Visualisation and integration of G protein-coupled receptor related information help the modelling: description and applications of the Viseur program

Language workbench user interfaces for data analysis

Biological data analysis is frequently performed with command line software. While this practice provides considerable flexibility for computationally savy individuals, such as investigators trained in bioinformatics, this also creates a barrier to the widespread use of data analysis software by investigators trained as biologists and/or clinicians. Workflow systems such as Galaxy and Taverna have been developed to try and provide generic user interfaces that can wrap command line analysis software. These solutions are useful for problems that can be solved with workflows, and that do not require specialized user interfaces. However, some types of analyses can benefit from custom user interfaces. For instance, developing biomarker models from high-throughput data is a type of analysis that can be expressed more succinctly with specialized user interfaces. Here, we show how Language Workbench (LW) technology can be used to model the biomarker development and validation process. We developed a language that models the concepts of Dataset, Endpoint, Feature Selection Method and Classifier. These high-level language concepts map directly to abstractions that analysts who develop biomarker models are familiar with. We found that user interfaces developed in the Meta-Programming System (MPS) LW provide convenient means to configure a biomarker development project, to train models and view the validation statistics. We discuss several advantages of developing user interfaces for data analysis with a LW, including increased interface consistency, portability and extension by language composition. The language developed during this experiment is distributed as an MPS plugin (available at http://campagnelab.org/software/bdval-for-mps/).

The family of G protein-coupled receptors: an example of membrane proteins

The G protein coupled receptors belong to the largest group of membrane proteins that regulates many essential physiological properties and represents an important class of drug targets. In this chapter, we show how the synergy between a laboratory experiment and computational modeling leads to structural delineation of the ligand binding pocket and how the knowledge of ligand-protein interactions is used for rational local and global drug design in which the structural knowledge of a particular receptor and its ligands is used for drug design of this particular GPCR and others.

Computational studies of ligand-receptor interactions in bitter taste receptors

Phenylthiocarbamide tastes intensely bitter to some individuals, but others find it completely tasteless. Recently, it was suggested that phenylthiocarbamide elicits bitter taste by interacting with a human G protein-coupled receptor (hTAS2R38) encoded by the PTC gene. The phenylthiocarbamide nontaster trait was linked to three single nucleotide polymorphisms occurring in the PTC gene. Using the crystal structure of bovine rhodopsin as template, we generated the 3D structure of hTAS2R38 bitter taste receptor. We were able to map on the receptor structure the amino acids affected by the genetic polymorphisms and to propose molecular functions for two of them that explained the emergence of the nontaster trait. We used molecular docking simulations to find that phenylthiocarbamide exhibited a higher affinity for the target receptor than the structurally similar molecule 6-n-propylthiouracil, in line with recent experimental studies. A 3D model was constructed for the hTAS2R16 bitter taste receptor as well, by applying the same protocol. We found that the recently published experimental ligand binding affinity data for this receptor correlated well with the binding scores obtained from our molecular docking calculations.

Modeled structure of a G-protein-coupled receptor: the cholecystokinin-1 receptor

The Cholecystokinin-1 receptor (CCK1R) mediates actions of CCK in areas of the central nervous system and of the gut. It is a potential target to treat a number of diseases. As for all G-protein-coupled receptors, docking of ligands into modeled CCK1R binding site should greatly help to understand intrinsic mechanisms of activation. Here, we describe the procedure we used to progressively build a structural model for the CCK1R, to integrated, and on the basis of site-directed mutagenesis data on its binding site. Reliability of the CCK1R model was confirmed by interaction networks that involved conserved and functionally crucial motifs in G-protein-coupled receptors, such as Glu/Asp-Arg-Tyr and Asn-Pro-Xaa-Xaa-Tyr motifs. In addition, the 3-D structure of CCK1R-bound CCK resembled that determined by NMR in a lipid environment. The derived computational model was also used for revealing binding modes of several nonpeptide ligands and for rationalizing ligand structure-activity relationships known from experiments. Our findings indeed support that our "validated CCK1R model" could be used to study the intrinsic mechanism of CCK1R activation and design new ligands.

