GPCRDB information system for G protein-coupled receptors

Proteome-wide analysis reveals G protein-coupled receptor-like proteins in rice (Oryza sativa)

G protein-coupled receptors (GPCRs) constitute the largest family of transmembrane proteins in metazoans that mediate the regulation of various physiological responses to discrete ligands through heterotrimeric G protein subunits. The existence of GPCRs in plant is contentious, but their comparable crucial role in various signaling pathways necessitates the identification of novel remote GPCR-like proteins that essentially interact with the plant G protein α subunit and facilitate the transduction of various stimuli. In this study, we identified three putative GPCR-like proteins (OsGPCRLPs) (LOC_Os06g09930.1, LOC_Os04g36630.1, and LOC_Os01g54784.1) in the rice proteome using a stringent bioinformatics workflow. The identified OsGPCRLPs exhibited a canonical GPCR 'type I' 7TM topology, patterns, and biologically significant sites for membrane anchorage and desensitization. Cluster-based interactome mapping revealed that the identified proteins interact with the G protein α subunit which is a characteristic feature of GPCRs. Computational results showing the interaction of identified GPCR-like proteins with G protein α subunit and its further validation by the membrane yeast-two-hybrid assay strongly suggest the presence of GPCR-like 7TM proteins in the rice proteome. The absence of a regulator of G protein signaling (RGS) box in the C- terminal domain, and the presence of signature motifs of canonical GPCR in the identified OsGPCRLPs strongly suggest that the rice proteome contains GPCR-like proteins that might be involved in signal transduction.

Single-Nucleotide Polymorphisms of TAS2R46 Affect the Receptor Downstream Calcium Regulation in Histamine-Challenged Cells

Bitter taste receptors (TAS2Rs) expressed in extraoral tissues represent a whole-body sensory system, whose role and mechanisms could be of interest for the identification of new therapeutic targets. It is known that TAS2R46s in pre-contracted airway smooth muscle cells increase mitochondrial calcium uptake, leading to bronchodilation, and that several SNPs have been identified in its gene sequence. There are very few reports on the structure-function analysis of TAS2Rs. Thus, we delved into the subject by using mutagenesis and in silico studies. We generated a cellular model that expresses native TAS2R46 to evaluate the influence of the four most common SNPs on calcium fluxes following the activation of the receptor by its specific ligand absinthin. Then, docking studies were conducted to correlate the calcium flux results to the structural mutation. The analysed SNPs differently modulate the TAS2R46 signal cascade according to the altered protein domain. In particular, the SNP in the sixth transmembrane domain of the receptors did not modulate calcium homeostasis, while the SNPs in the sequence coding for the fourth transmembrane domain completely abolished the mitochondrial calcium uptake. In conclusion, these results indicate the fourth transmembrane domain of TAS2R46 is critical for the intrinsic receptor activity.

GPCR-BERT: Interpreting Sequential Design of G Protein-Coupled Receptors Using Protein Language Models

With the rise of transformers and large language models (LLMs) in chemistry and biology, new avenues for the design and understanding of therapeutics have been opened up to the scientific community. Protein sequences can be modeled as language and can take advantage of recent advances in LLMs, specifically with the abundance of our access to the protein sequence data sets. In this letter, we developed the GPCR-BERT model for understanding the sequential design of G protein-coupled receptors (GPCRs). GPCRs are the target of over one-third of Food and Drug Administration-approved pharmaceuticals. However, there is a lack of comprehensive understanding regarding the relationship among amino acid sequence, ligand selectivity, and conformational motifs (such as NPxxY, CWxP, and E/DRY). By utilizing the pretrained protein model (Prot-Bert) and fine-tuning with prediction tasks of variations in the motifs, we were able to shed light on several relationships between residues in the binding pocket and some of the conserved motifs. To achieve this, we took advantage of attention weights and hidden states of the model that are interpreted to extract the extent of contributions of amino acids in dictating the type of masked ones. The fine-tuned models demonstrated high accuracy in predicting hidden residues within the motifs. In addition, the analysis of embedding was performed over 3D structures to elucidate the higher-order interactions within the conformations of the receptors.

GLP1R (glucagon-like-peptide-1 incretin receptor), diabetes and obesity phenotypes: An in silico approach revealed new pathogenic variants

OBJECTIVE

Glucagon-like peptide-1 receptor belongs to the B family of G protein-coupled receptors, serving as a binding protein in membranes and is widely expressed in human tissues. Upon stimulation by its agonist, the glucagon-like peptide-1, the receptor plays a role in glucose metabolism, enhancing insulin secretion, and regulating appetite in the hypothalamus. Mutations in the glucagon-like peptide-1 receptor gene can lead to physiological changes that may explain phenotypic variations in individuals with obesity and diabetes. Therefore, this study aimed to evaluate missense variants of the glucagon-like peptide-1 receptor gene.

METHODS

Data mining was performed on the single nucleotide polymorphism database, retrieving a total of 16,399 variants. Among them, 356 were missense. These 356 variants were analyzed using the PolyPhen-2 and filtered based on allele frequency, resulting in 6 pathogenic variants.

RESULTS

D344E, A239T, R310Q, R227H, R421P, and R176G were analyzed using four different prediction tools. The D344E and A239T resulted in larger amino acid residues compared to their wild-type counterparts. The D344E showed a slightly destabilized structure, while A239T affected the transmembrane helices. Conversely, the R310Q, R227H, R421P, and R176G resulted in smaller amino acid residues than the wild-type, leading to a loss of positive charge and increased hydrophobicity. Particularly, the R421P, due to the presence of proline, significantly destabilized the α-helix structure and caused severe damage to the receptor.

