequencing results, three Arg-targeted changes at the same 212 position within the third cytoplasmic loop of the human prostacyclin (hIP) receptor were detected: 1) R212C (CGC-->TGC), 2) R212H (CGC-->CAC), and 3) R212R (CGC-->CGT). Three additional Arg codon variants (all exhibiting the same CGC to TGC change) were also detected, R77C, R215C, and R279C. Analysis (GPCR and SNP databases) of 200 other GPCRs, with recorded non-synonymous mutations, confirmed a high frequency of Arg-targeted missense mutations, particularly within the important cytoplasmic domain. Preferential nucleotide changes (at Arg codons), were observed involving cytosine (C) to thymine (T) (pyrimidine to pyrimidine), as well as guanine (G) to adenine (A) (purine to purine) (p<0.001, Pearson's goodness-of-fit test). Such targeting of Arg residues, leading to significant changes in coding amino acid size and/or charge, may have potentially-important structural and evolutionary implications on the hIP and GPCRs in general. In the case of the human prostacyclin receptor, such alterations may reduce the cardio-, vasculo-, and cytoprotective effects of prostacyclin.

Biosynthesis and trafficking of seven transmembrane receptor signalling complexes

Recent studies have shown that 7-transmembrane receptors (7TM-Rs), their associated signalling molecules and scaffolding proteins are often constitutively associated under basal conditions. These studies highlight that receptor ontogeny and trafficking are likely to play key roles in the determination of both signalling specificity and efficacy. This review highlights information about how 7TM-Rs and their associated signalling molecules are trafficked to the cell surface as well as other intracellular destinations.

Recent developments in constitutive receptor activity and inverse agonism, and their potential for GPCR drug discovery

The concept of constitutively active G-protein-coupled receptors is now firmly rooted in receptor pharmacology. Many independent research groups have contributed to its acceptance since its introduction by Costa and Herz in 1989. This concept necessitated a revised ligand classification, and a new category of inverse agonists was introduced alongside existing agonist and antagonist ligands. Initially, it was hoped that new therapeutic modalities would become available. However, the drug industry has not adopted inverse agonism as a design criterion and instead accepted that some compounds emerge as (neutral) antagonists in compound screening, whereas other compounds possess inverse agonistic activity. In this article, we summarize aspects of the impact of constitutive activity on the drug-discovery process: for example, its use in orphan receptor assays, its link with pharmacogenetics and genomics, and its relevance for currently marketed drugs.

Human adenosine 2B receptor: SNP discovery and evaluation of expression in patients with cystic fibrosis

OBJECTIVES AND METHODS

We analyzed the adenosine 2B (A2B) receptor gene, which consists of two exons, for single nucleotide polymorphisms (SNPs) and tested the hypothesis that coding sequence polymorphisms in the gene contribute to disease state in patients with cystic fibrosis (CF). Using PCR and restriction fragment length polymorphism (RFLP) analysis, we assessed 53 American subjects of mixed ethnicity, 64 European Caucasian control subjects and 148 Caucasian patients with CF for A2B SNPs.

RESULTS

We identified one SNP in the 5' untranslated region (UTR) and seven SNPs in the open reading frame. One SNP was identified in the coding region of a German patient with CF but in none of the American subjects. No other SNPs were found in CF patients. A nonsynonymous SNP was identified in exon 2 of the German controls with an allelic frequency of 11%. The US subjects were of mixed ethnicity and most frequently (10.4%) had a SNP in the 5'UTR; 7 coding SNPs occurred in <3%. All SNPs other than the Leu96Phe and Gly136Arg variants were found only in African-Americans. Of the 26 African-Americans who were genotyped, 42% were hypertensive but the study group was too small to show an association between blood pressure status and SNP expression.

CONCLUSIONS

The data show that SNPs in the A2B receptor gene are much more frequent in African-Americans than in Caucasians and that German Caucasians, but not African-Americans, express Gly136Arg. None of the SNPs identified in A2B receptors are likely to be modifiers in CF.

Sequence variation in G-protein-coupled receptors: analysis of single nucleotide polymorphisms

We assessed the disease-causing potential of single nucleotide polymorphisms (SNPs) based on a simple set of sequence-based features. We focused on SNPs from the dbSNP database in G-protein-coupled receptors (GPCRs), a large class of important transmembrane (TM) proteins. Apart from the location of the SNP in the protein, we evaluated the predictive power of three major classes of features to differentiate between disease-causing mutations and neutral changes: (i) properties derived from amino-acid scales, such as volume and hydrophobicity; (ii) position-specific phylogenetic features reflecting evolutionary conservation, such as normalized site entropy, residue frequency and SIFT score; and (iii) substitution-matrix scores, such as those derived from the BLOSUM62, GRANTHAM and PHAT matrices. We validated our approach using a control dataset consisting of known disease-causing mutations and neutral variations. Logistic regression analyses indicated that position-specific phylogenetic features that describe the conservation of an amino acid at a specific site are the best discriminators of disease mutations versus neutral variations, and integration of all our features improves discrimination power. Overall, we identify 115 SNPs in GPCRs from dbSNP that are likely to be associated with disease and thus are good candidates for genotyping in association studies.

Lower rate of genomic variation identified in the trans-membrane domain of monoamine sub-class of Human G-Protein Coupled Receptors: the Human GPCR-DB Database

Background

We have surveyed, compiled and annotated nucleotide variations in 338 human 7-transmembrane receptors (G-protein coupled receptors). In a sample of 32 chromosomes from a Nordic population, we attempted to determine the allele frequencies of 80 non-synonymous SNPs, and found 20 novel polymorphic markers. GPCR receptors of physiological and clinical importance were prioritized for statistical analysis. Natural variation and rare mutation information were merged and presented online in the Human GPCR-DB database .