Prediction of the odorant binding site of olfactory receptor proteins by human-mouse comparisons

Olfactory receptors (ORs) are a large family of proteins involved in the recognition and discrimination of numerous odorants. These receptors belong to the G-protein coupled receptor (GPCR) hyperfamily, for which little structural data are available. In this study we predict the binding site residues of OR proteins by analyzing a set of 1441 OR protein sequences from mouse and human. The central insight utilized is that functional contact residues would be conserved among pairs of orthologous receptors, but considerably less conserved among paralogous pairs. Using judiciously selected subsets of 218 ortholog pairs and 518 paralog pairs, we have identified 22 sequence positions that are both highly conserved among the putative orthologs and variable among paralogs. These residues are disposed on transmembrane helices 2 to 7, and on the second extracellular loop of the receptor. Strikingly, although the prediction makes no assumption about the location of the binding site, these amino acid positions are clustered around a pocket in a structural homology model of ORs, mostly facing the inner lumen. We propose that the identified positions constitute the odorant binding site. This conclusion is supported by the observation that all but one of the predicted binding site residues correspond to ligand-contact positions in other rhodopsin-like GPCRs.

Identification of core amino acids stabilizing rhodopsin

Rhodopsin is the only G protein-coupled receptor (GPCR) whose 3D structure is known; therefore, it serves as a prototype for studies of the GPCR family of proteins. Rhodopsin dysfunction has been linked to misfolding, caused by chemical modifications that affect the naturally occurring disulfide bond between C110 and C187. Here, we identify the structural elements that stabilize rhodopsin by computational analysis of the rhodopsin structure and comparison with data from previous in vitro mutational studies. We simulate the thermal unfolding of rhodopsin by breaking the native-state hydrogen bonds sequentially in the order of their relative strength, using the recently developed Floppy Inclusion and Rigid Substructure Topography (FIRST) method [Jacobs, D. J., Rader, A. J., Kuhn, L. A. & Thorpe, M. F. (2001) Proteins 44, 150-165]. Residues most stable under thermal denaturation are part of a core, which is assumed to be important for the formation and stability of folded rhodopsin. This core includes the C110-C187 disulfide bond at the center of residues forming the interface between the transmembrane and the extracellular domains near the retinal binding pocket. Fast mode analysis of rhodopsin using the Gaussian network model also identifies the disulfide bond and the retinal ligand binding pocket to be the most rigid region in rhodopsin. Experiments confirm that 90% of the amino acids predicted by the FIRST method to be part of the core cause misfolding upon mutation. The observed high degree of conservation (78.9%) of this disulfide bond across all GPCR classes suggests that it is critical for the stability and function of GPCRs.

Building protein diagrams on the web with the residue-based diagram editor RbDe

The residue-based diagram editor (RbDe) is web-based software that greatly simplifies the construction of schematic diagrams of proteins. Residue-based diagrams display the sequence of a given protein in the context of its secondary and tertiary structure. Such diagrams are frequently used to summarize mutations or sequence features, in the context of the overall topology of a protein. The initial version of RbDe was designed for transmembrane proteins and has enabled many users to create diagrams of large systems such as G protein-coupled receptors or transporters. We present an extended diagram editor that supports other families of proteins. Users can now import custom-diagram layouts, use them to render members of any protein family and generate high-quality output for publication purposes. RbDe is available free over the web, at http://icb.mssm.edu/crt/RbDe

Identification of tyrosine 189 and asparagine 358 of the cholecystokinin 2 receptor in direct interaction with the crucial C-terminal amide of cholecystokinin by molecular modeling, site-directed mutagenesis, and structure/affinity studies