CONCLUSION

Elucidating the glucagon-like peptide-1 receptor variants and their potentially detrimental effects on receptor functionality can contribute to an understanding of metabolic diseases and the response to available pharmacological treatments.

What Makes GPCRs from Different Families Bind to the Same Ligand?

G protein-coupled receptors (GPCRs) are the largest class of cell-surface receptor proteins with important functions in signal transduction and often serve as therapeutic drug targets. With the rapidly growing public data on three dimensional (3D) structures of GPCRs and GPCR-ligand interactions, computational prediction of GPCR ligand binding becomes a convincing option to high throughput screening and other experimental approaches during the beginning phases of ligand discovery. In this work, we set out to computationally uncover and understand the binding of a single ligand to GPCRs from several different families. Three-dimensional structural comparisons of the GPCRs that bind to the same ligand revealed local 3D structural similarities and often these regions overlap with locations of binding pockets. These pockets were found to be similar (based on backbone geometry and side-chain orientation using APoc), and they correlate positively with electrostatic properties of the pockets. Moreover, the more similar the pockets, the more likely a ligand binding to the pockets will interact with similar residues, have similar conformations, and produce similar binding affinities across the pockets. These findings can be exploited to improve protein function inference, drug repurposing and drug toxicity prediction, and accelerate the development of new drugs.

Predicted N-terminal N-linked glycosylation sites may underlie membrane protein expression patterns in Saccharomyces cerevisiae

N-linked glycosylation is one type of posttranslational modification that proteins undergo during expression. The following describes the effects of N-linked glycosylation on high-level membrane protein expression in yeast with an emphasis on Saccharomyces cerevisiae. N-linked glycosylation is highlighted here as an important consideration when preparing membrane protein gene constructs for expression in S. cerevisiae, which continues to be used as a workhorse in both research and industrial applications. Non-native N-linked glycosylation commonly occurs during the heterologous expression of mammalian proteins in many yeast species which can have important immunological consequences when used in the production of biotherapeutic proteins or peptides. Further, non-native N-linked glycosylation can lead to improper protein folding and premature degradation, which can impede high-level expression yields and hinder downstream analysis. Multiple strategies are presented in this article, which suggest different methods that can be implemented to circumvent the unwanted consequences of N-linked glycosylation during the expression process. These considerations may have long-term benefits for high-level protein production in S. cerevisiae across a broad spectrum of expression targets with special emphasis placed on G-protein coupled receptors, one of the largest families of membrane proteins.

G Protein-Coupled Receptors in Taste Physiology and Pharmacology

Heterotrimeric G protein-coupled receptors (GPCRs) comprise the largest receptor family in mammals and are responsible for the regulation of most physiological functions. Besides mediating the sensory modalities of olfaction and vision, GPCRs also transduce signals for three basic taste qualities of sweet, umami (savory taste), and bitter, as well as the flavor sensation kokumi. Taste GPCRs reside in specialised taste receptor cells (TRCs) within taste buds. Type I taste GPCRs (TAS1R) form heterodimeric complexes that function as sweet (TAS1R2/TAS1R3) or umami (TAS1R1/TAS1R3) taste receptors, whereas Type II are monomeric bitter taste receptors or kokumi/calcium-sensing receptors. Sweet, umami and kokumi receptors share structural similarities in containing multiple agonist binding sites with pronounced selectivity while most bitter receptors contain a single binding site that is broadly tuned to a diverse array of bitter ligands in a non-selective manner. Tastant binding to the receptor activates downstream secondary messenger pathways leading to depolarization and increased intracellular calcium in TRCs, that in turn innervate the gustatory cortex in the brain. Despite recent advances in our understanding of the relationship between agonist binding and the conformational changes required for receptor activation, several major challenges and questions remain in taste GPCR biology that are discussed in the present review. In recent years, intensive integrative approaches combining heterologous expression, mutagenesis and homology modeling have together provided insight regarding agonist binding site locations and molecular mechanisms of orthosteric and allosteric modulation. In addition, studies based on transgenic mice, utilizing either global or conditional knock out strategies have provided insights to taste receptor signal transduction mechanisms and their roles in physiology. However, the need for more functional studies in a physiological context is apparent and would be enhanced by a crystallized structure of taste receptors for a more complete picture of their pharmacological mechanisms.

Molecular cloning and expression analysis of mc5r like genes (mc5rl) in Ruditapes philippinarum (Manila clam) after aerial exposure and low-temperature stress

The melanocortin-5 receptor (mc5r) plays an important role in exocrine function, lipid metabolism, obesity, and stress response in the vertebrate. However, the functions of the mc5r in mollusks have been rarely investigated. We cloned the full length of Ruditapes philippinarum mc5r like gene (mc5rl) and the sequence structure and phylogenetic relationship of mc5rl were analyzed. Besides, we detected the tissue distribution and the expression pattern of R. philippinarum mc5r like (mc5rl) genes after aerial exposure and low-temperature stress. The full-length cDNA of the mc5rl-1 was 2143 bp, consisting of a 1224 bp open reading frame encoding (ORF) 408 amino acids. Sequence and phylogenetic analyses revealed that the nucleotide and amino acid sequences of Manila clam mc5rl were highly homologous with mc5r of Crassostrea virginica, Crassostrea gigas, Mizuhopecten yessoensis, and Pecten maximus (32%-36%) and low homologous with vertebrates. The results of the distribution of mc5rl genes showed that mc5rl genes were dominant in the mantle, gonad, and hepatopancreas in R. philippinarum. The expression of mc5rl genes was significantly increased after aerial exposure and low-temperature stress in R. philippinarum in hepatopancreas. Aerial exposure and low-temperature stress could induce mc5rl expressed. Mc5rl might serve as a sensor and promote stress response in R. philippinarum. The cloning and expression characteristics of mc5rl will facilitate the investigation of its function in stress response and other physiological processes in R. philippinarum.