Results

The average number of SNPs per 1000 bases of exonic sequence was found to be twice the average number of SNPs per Kilobase of intronic regions (2.2 versus 1.0). Of the 338 genes, 111 were single exon genes, that is, were intronless. The average number of exonic-SNPs per single-exon gene was 3.5 (n = 395) while that for multi-exon genes was 0.8 (n = 1176). The average number of variations within the different protein domain (N-terminus, internal- and external-loops, trans-membrane region, C-terminus) indicates a lower rate of variation in the trans-membrane region of Monoamine GPCRs, as compared to Chemokine- and Peptide-receptor sub-classes of GPCRs.

Conclusions

Single-exon GPCRs on average have approximately three times the number of SNPs as compared to GPCRs with introns. Among various functional classes of GPCRs, Monoamine GPRCs have lower number of natural variations within the trans-membrane domain indicating evolutionary selection against non-synonymous changes within the membrane-localizing domain of this sub-class of GPCRs.

Inherited Diseases Involving G Proteins and G Protein–Coupled Receptors

Heterotrimeric G proteins couple seven-transmembrane receptors for diverse extracellular signals to effectors that generate intracellular signals altering cell function. Mutations in the gene encoding the alpha subunit of the G protein-coupling receptors to stimulation of adenylyl cyclase cause developmental abnormalities of bone, as well as hormone resistance (pseudohypoparathyroidism caused by loss-of-function mutations) and hormone hypersecretion (McCune-Albright syndrome caused by gain-of-function mutations). Loss- and gain-of-function mutations in genes encoding G protein-coupled receptors (GPCRs) have been identified as the cause of an increasing number of retinal, endocrine, metabolic, and developmental disorders. GPCRs comprise an evolutionarily conserved gene superfamily ( 1 ). By coupling to heterotrimeric G proteins, GPCRs transduce a wide variety of extracellular signals including monoamine, amino acid, and nucleoside neurotransmitters, as well as photons, chemical odorants, divalent cations, hormones, lipids, peptides and proteins. Following a brief overview of G protein-coupled signal transduction, we review the growing body of evidence that mutations in genes encoding GPCRs and G proteins are an important cause of human disease.

Drug receptor/effector polymorphisms and pharmacogenetics: current status and challenges

The pharmacogenetics literature of drug receptors and effector proteins is in its relative infancy compared to that of drug metabolism pharmacogenetics. Nonetheless, in a short time period, numerous studies have demonstrated that receptor/effector polymorphisms contribute to variable drug response. We review the current status, and list challenges that confront drug target pharmacogenetics before we can use genetic information in drug-therapy decision-making. We focus our review on G protein coupled receptors (GPCRs), which represent over 50% of all drug targets, and use specific examples from the beta-adrenergic receptor pharmacogenetic literature to illustrate important issues. Recent resequencing efforts of GPCR genes suggest that they have more coding region and nonsynonymous polymorphisms than non-GPCR genes, thus making GPCRs important foci for pharmacogenetic investigation. Our inability to use drug target genetic information to guide in the selection of drug therapy is due to several factors, including (i) the relatively subtle functional effects of the single gene polymorphisms, which do not account for enough of the drug response variability to accurately predict response and (ii) inconsistencies between studies. The latter may be due to some studies having inadequate sample sizes, studying different drug response phenotypes and patient populations, difficulties in identifying and measuring a valid drug response phenotype, and focusing on single polymorphisms in single genes, rather than haplotypes or multiple genes. To move the field to the point of clinical application, future studies will need to be larger, and will have to consider the complexity of the drug response, either by inclusion of polymorphisms from signal transduction proteins and other proteins relevant to the drug response, or through a genomics approach. Finally, the literature suggests that, for those drugs with multiple pharmacologic effects, or effects in multiple organs, the genetic contribution to each drug response phenotype will have to be considered separately. The knowledge necessary to move forward on all these fronts is not yet available, but will be increasingly accessible over the next few years.

Pharmacogenomics and ???Individualized Drug Therapy???

Since 1965 there have been more than 800 pharmacogenetics/genomics reviews - most suggesting that we are on the verge of offering individualized drug therapy to everyone. However, there are numerous reasons why this approach will be extremely difficult to achieve in the foreseeable future. Drug treatment outcome represents a complex phenotype, encoded by dozens, if not hundreds, of genes, and affected by many environmental factors; therefore, we will almost always see a gradient of response. Phenotyping assays of blood enzyme activities (if feasible) are generally more successful than DNA genotyping for predicting unequivocal outcomes of drug therapy in each and every patient. Phenotyping with probe drugs has generally not succeeded, because of the overlapping substrate specificities not only of drug-metabolizing enzymes but also transporters, receptors, ion channels, transcription factors, and other drug targets; drug-drug interactions, enzyme induction and inhibition, and multiple (enzyme, transporter, second-messenger, signal transduction) pathways also present enormous problems. Genotyping to predict drug disposition, efficacy, toxicity, and clinical outcome has been proposed, but the success of genotyping in individualized drug therapy currently appears unlikely because of the many shortcomings (frequency of DNA variant sites, ethnic differences, admixture) and complexities (plasticity of the genome, multiple mechanisms for determining sizes and locations of haplotype blocks) of this approach. Genomics is an important tool in basic research; yet, it is unrealistic to include genotyping within the realm of tests available to the practicing clinician in the foreseeable future. The same can be said for transcriptomics and proteomics, which also rely on available sources (tumors, biopsies, excreta). The newly emerging fields of metabonomics and phenomics might offer solutions to anticipating and decreasing individual risk for adverse drug reactions in each individual patient; however, tests based on these approaches are not expected to become available to the practicing clinician for at least the next 5-10 years.