The cholecystokinin (CCK) receptors CCK1R and CCK2R exert important central and peripheral functions by binding the neuropeptide cholecystokinin. Because these receptors are potential therapeutic targets, great interest has been devoted to the identification of efficient ligands that selectively activate or inhibit these receptors. A complete mapping of the CCK binding site in these receptors would help to design new CCK ligands and to optimize their properties. In this view, a molecular model of the CCK2R occupied by CCK was built to identify CCK2R residues that interact with CCK functional groups. No such study has yet been reported for the CCK2R. Docking of CCK in the receptor was performed by taking into account our previous mutagenesis data and by using, as constraint, the direct interaction that we demonstrated between His207 in the CCK2R and Asp8 of CCK (Mol Pharmacol 54:364-371, 1998; J Biol Chem 274:23191-23197, 1999). Two residues that had not been revealed in our previous mutagenesis studies, Tyr189 (Y4.60) and Asn358 (N6.55), were identified in interaction via hydrogen bonds with the C-terminal amide of CCK, a crucial functional group of the peptide. Mutagenesis of Tyr189 (Y4.60) and Asn358 (N6.55) as well as structure-affinity studies with modified CCK analogs validated these interactions and the involvement of both residues in the CCK binding site. These results indicate that the present molecular model is an important tool to identify direct contact points between CCK and the CCK2R and to rapidly progress in mapping of the CCK2R binding site. Moreover, comparison of the present CCK2R.CCK molecular model with that of CCK1R.CCK, which we have previously published and validated, clearly argues that the positioning of CCK in these receptors is different.

Rhodopsin crystal: new template yielding realistic models of G-protein-coupled receptors?

Molecular modelling is of major help to understand structure-function data on G-protein-coupled receptors (GPCRs). Since the first determination of the structure of rhodopsin, at high resolution, the view has emerged that it will be now easy to automatically obtain realistic models for any GPCR by homology modeling. Our experience on cholecystokinin CCK(1) receptor modelling together with available data on other GPCRs leads us to rule out this opinion. We believe that construction of realistic models of certain GPCRs still remains time-consuming and requires many refinements of the models in close association with experiments. This conclusion has important consequences for modelling orphan GPCRs.

GPCRDB information system for G protein-coupled receptors

The GPCRDB is a molecular class-specific information system that collects, combines, validates and disseminates heterogeneous data on G protein-coupled receptors (GPCRs). The database stores data on sequences, ligand binding constants and mutations. The system also provides computationally derived data such as sequence alignments, homology models, and a series of query and visualization tools. The GPCRDB is updated automatically once every 4-5 months and is freely accessible at http://www.gpcr.org/7tm/.

Structure of cholecystokinin receptor binding sites and mechanism of activation/inactivation by agonists/antagonists

Delineation of CCK receptor binding sites is a prerequisite for the understanding of the molecular basis for ligand recognition, partial agonism, ligand-induced traffiking of receptor signalling. In the current paper, we illustrate how, in the past 5 years, studies from our laboratory and others have provided new data on the molecular basis of the pharmacology and functioning of CCK1 and CCK2 receptors. Available data on CCK1 and CCK2R binding sites indicate that 1) homologous regions of the two receptors are involved in the binding site of CCK, however, positioning of CCK slightly differs; 2) binding sites of non-peptide agonists/antagonist are buried in the pocket formed by transmembrane helices and overlap that of CCK and 3) residues of the binding sites as well as of conserved motifs such as E/DRY, NPXXY are crucial for receptor activation.

DNA variation and psychopharmacology of the human serotonin receptor 1B (HTR1B) gene