G-Protein coupled receptors: structure and function in drug discovery

The G-protein coupled receptors (GPCRs) superfamily comprise similar proteins arranged into families or classes thus making it one of the largest in the mammalian genome. GPCRs take part in many vital physiological functions making them targets for numerous novel drugs. GPCRs share some distinctive features, such as the seven transmembrane domains, they also differ in the number of conserved residues in their transmembrane domain. Here we provide an introductory and accessible review detailing the computational advances in GPCR pharmacology and drug discovery. An overview is provided on family A-C GPCRs; their structural differences, GPCR signalling, allosteric binding and cooperativity. The dielectric constant (relative permittivity) of proteins is also discussed in the context of site-specific environmental effects.

Dual binding mode of "bitter sugars" to their human bitter taste receptor target

The 25 human bitter taste receptors (hTAS2Rs) are responsible for detecting bitter molecules present in food, and they also play several physiological and pathological roles in extraoral compartments. Therefore, understanding their ligand specificity is important both for food research and for pharmacological applications. Here we provide a molecular insight into the exquisite molecular recognition of bitter β-glycopyranosides by one of the members of this receptor subclass, hTAS2R16. Most of its agonists have in common the presence of a β-glycopyranose unit along with an extremely structurally diverse aglycon moiety. This poses the question of how hTAS2R16 can recognize such a large number of "bitter sugars". By means of hybrid molecular mechanics/coarse grained molecular dynamics simulations, here we show that the three hTAS2R16 agonists salicin, arbutin and phenyl-β-D-glucopyranoside interact with the receptor through a previously unrecognized dual binding mode. Such mechanism may offer a seamless way to fit different aglycons inside the binding cavity, while maintaining the sugar bound, similar to the strategy used by several carbohydrate-binding lectins. Our prediction is validated a posteriori by comparison with mutagenesis data and also rationalizes a wealth of structure-activity relationship data. Therefore, our findings not only provide a deeper molecular characterization of the binding determinants for the three ligands studied here, but also give insights applicable to other hTAS2R16 agonists. Together with our results for other hTAS2Rs, this study paves the way to improve our overall understanding of the structural determinants of ligand specificity in bitter taste receptors.

Multiscale simulations on human Frizzled and Taste2 GPCRs

Recently, molecular dynamics simulations, from all atom and coarse grained to hybrid methods bridging the two scales, have provided exciting functional insights into class F (Frizzled and Taste2) GPCRs (about 40 members in humans). Findings include: (i) The activation of one member of the Frizzled receptors (FZD4) involves a bending of transmembrane helix TM7 far larger than that in class A GPCRs. (ii) The affinity of an anticancer drug targeting another member (Smoothened receptor) decreases in a specific drug-resistant variant, because the mutation ultimately disrupts the binding cavity and affects TM6. (iii) A novel two-state recognition mechanism explains the very large agonist diversity for at least one member of the Taste2 GPCRs, hTAS2R46.

GPCR-SAS: A web application for statistical analyses on G protein-coupled receptors sequences

G protein-coupled receptors (GPCRs) are one of the largest protein families in mammals. They mediate signal transduction across cell membranes and are important targets for the pharmaceutical industry. The G Protein-Coupled Receptors-Sequence Analysis and Statistics (GPCR-SAS) web application provides a set of tools to perform comparative analysis of sequence positions between receptors, based on a curated structural-informed multiple sequence alignment. The analysis tools include: (i) percentage of occurrence of an amino acid or motif and entropy at a position or range of positions, (ii) covariance of two positions, (iii) correlation between two amino acids in two positions (or two sequence motifs in two ranges of positions), and (iv) snake-plot representation for a specific receptor or for the consensus sequence of a group of selected receptors. The analysis of conservation of residues and motifs across transmembrane (TM) segments may guide the design of more selective ligands or help to rationalize activation mechanisms, among others. As an example, here we analyze the amino acids of the "transmission switch", that initiates receptor activation following ligand binding. The tool is freely accessible at http://lmc.uab.cat/gpcrsas/.

Decarboxylation of Ang-(1-7) to Ala1-Ang-(1-7) leads to significant changes in pharmacodynamics

The heptapeptide angiotensin (Ang)-(1-7) is part of the beneficial arm of the renin-angiotensin system. Ang-(1-7) has cardiovascular protective effects, stimulates regeneration, and opposes the often detrimental effects of AngII. We recently identified the G protein-coupled receptors Mas and MrgD as receptors for the heptapeptide. Ala¹-Ang-(1-7) (Alamandine), a decarboxylated form of Ang-(1-7), has similar vasorelaxant effects, but has been described as only stimulating MrgD. Therefore, this study aimed to characterise the consequences of the lack of the carboxyl group in amino acid 1 on intracellular signalling and to identify the receptor fingerprint for Ala¹-Ang-(1-7). In primary endothelial and mesangial cells, Ala¹-Ang-(1-7) elevated cAMP concentration. Dose response curves generated with Ang-(1-7) and Ala¹-Ang-(1-7) significantly differed from each other, with a much lower EC₅₀ and a bell-shape curve for Ala¹-Ang-(1-7). We provided pharmacological proof that both, Mas and MrgD, are functional receptors for Ala¹-Ang-(1-7). Consequently, in primary mesangial cells with genetic deficiency in both receptors, the heptapeptide failed to increase cAMP concentration. As we previously described for Ang-(1-7), the Ala¹-Ang-(1-7)-mediated cAMP increase in Mas/MrgD-transfected HEK293 cells and primary cells was blocked by the AT2 receptor blocker, PD123319. The very distinct dose-response curves for both heptapeptides could be explained by in silico modelling, electrostatic potential calculations, and an involvement of G_{alpha i} for higher concentrations of Ala¹-Ang-(1-7). Our results identify Ala¹-Ang-(1-7) as a peptide with specific pharmacodynamic properties and builds the basis for the design of more potent and efficient Ang-(1-7) analogues for therapeutic intervention in a rapidly growing number of diseases.

