A common motif in G-protein-coupled seven transmembrane helix receptors

G protein-coupled receptors of class A harness the energy of membrane potential to increase their sensitivity and selectivity

The human genome contains about 700 genes of G protein-coupled receptors (GPCRs) of class A; these seven-helical membrane proteins are the targets of almost half of all known drugs. In the middle of the helix bundle, crystal structures reveal a highly conserved sodium-binding site, which is connected with the extracellular side by a water-filled tunnel. This binding site contains a sodium ion in those GPCRs that are crystallized in their inactive conformations but does not in those GPCRs that are trapped in agonist-bound active conformations. The escape route of the sodium ion upon the inactive-to-active transition and its very direction have until now remained obscure. Here, by modeling the available experimental data, we show that the sodium gradient over the cell membrane increases the sensitivity of GPCRs if their activation is thermodynamically coupled to the sodium ion translocation into the cytoplasm but decreases it if the sodium ion retreats into the extracellular space upon receptor activation. The model quantitatively describes the available data on both activation and suppression of distinct GPCRs by membrane voltage. The model also predicts selective amplification of the signal from (endogenous) agonists if only they, but not their (partial) analogs, induce sodium translocation. Comparative structure and sequence analyses of sodium-binding GPCRs indicate a key role for the conserved leucine residue in the second transmembrane helix (Leu2.46) in coupling sodium translocation to receptor activation. Hence, class A GPCRs appear to harness the energy of the transmembrane sodium potential to increase their sensitivity and selectivity.

Somatostatin receptors as a new active targeting sites for nanoparticles

The delivery of nanoparticles through receptor-mediated cell interactions has nowadays a major attention in the area of drug targeting applications. This specific kind of targeting is mediated by localized receptors impeded into the target site with subsequent drugs internalization. Hence, this type of interaction would diminish side effects and enhance drug delivery efficacy to the target site. Somatostatin receptors (SSTRs) are one type of G protein-coupled receptors, which could be active targeted for various purposes. There are five SSTRs types (SSTR1-5) which are localized at various organs in the body and spread into different tissues. SSTRs could be considered as a promising target to various nanoparticles which is facilitated when nanoparticles are modified through specific ligand or coating to allow better binding. This review discusses the exploration of SSTRs for active targeting of nanoparticles with certain emphasize on their interaction at the cellular level.

A Structural Framework for GPCR Chemogenomics: What's In a Residue Number?

The recent surge of crystal structures of G protein-coupled receptors (GPCRs), as well as comprehensive collections of sequence, structural, ligand bioactivity, and mutation data, has enabled the development of integrated chemogenomics workflows for this important target family. This chapter will focus on cross-family and cross-class studies of GPCRs that have pinpointed the need for, and the implementation of, a generic numbering scheme for referring to specific structural elements of GPCRs. Sequence- and structure-based numbering schemes for different receptor classes will be introduced and the remaining caveats will be discussed. The use of these numbering schemes has facilitated many chemogenomics studies such as consensus binding site definition, binding site comparison, ligand repurposing (e.g. for orphan receptors), sequence-based pharmacophore generation for homology modeling or virtual screening, and class-wide chemogenomics studies of GPCRs.

■ REVIEW : Olfactory Receptors: A Large Gene Family with Broad Affinities and Multiple Functions

Five years have passed since the first cloning and sequencing of a large family of G protein-coupled receptors from the olfactory epithelium. These receptors are believed to be the initial sites of odor transduction. Although direct experimental evidence concerning the properties of these molecules is still limited, a variety of studies has provided fascinating insights into a range of possible functions, extending beyond olfactory transduction to include functions as diverse as sperm navigation and neural and cardiac development. To serve these functions, the olfactory receptors appear to express interesting adaptations of the basic seven transmembrane domain structures found in the neurotransmitter members of the G protein-coupled receptor superfamily. We review here this evidence and propose hypotheses for the molecular mechanisms underlying several distinct functions for this receptor family as guides for future experimental testing. NEUROSCIENTIST 2:262-271, 1996

Bitter taste receptors: Novel insights into the biochemistry and pharmacology

Bitter taste receptors (T2Rs) belong to the super family of G protein-coupled receptors (GPCRs). There are 25 T2Rs expressed in humans, and these interact with a large and diverse group of bitter ligands. T2Rs are expressed in many extra-oral tissues and can perform diverse physiological roles. Structure-function studies led to the identification of similarities and dissimilarities between T2Rs and Class A GPCRs including amino acid conservation and novel motifs. However, the efficacy of most of the T2R ligands is not yet elucidated and the biochemical pharmacology of T2Rs is poorly understood. Recent studies on T2Rs characterized novel ligands including blockers for these receptors that include inverse agonist and antagonists. In this review we discuss the techniques used for elucidating bitter blockers, concept of ligand bias, generic amino acid numbering, the role of cholesterol, and conserved water molecules in the biochemistry and pharmacology of T2Rs.

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.

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.

The GPCR crystallography boom: providing an invaluable source of structural information and expanding the scope of homology modeling

G protein-coupled receptors (GPCRs) are integral membrane proteins of high pharmaceutical interest. Until relatively recently, their structures have been particularly elusive, and rhodopsin has been for many years the only member of the superfamily with experimentally elucidated structures. However, a number of recent technical and scientific advancements made the determination of GPCR structures more feasible, thus leading to the solution of the structures of several receptors. Besides providing direct structural information, these experimental GPCR structures also provide templates for the construction of GPCR models. In depth studies have been performed to probe the accuracy of these models, in particular with respect to the interactions with their ligands, and to assess their applicability the rational discovery of GPCR modulators. Given the current state of the art and the pace of the field, the future of GPCR structural studies is likely to be characterized by a landscape populated by an increasingly higher number of experimental and theoretical structures.