One of the neurotransmitter serotonin's receptors, HTR1B, is of interest for many neuropsychiatric traits, illnesses and treatments for multiple reasons, especially its tissue distribution, pharmacological profile and findings from mice lacking the receptor, along with reasons generally implicating serotonin. Eight mutation scans have uncovered sixteen polymorphisms in the coding sequence and surrounding 5'- and 3'-untranslated regions and much is now known of the distribution of these polymorphisms in various ethnic groups and their linkage disequilibrium relationships. Thus far, evidence exists that the uncommon missense T371G (Phe124Cys) and the common promoter region A-161T polymorphisms may exhibit functional effects and possibly that the common synonymous G861C (or more likely a variant in linkage disequilibrium with G861C) does as well. From the eighteen reported population-based case control studies of HTR1B to multiple disorders, several facts stand out. There exists preliminary evidence for association of G861C with i) antisocial alcoholism in the Finnish; ii) alcoholism in the presence of inactive aldehyde dehydrogenase 2 in the Japanese; iii) a history of suicide attempts in European-American personality disorder patients; and iv) minimum lifetime body mass index in Canadian bulimia nervosa patients. From the three reported family-based case control studies of HTR1B to various disorders, one provides preliminary evidence for association of G861C with obsessive compulsive disorder. Although many association studies have been completed, positive results should still be considered preliminary. As these preliminary reports are tested for replication with larger, more powerful samples, there should be increased clarity as to which findings remain robust; in some cases this will require the application of meta-analytic techniques.

The biologically crucial C terminus of cholecystokinin and the non-peptide agonist SR-146,131 share a common binding site in the human CCK1 receptor. Evidence for a crucial role of Met-121 in the activation process

The cholecystokinin (CCK) receptor-1 (CCK1R) is a G protein-coupled receptor, which mediates important central and peripheral cholecystokinin actions. Our aim was to progress in mapping of the CCK1R binding site by identifying residues that interact with the methionine and phenylalanine residues of the C-terminal moiety of CCK because these are crucial for its binding and biological activity, and to determine whether CCK and the selective non-peptide agonist, SR-146,131, share a common binding site. Identification of putative amino acids of the CCK1R binding site was achieved by dynamics-based docking of the ligand CCK in a refined three-dimensional model of the CCK1R using, as constraints, previous results that identified contact points between residues of CCK and CCK1R (Kennedy, K., Gigoux, V., Escrieut, C., Maigret, B., Martinez, J., Moroder, L., Frehel, D., Gully, D., Vaysse, N., and Fourmy, D. (1997) J. Biol. Chem. 272, 2920-2926 and Gigoux, V., Escrieut, C., Fehrentz, J. A., Poirot, S., Maigret, B., Moroder, L., Gully, D., Martinez, J., Vaysse, N., and Fourmy, D. (1999) J. Biol. Chem. 274, 20457-20464). By this approach, a series of residues forming connected hydrophobic clusters were identified. Pharmacological and functional analysis of mutated receptors indicated that a network of hydrophobic residues including Cys-94, Met-121, Val-125, Phe-218, Ile-329, Phe-330, Trp-326, Ile-352, Leu-356, and Tyr-360, is involved in the binding site for CCK and in the activation process of the CCK1R. Within this hydrophobic network, the physico-chemical nature of residue 121 seems to be essential for CCK1R functioning. Finally, the biological properties of mutants together with dynamic docking of SR-146,131 in the CCK1R binding site demonstrated that SR-146,131 occupies a region of CCK1R binding site which interacts with the C-terminal amidated tripeptide of CCK, i.e. Met-Asp-Phe-NH(2). These new and important insights will serve to better understand the activation process of CCK1R and to design or optimize ligands.

tGRAP, the G-protein coupled receptors mutant database

The searchable mutant database tGRAP (previously called tinyGRAP) at the University of Tromsø contains data on mutated G-protein coupled receptors (GPCRs). All data have been extracted from scientific papers and entered manually into the database. The current version of the tGRAP mutant database (tGRAP.uit.no, release 10, April 2001) contains around 10 500 mutants extracted from almost 1400 research papers containing mutant data on five families of GPCRs, i.e. Family A, rhodopsin-like; Family B, secretin-like; Family C, metabotropic glutamate-like; Family D, pheromone; Family E, cAMP receptors. A query form provides rapid and simple access to relevant mutant information. In addition to this query form, a tool that enables the user to access mutation data via sequence alignments has been introduced. The ability to access mutant data from such alignments increases the usefulness of the mutant database and facilitates comparison of mutagenesis data between receptors. Moreover, this tool allows the construction of tailor-made sequence alignment views from any combination of receptors belonging to the same class. The database is available at http://tGRAP.uit.no/.