Structure and biological activity of endogenous and synthetic agonists of GPR119

A G-protein-coupled receptor, GPR119, is a promising pharmacological target for a new class of hypoglycaemic drugs with an original mechanism of action, namely, increase in the glucose-dependent incretin and insulin secretion. In 2005, the first ligands were found and in the subsequent years, a large number of GPR119 agonists were synthesized in laboratories in various countries; the safest and most promising agonists have entered phase I and II clinical trials as agents for the treatment of type 2 diabetes mellitus and obesity. The review describes the major endogenous GPR119 agonists and the main trends in the design and modification of synthetic structures for increasing the hypoglycaemic activity. The data on synthetic agonists are arranged according to the type of the central core of the molecules.

The bibliography includes 104 references.

Apelinergic System Structure and Function

Apelin and apela (ELABELA/ELA/Toddler) are two peptide ligands for a class A G-protein-coupled receptor named the apelin receptor (AR/APJ/APLNR). Ligand-AR interactions have been implicated in regulation of the adipoinsular axis, cardiovascular system, and central nervous system alongside pathological processes. Each ligand may be processed into a variety of bioactive isoforms endogenously, with apelin ranging from 13 to 55 amino acids and apela from 11 to 32, typically being cleaved C-terminal to dibasic proprotein convertase cleavage sites. The C-terminal region of the respective precursor protein is retained and is responsible for receptor binding and subsequent activation. Interestingly, both apelin and apela exhibit isoform-dependent variability in potency and efficacy under various physiological and pathological conditions, but most studies focus on a single isoform. Biophysical behavior and structural properties of apelin and apela isoforms show strong correlations with functional studies, with key motifs now well determined for apelin. Unlike its ligands, the AR has been relatively difficult to characterize by biophysical techniques, with most characterization to date being focused on effects of mutagenesis. This situation may improve following a recently reported AR crystal structure, but there are still barriers to overcome in terms of comprehensive biophysical study. In this review, we summarize the three components of the apelinergic system in terms of structure-function correlation, with a particular focus on isoform-dependent properties, underlining the potential for regulation of the system through multiple endogenous ligands and isoforms, isoform-dependent pharmacological properties, and biological membrane-mediated receptor interaction. © 2018 American Physiological Society. Compr Physiol 8:407-450, 2018.

Experiences with Deriva: An Asset Management Platform for Accelerating eScience

The pace of discovery in eScience is increasingly dependent on a scientist's ability to acquire, curate, integrate, analyze, and share large and diverse collections of data. It is all too common for investigators to spend inordinate amounts of time developing ad hoc procedures to manage their data. In previous work, we presented Deriva, a Scientific Asset Management System, designed to accelerate data driven discovery. In this paper, we report on the use of Deriva in a number of substantial and diverse eScience applications. We describe the lessons we have learned, both from the perspective of the Deriva technology, as well as the ability and willingness of scientists to incorporate Scientific Asset Management into their daily workflows.

Structural Analysis of Chemokine Receptor-Ligand Interactions

This review focuses on the construction and application of structural chemokine receptor models for the elucidation of molecular determinants of chemokine receptor modulation and the structure-based discovery and design of chemokine receptor ligands. A comparative analysis of ligand binding pockets in chemokine receptors is presented, including a detailed description of the CXCR4, CCR2, CCR5, CCR9, and US28 X-ray structures, and their implication for modeling molecular interactions of chemokine receptors with small-molecule ligands, peptide ligands, and large antibodies and chemokines. These studies demonstrate how the integration of new structural information on chemokine receptors with extensive structure–activity relationship and site-directed mutagenesis data facilitates the prediction of the structure of chemokine receptor–ligand complexes that have not been crystallized. Finally, a review of structure-based ligand discovery and design studies based on chemokine receptor crystal structures and homology models illustrates the possibilities and challenges to find novel ligands for chemokine receptors.

A Method for the Annotation of Functional Similarities of Coding DNA Sequences: the Case of a Populated Cluster of Transmembrane Proteins

The analysis of a large number of human and mouse genes codifying for a populated cluster of transmembrane proteins revealed that some of the genes significantly vary in their primary nucleotide sequence inter-species and also intra-species. In spite of that divergence and of the fact that all these genes share a common parental function we asked the question of whether at DNA level they have some kind of common compositional structure, not evident from the analysis of their primary nucleotide sequence. To reveal the existence of gene clusters not based on primary sequence relationships we have analyzed 13574 human and 14047 mouse genes by the composon-clustering methodology. The data presented show that most of the genes from each one of the samples are distributed in 18 clusters sharing the common compositional features between the particular human and mouse clusters. It was observed, in addition, that between particular human and mouse clusters having similar composon-profiles large variations in gene population were detected as an indication that a significant amount of orthologs between both species differs in compositional features. A gene cluster containing exclusively genes codifying for transmembrane proteins, an important fraction of which belongs to the Rhodopsin G-protein coupled receptor superfamily, was also detected. This indicates that even though some of them display low sequence similarity, all of them, in both species, participate with similar compositional features in terms of composons. We conclude that in this family of transmembrane proteins in general and in the Rhodopsin G-protein coupled receptor in particular, the composon-clustering reveals the existence of a type of common compositional structure underlying the primary nucleotide sequence closely correlated to function.

Prediction of G-protein coupled receptors and their subfamilies by incorporating various sequence features into Chou's general PseAAC

BACKGROUND AND OBJECTIVE

The G-protein coupled receptors are the largest superfamilies of membrane proteins and important targets for the drug design. G-protein coupled receptors are responsible for many physiochemical processes such as smell, taste, vision, neurotransmission, metabolism, cellular growth and immune response. So it is necessary to design a robust and efficient approach for the prediction of G-protein coupled receptors and their subfamilies.

METHODS

In this paper, the protein samples are represented by amino acid composition, dipeptide composition, correlation features, composition, transition, distribution, sequence order descriptors and pseudo amino acid composition with total 1497 number of sequence derived features. To address the issue of efficient classification of G-protein coupled receptors and their subfamilies, we propose to use a weighted k-nearest neighbor classifier with UNION of best 50 features, selected by Fisher score based feature selection, ReliefF, fast correlation based filter, minimum redundancy maximum relevancy, and support vector machine based recursive elimination feature selection methods to exploit the advantages of these feature selection methods.

RESULTS

The proposed method achieved an overall accuracy of 99.9%, 98.3%, 95.4%, MCC values of 1.00, 0.98, 0.95, ROC area values of 1.00, 0.998, 0.996 and precision of 99.9%, 98.3% and 95.5% using 10-fold cross-validation to predict the G-protein coupled receptors and non-G-protein coupled receptors, subfamilies of G-protein coupled receptors, and subfamilies of class A G-protein coupled receptors, respectively.

CONCLUSIONS

The high accuracies, MCC, ROC area values, and precision values indicate that the proposed method is better for the prediction of G-protein coupled receptors families and their subfamilies.

Prediction of G Protein-Coupled Receptors with SVM-Prot Features and Random Forest

G protein-coupled receptors (GPCRs) are the largest receptor superfamily. In this paper, we try to employ physical-chemical properties, which come from SVM-Prot, to represent GPCR. Random Forest was utilized as classifier for distinguishing them from other protein sequences. MEME suite was used to detect the most significant 10 conserved motifs of human GPCRs. In the testing datasets, the average accuracy was 91.61%, and the average AUC was 0.9282. MEME discovery analysis showed that many motifs aggregated in the seven hydrophobic helices transmembrane regions adapt to the characteristic of GPCRs. All of the above indicate that our machine-learning method can successfully distinguish GPCRs from non-GPCRs.

Genome and Transcriptome Sequences Reveal the Specific Parasitism of the Nematophagous Purpureocillium lilacinum 36-1

Purpureocillium lilacinum is a promising nematophagous ascomycete able to adapt diverse environments and it is also an opportunistic fungus that infects humans. A microbial inoculant of P. lilacinum has been registered to control plant parasitic nematodes. However, the molecular mechanism of the toxicological processes is still unclear because of the relatively few reports on the subject. In this study, using Illumina paired-end sequencing, the draft genome sequence and the transcriptome of P. lilacinum strain 36-1 infecting nematode-eggs were determined. Whole genome alignment indicated that P. lilacinum 36-1 possessed a more dynamic genome in comparison with P. lilacinum India strain. Moreover, a phylogenetic analysis showed that the P. lilacinum 36-1 had a closer relation to entomophagous fungi. The protein-coding genes in P. lilacinum 36-1 occurred much more frequently than they did in other fungi, which was a result of the depletion of repeat-induced point mutations (RIP). Comparative genome and transcriptome analyses revealed the genes that were involved in pathogenicity, particularly in the recognition, adhesion of nematode-eggs, downstream signal transduction pathways and hydrolase genes. By contrast, certain numbers of cellulose and xylan degradation genes and a lack of polysaccharide lyase genes showed the potential of P. lilacinum 36-1 as an endophyte. Notably, the expression of appressorium-formation and antioxidants-related genes exhibited similar infection patterns in P. lilacinum strain 36-1 to those of the model entomophagous fungi Metarhizium spp. These results uncovered the specific parasitism of P. lilacinum and presented the genes responsible for the infection of nematode-eggs.

GPCRdb: the G protein-coupled receptor database - an introduction

GPCRs make up the largest family of human membrane proteins and of drug targets. Recent advances in GPCR pharmacology and crystallography have shed new light on signal transduction, allosteric modulation and biased signalling, translating into new mechanisms and principles for drug design. The GPCR database, GPCRdb, has served the community for over 20 years and has recently been extended to include a more multidisciplinary audience. This review is intended to introduce new users to the services in GPCRdb, which meets three overall purposes: firstly, to provide reference data in an integrated, annotated and structured fashion, with a focus on sequences, structures, single‐point mutations and ligand interactions. Secondly, to equip the community with a suite of web tools for swift analysis of structures, sequence similarities, receptor relationships, and ligand target profiles. Thirdly, to facilitate dissemination through interactive diagrams of, for example, receptor residue topologies, phylogenetic relationships and crystal structure statistics. Herein, these services are described for the first time; visitors and guides are provided with good practices for their utilization. Finally, we describe complementary databases cross‐referenced by GPCRdb and web servers with corresponding functionality.