Genetic diversity of the human serotonin receptor 1B (HTR1B) gene

We systematically and comprehensively investigated polymorphisms of the HTR1B gene as well as their linkage disequilibrium and ancestral relationships. We have detected the following polymorphisms in our sample via denaturing gradient gel electrophoresis, database comparisons, and/or previously published assays: G-511T, T-261G, -182INS/DEL-181, A-161T, C129T, T371G, T655C, C705T, G861C, A1099G, G1120A, and A1180G. The results of the intermarker analyses showed strong linkage disequilibrium between the C129T and the G861C polymorphisms and revealed four common haplotypes: ancestral (via chimpanzee comparisons), 129T/861C, -161T, and -182DEL-181. The results of association tests with schizophrenia were negative, although A-161T had a nominal P = 0.04 via ASPEX/sib_tdt. The expressed missense substitutions, Phe124Cys, Phe219Leu, Ile367Val, and Glu374Lys, could potentially affect ligand binding or interaction with G proteins and thus modify drug response in carriers of these variants. On average, the human cSNPs and differences among other primates clustered in the more thermodynamically unstable regions of the mRNA, which suggests that the evolutionary survival of nucleotide sequence variation may be influenced by the mRNA structure of this gene.

Collecting and harvesting biological data: the GPCRDB and NucleaRDB information systems

The amount of genomic and proteomic data that is entered each day into databases and the experimental literature is outstripping the ability of experimental scientists to keep pace. While generic databases derived from automated curation efforts are useful, most biological scientists tend to focus on a class or family of molecules and their biological impact. Consequently, there is a need for molecular class-specific or other specialized databases. Such databases collect and organize data around a single topic or class of molecules. If curated well, such systems are extremely useful as they allow experimental scientists to obtain a large portion of the available data most relevant to their needs from a single source. We are involved in the development of two such databases with substantial pharmacological relevance. These are the GPCRDB and NucleaRDB information systems, which collect and disseminate data related to G protein-coupled receptors and intra-nuclear hormone receptors, respectively. The GPCRDB was a pilot project aimed at building a generic molecular class-specific database capable of dealing with highly heterogeneous data. A first version of the GPCRDB project has been completed and it is routinely used by thousands of scientists. The NucleaRDB was started recently as an application of the concept for the generalization of this technology. The GPCRDB is available via the WWW at http://www.gpcr.org/7tm/ and the NucleaRDB at http://www.receptors.org/NR/.

Interactive construction of residue-based diagrams of proteins: the RbDe web service

We announce the Residue-based Diagram Editor (RbDe) web service that allows online construction of residue-based diagrams and the creation of stored diagram libraries. The service has been tuned for the construction of snake-like diagrams (for transmembrane proteins) but can be used to render any protein for which defined secondary structure data or hypotheses are available. RbDe is freely available through the Internet from our web site: http://transport.physbio. mssm.edu/rbde/RbDe.html. Licenses for intranet uses can be obtained upon request.

Schematic representation of residue-based protein context-dependent data: an application to transmembrane proteins

An algorithmic method for drawing residue-based schematic diagrams of proteins on a 2D page is presented and illustrated. The method allows the creation of rendering engines dedicated to a given family of sequences, or fold. The initial implementation provides an engine that can produce a 2D diagram representing secondary structure for any transmembrane protein sequence. We present the details of the strategy for automating the drawing of these diagrams. The most important part of this strategy is the development of an algorithm for laying out residues of a loop that connects to arbitrary points of a 2D plane. As implemented, this algorithm is suitable for real-time modification of the loop layout. This work is of interest for the representation and analysis of data from (1) protein databases, (2) mutagenesis results, or (3) various kinds of protein context-dependent annotations or data.