Camphor-based CCR5 blocker lead compounds – a computational and experimental approach

This study identifies novel camphor-derived compounds that bind the CCR5 receptor and can be used as lead compounds for drug discovery.

Comparing Class A GPCRs to bitter taste receptors: Structural motifs, ligand interactions and agonist-to-antagonist ratios

G protein-coupled receptors (GPCRs) are seven transmembrane (TM) proteins that play a key role in human physiology. The GPCR superfamily comprises about 800 members, classified into several classes, with rhodopsin-like Class A being the largest and most studied thus far. A huge component of the human repertoire consists of the chemosensory GPCRs, including ∼400 odorant receptors, 25 bitter taste receptors (TAS2Rs), which are thought to guard the organism from consuming poisons, and sweet and umami TAS1R heteromers, which indicate the nutritive value of food. The location of the binding site of TAS2Rs is similar to that of Class A GPCRs. However, most of the known bitter ligands are agonists, with only a few antagonists documented thus far. The agonist-to-antagonist ratios of Class A GPCRs vary, but in general are much lower than for TAS2Rs. For a set of well-studied GPCRs, a gradual change in agonists-to-antagonists ratios is observed when comparing low (10 μM)- and high (10 nM)-affinity ligand sets from ChEMBL and the DrugBank set of drugs. This shift reflects pharmaceutical bias toward the therapeutically desirable pharmacology for each of these GPCRs, while the 10 μM sets possibly represent the native tendency of the receptors toward either agonists or antagonists. Analyzing ligand-GPCR interactions in 56 X-ray structures representative of currently available structural data, we find that the N-terminus, TM1 and TM2 are more involved in binding of antagonists than of agonists. On the other hand, ECL2 tends to be more involved in binding of agonists. This is of interest, since TAS2Rs harbor variations on the typical Class A sequence motifs, including the absence of the ECL2-TM3 disulfide bridge. This suggests an alternative mode of regulation of conformational states for TAS2Rs, with potentially less stabilized inactive state. The comparison of TAS2Rs and Class A GPCRs structural features and the pharmacology of the their ligands highlights the intricacies of GPCR architecture and provides a framework for rational design of new ligands.

GPCRdb: an information system for G protein-coupled receptors

Recent developments in G protein-coupled receptor (GPCR) structural biology and pharmacology have greatly enhanced our knowledge of receptor structure-function relations, and have helped improve the scientific foundation for drug design studies. The GPCR database, GPCRdb, serves a dual role in disseminating and enabling new scientific developments by providing reference data, analysis tools and interactive diagrams. This paper highlights new features in the fifth major GPCRdb release: (i) GPCR crystal structure browsing, superposition and display of ligand interactions; (ii) direct deposition by users of point mutations and their effects on ligand binding; (iii) refined snake and helix box residue diagram looks; and (iii) phylogenetic trees with receptor classification colour schemes. Under the hood, the entire GPCRdb front- and back-ends have been re-coded within one infrastructure, ensuring a smooth browsing experience and development. GPCRdb is available at http://www.gpcrdb.org/ and it's open source code at https://bitbucket.org/gpcr/protwis.

Medicinal chemistry in the era of big data

In the era of big data medicinal chemists are exposed to an enormous amount of bioactivity data. Numerous public data sources allow for querying across medium to large data sets mostly compiled from literature. However, the data available are still quite incomplete and of mixed quality. This mini review will focus on how medicinal chemists might use such resources and how valuable the current data sources are for guiding drug discovery.

Applying random forest and subtractive fuzzy c-means clustering techniques for the development of a novel G protein-coupled receptor discrimination method using pseudo amino acid compositions

G protein-coupled receptors (GPCRs) constitute the largest superfamily of integral membrane proteins (IMPs) and they tremendously contribute in the flow of information into cells. In this study, the random forest (RF) and the subtractive fuzzy c-means clustering (SBC) methods have been used to determine the importance of input variables and discriminate GPCRs from non-GPCRs using twenty amino acid and fifty pseudo amino acid compositions derived from GPCR sequences. The studied dataset was retrieved from the UniProt/SWISSPROT database and consists of 1000 GPCR and 1000 non-GPCR reviewed sequences. The top ranked RF-SBC-based model discriminates GPCRs and non-GPCRs successfully with the accuracy, sensitivity, specificity and Matthew's coefficient correlation (MCC) rates of 99.15%, 99.60%, 98.70% and 0.983%, respectively. These rates were obtained from averaged values of 5-fold cross validation using only twenty four out of fifty pseudo amino acid composition features. The results show that the proposed RF-SBC-based model outperforms other existing algorithms in terms of the evaluated performance criteria. The webserver for the proposed algorithm is available at http://brcinfo.shinyapps.io/GPCRIden.

GPCRserver: an accurate and novel G protein-coupled receptor predictor

G protein coupled receptors (GPCRs), also known as seven-transmembrane domain receptors, pass through the cellular membrane seven times and play diverse biological roles in the cells such as signaling, transporting of molecules and cell-cell communication. In this work, we develop a web server, namely the GPCRserver, which is capable of identifying GPCRs from genomic sequences, and locating their transmembrane regions. The GPCRserver contains three modules: (1) the Trans-GPCR for the transmembrane region prediction by using sequence evolutionary profiles with the assistance of neural network training, (2) the SSEA-GPCR for identifying GPCRs from genomic data by using secondary structure element alignment, and (3) the PPA-GPCR for identifying GPCRs by using profile-to-profile alignment. Our predictor was strictly benchmarked and showed its favorable performance in the real application. The web server and stand-alone programs are publicly available at .

Promiscuity and selectivity of bitter molecules and their receptors

Bitter taste is essential for survival, as it protects against consuming poisonous compounds, which are often bitter. Bitter taste perception is mediated by bitter taste receptors (TAS2Rs), a subfamily of G-protein coupled receptors (GPCRs). The number of TAS2R subtypes is species-dependent, and varies from 3 in chicken to 50 in frog. TAS2Rs present an intriguing case for studying promiscuity: some of the receptors are still orphan, or have few known agonists, while others can be activated by numerous, structurally dissimilar compounds. The ligands also vary in the repertoire of TAS2Rs that they activate: some bitter compounds are selective toward a single TAS2R, while others activate multiple TAS2Rs. Selectivity/promiscuity profile of bitter taste receptors and their compounds was explored by a chemoinformatic approach. TAS2R-promiscuous and TAS2R-selective bitter molecules were found to differ in chemical features, such as AlogP, E-state, total charge, number of rings, globularity, and heavy atom count. This allowed the prediction of bitter ligand selectivity toward TAS2Rs. Interestingly, while promiscuous TAS2Rs are activated by both TAS2R-promiscuous and TAS2R-selective compounds, almost all selective TAS2Rs in human are activated by promiscuous compounds, which are recognized by other TAS2Rs anyway. Thus, unique ligands, that may have been the evolutionary driving force for development of selective TAS2Rs, still need to be unraveled.

Role of G protein-coupled orphan receptors in intestinal inflammation: novel targets in inflammatory bowel diseases

A large number of proteins were classified into the family of G protein-coupled receptors (GPCRs). Based on their characteristic serpentine domain, they are called 7 TM receptors. Presently, their ligands and physiological functions remain unknown. In this review, we summarize what is known on these receptors and discuss the potential use of these orphan GPCRs (GPRs) in the induction or maintenance of remission in inflammatory bowel diseases. We focus on GPRs 30, 41, 43, 55, 119, and 120, where scientific evidence supports a potential role in intestinal inflammation.

Generic GPCR residue numbers - aligning topology maps while minding the gaps

Generic residue numbers facilitate comparisons of, for example, mutational effects, ligand interactions, and structural motifs. The numbering scheme by Ballesteros and Weinstein for residues within the class A GPCRs (G protein-coupled receptors) has more than 1100 citations, and the recent crystal structures for classes B, C, and F now call for a community consensus in residue numbering within and across these classes. Furthermore, the structural era has uncovered helix bulges and constrictions that offset the generic residue numbers. The use of generic residue numbers depends on convenient access by pharmacologists, chemists, and structural biologists. We review the generic residue numbering schemes for each GPCR class, as well as a complementary structure-based scheme, and provide illustrative examples and GPCR database (GPCRDB) web tools to number any receptor sequence or structure.

Exploiting open data: a new era in pharmacoinformatics

Within the last decade open data concepts has been gaining increasing interest in the area of drug discovery. With the launch of ChEMBL and PubChem, an enormous amount of bioactivity data was made easily accessible to the public domain. In addition, platforms that semantically integrate those data, such as the Open PHACTS Discovery Platform, permit querying across different domains of open life science data beyond the concept of ligand-target-pharmacology. However, most public databases are compiled from literature sources and are thus heterogeneous in their coverage. In addition, assay descriptions are not uniform and most often lack relevant information in the primary literature and, consequently, in databases. This raises the question how useful large public data sources are for deriving computational models. In this perspective, we highlight selected open-source initiatives and outline the possibilities and also the limitations when exploiting this huge amount of bioactivity data.

Analysis of the pharmacological properties of chicken melanocortin-2 receptor (cMC2R) and chicken melanocortin-2 accessory protein 1 (cMRAP1)

The chicken (Gallus gallus) melanocortin-2 receptor (cMC2R) can be functionally expressed in CHO cells when chicken melanocortin-2 receptor accessory protein 1 (cMRAP1) is co-expressed. The transiently transfected CHO cells responded in a robust manner to stimulation by hACTH(1-24) (EC50 value=2.7 × 10(-12)M +/- 1.3 × 10(-12)), but the transfected CHO cells could not be stimulated by NDP-MSH at concentrations as high as 10(-7)M. Incubation of cMC2R/cMRAP1 transfected cells with alanine substituted analogs of hACTH(1-24) at amino acid positions F(7) or W(9) completely blocked stimulation of the transfected cells. Similarly, incubation of cMC2R/cMRAP1 transfected cells with an analog of hACTH(1-24) with alanine substitutions at amino acid positions R(17)R(18)P(19) resulted in a 276 fold shift in EC50 value relative to the positive control (p<0.004). Collectively these observations suggest that cMC2R has binding sites for the HFRW motif and KKRRP motif of hACTH(1-24), and both motifs are required for full activation of the receptor. While previous studies had shown that Anolis carolinensis MC2R and Xenopus tropicalis MC2R could be functionally expressed in CHO cells that co-expressed mouse MRAP1, co-expression of these non-mammalian tetrapod MC2Rs with cMRAP1 resulted in a significant increase in sensitivity to hACTH(1-24), as measured by EC50 value, for A. carolinensis MC2R (p<0.005) and X. tropicalis MC2R (p<0.007). The implications of these observations are discussed.

GPCRsort-responding to the next generation sequencing data challenge: prediction of G protein-coupled receptor classes using only structural region lengths

Next generation sequencing (NGS) and the attendant data deluge are increasingly impacting molecular life sciences research. Chief among the challenges and opportunities is to enhance our ability to classify molecular target data into meaningful and cohesive systematic nomenclature. In this vein, the G protein-coupled receptors (GPCRs) are the largest and most divergent receptor family that plays a crucial role in a host of pathophysiological pathways. For the pharmaceutical industry, GPCRs are a major drug target and it is estimated that 60%-70% of all medicines in development today target GPCRs. Hence, they require an efficient and rapid classification to group the members according to their functions. In addition to NGS and the Big Data challenge we currently face, an emerging number of orphan GPCRs further demand for novel, rapid, and accurate classification of the receptors since the current classification tools are inadequate and slow. This study presents the development of a new classification tool for GPCRs using the structural features derived from their primary sequences: GPCRsort. Comparison experiments with the current known GPCR classification techniques showed that GPCRsort is able to rapidly (in the order of minutes) classify uncharacterized GPCRs with 97.3% accuracy, whereas the best available technique's accuracy is 90.7%. GPCRsort is available in the public domain for postgenomics life scientists engaged in GPCR research with NGS: http://bioserver.ceng.metu.edu.tr/GPCRSort .

Molecular evolution of GPCRs: Melanocortin/melanocortin receptors

The melanocortin receptors (MCRs) are a family of G protein-coupled receptors that are activated by melanocortin ligands derived from the proprotein, proopiomelanocortin (POMC). During the radiation of the gnathostomes, the five receptors have become functionally segregated (i.e. melanocortin 1 receptor (MC1R), pigmentation regulation; MC2R, glucocorticoid synthesis; MC3R and MC4R, energy homeostasis; and MC5R, exocrine gland physiology). A focus of this review is the role that ligand selectivity plays in the hypothalamus/pituitary/adrenal-interrenal (HPA-I) axis of teleosts and tetrapods as a result of the exclusive ligand selectivity of MC2R for the ligand ACTH. A second focal point of this review is the roles that the accessory proteins melanocortin 2 receptor accessory protein 1 (MRAP1) and MRAP2 are playing in, respectively, the HPA-I axis (MC2R) and the regulation of energy homeostasis by neurons in the hypothalamus (MC4R) of teleosts and tetrapods. In addition, observations are presented on trends in the ligand selectivity parameters of cartilaginous fish, teleost, and tetrapod MC1R, MC3R, MC4R, and MC5R paralogs, and the modeling of the HFRW motif of ACTH(1-24) when compared with α-MSH. The radiation of the MCRs during the evolution of the gnathostomes provides examples of how the physiology of endocrine and neuronal circuits can be shaped by ligand selectivity, the intersession of reverse agonists (agouti-related peptides (AGRPs)), and interactions with accessory proteins (MRAPs).

Bioinformatics tools for predicting GPCR gene functions

The automatic classification of GPCRs by bioinformatics methodology can provide functional information for new GPCRs in the whole 'GPCR proteome' and this information is important for the development of novel drugs. Since GPCR proteome is classified hierarchically, general ways for GPCR function prediction are based on hierarchical classification. Various computational tools have been developed to predict GPCR functions; those tools use not simple sequence searches but more powerful methods, such as alignment-free methods, statistical model methods, and machine learning methods used in protein sequence analysis, based on learning datasets. The first stage of hierarchical function prediction involves the discrimination of GPCRs from non-GPCRs and the second stage involves the classification of the predicted GPCR candidates into family, subfamily, and sub-subfamily levels. Then, further classification is performed according to their protein-protein interaction type: binding G-protein type, oligomerized partner type, etc. Those methods have achieved predictive accuracies of around 90 %. Finally, I described the future subject of research of the bioinformatics technique about functional prediction of GPCR.

Alpha-bulges in G protein-coupled receptors

Agonist binding is related to a series of motions in G protein-coupled receptors (GPCRs) that result in the separation of transmembrane helices III and VI at their cytosolic ends and subsequent G protein binding. A large number of smaller motions also seem to be associated with activation. Most helices in GPCRs are highly irregular and often contain kinks, with extensive literature already available about the role of prolines in kink formation and the precise function of these kinks. GPCR transmembrane helices also contain many α-bulges. In this article we aim to draw attention to the role of these α-bulges in ligand and G-protein binding, as well as their role in several aspects of the mobility associated with GPCR activation. This mobility includes regularization and translation of helix III in the extracellular direction, a rotation of the entire helix VI, an inward movement of the helices near the extracellular side, and a concerted motion of the cytosolic ends of the helices that makes their orientation appear more circular and that opens up space for the G protein to bind. In several cases, α-bulges either appear or disappear as part of the activation process.

Topology assessment, G protein-coupled receptor (GPCR) prediction, and in vivo interaction assays to identify plant candidate GPCRs

Genomic sequencing has provided a vast resource for identifying interesting genes, but often an exact "gene-of-interest" is unknown and is only described as putatively present in a genome by an observed phenotype, or by the known presence of a conserved signaling cascade, such as that facilitated by the heterotrimeric G-protein. The low sequence similarity of G protein-coupled receptors (GPCRs) and the absence of a known ligand with an associated high-throughput screening system in plants hampers their identification by simple BLAST queries or brute force experimental assays. Combinatorial bioinformatic analysis is useful in that it can reduce a large pool of possible candidates to a number manageable by medium or even low-throughput methods. Here we describe a method for the bioinformatic identification of candidate GPCRs from whole proteomes and their subsequent in vivo analysis for G-protein coupling using a membrane based yeast two-hybrid variant (Gookin et al., Genome Biol 9:R120, 2008). Rather than present the bioinformatic process in a format requiring scripts or computer programming knowledge, we describe procedures here in a simple, biologist-friendly outline that only utilizes the basic syntax of regular expressions.