GPCRDB: an information system for G protein-coupled receptors

For the past 20 years, the GPCRDB (G protein-coupled receptors database; http://www.gpcr.org/7tm/) has been a ‘one-stop shop’ for G protein-coupled receptor (GPCR)-related data. The GPCRDB contains experimental data on sequences, ligand-binding constants, mutations and oligomers, as well as many different types of computationally derived data, such as multiple sequence alignments and homology models. The GPCRDB also provides visualization and analysis tools, plus a number of query systems. In the latest GPCRDB release, all multiple sequence alignments, and >65 000 homology models, have been significantly improved, thanks to a recent flurry of GPCR X-ray structure data. Tools were introduced to browse X-ray structures, compare binding sites, profile similar receptors and generate amino acid conservation statistics. Snake plots and helix box diagrams can now be custom coloured (e.g. by chemical properties or mutation data) and saved as figures. A series of sequence alignment visualization tools has been added, and sequence alignments can now be created for subsets of sequences and sequence positions, and alignment statistics can be produced for any of these subsets.

Modeling of mammalian olfactory receptors and docking of odorants

Olfactory receptors (ORs) belong to the superfamily of G protein-coupled receptors (GPCRs), the second largest class of genes after those related to immunity, and account for about 3 % of mammalian genomes. ORs are present in all multicellular organisms and represent more than half the GPCRs in mammalian species (e.g., the mouse OR repertoire contains >1,000 functional genes). ORs are mainly expressed in the olfactory epithelium where they detect odorant molecules, but they are also expressed in a number of other cells, such as sperm cells, although their functions in these cells remain mostly unknown. It has recently been reported that ORs are present in tumoral tissues where they are expressed at different levels than in healthy tissues. A specific OR is over-expressed in prostate cancer cells, and activation of this OR has been shown to inhibit the proliferation of these cells. Odorant stimulation of some of these receptors results in inhibition of cell proliferation. Even though their biological role has not yet been elucidated, these receptors might constitute new targets for diagnosis and therapeutics. It is important to understand the activation mechanism of these receptors at the molecular level, in particular to be able to predict which ligands are likely to activate a particular receptor ('deorphanization') or to design antagonists for a given receptor. In this review, we describe the in silico methodologies used to model the three-dimensional (3D) structure of ORs (in the more general framework of GPCR modeling) and to dock ligands into these 3D structures.

Molecular evolution of the neuropeptide S receptor

The neuropeptide S receptor (NPSR) is a recently deorphanized member of the G protein-coupled receptor (GPCR) superfamily and is activated by the neuropeptide S (NPS). NPSR and NPS are widely expressed in central nervous system and are known to have crucial roles in asthma pathogenesis, locomotor activity, wakefulness, anxiety and food intake. The NPS-NPSR system was previously thought to have first evolved in the tetrapods. Here we examine the origin and the molecular evolution of the NPSR using in-silico comparative analyses and document the molecular basis of divergence of the NPSR from its closest vertebrate paralogs. In this study, NPSR-like sequences have been identified in a hemichordate and a cephalochordate, suggesting an earlier emergence of a NPSR-like sequence in the metazoan lineage. Phylogenetic analyses revealed that the NPSR is most closely related to the invertebrate cardioacceleratory peptide receptor (CCAPR) and the group of vasopressin-like receptors. Gene structure features were congruent with the phylogenetic clustering and supported the orthology of NPSR to the invertebrate NPSR-like and CCAPR. A site-specific analysis between the vertebrate NPSR and the well studied paralogous vasopressin-like receptor subtypes revealed several putative amino acid sites that may account for the observed functional divergence between them. The data can facilitate experimental studies aiming at deciphering the common features as well as those related to ligand binding and signal transduction processes specific to the NPSR.

Drug design for ever, from hype to hope

In its first 25 years JCAMD has been disseminating a large number of techniques aimed at finding better medicines faster. These include genetic algorithms, COMFA, QSAR, structure based techniques, homology modelling, high throughput screening, combichem, and dozens more that were a hype in their time and that now are just a useful addition to the drug-designers toolbox. Despite massive efforts throughout academic and industrial drug design research departments, the number of FDA-approved new molecular entities per year stagnates, and the pharmaceutical industry is reorganising accordingly. The recent spate of industrial consolidations and the concomitant move towards outsourcing of research activities requires better integration of all activities along the chain from bench to bedside. The next 25 years will undoubtedly show a series of translational science activities that are aimed at a better communication between all parties involved, from quantum chemistry to bedside and from academia to industry. This will above all include understanding the underlying biological problem and optimal use of all available data.

STR-33, a novel G protein-coupled receptor that regulates locomotion and egg laying in Caenorhabditis elegans

Despite their predicted functional importance, most G protein-coupled receptors (GPCRs) in Caenorhabditis elegans have remained largely uncharacterized. Here, we focused on one GPCR, STR-33, encoded by the str-33 gene, which was discovered through a ligand-based screening procedure. To characterize STR-33 function, we performed UV-trimethylpsolaren mutagenesis and isolated an str-33-null mutant. The resulting mutant showed hypersinusoidal movement and a hyperactive egg-laying phenotype. Two types of egg laying-related mutations have been characterized: egg laying-deficient (Egl-d) and hyperactive egg laying (Egl-c). The defect responsible for the egg laying-deficient Egl-d phenotype is related to Gα(q) signaling, whereas that responsible for the opposite, hyperactive egg-laying Egl-c phenotype is related to Gα(o) signaling. We found that the hyperactive egg-laying defect of the str-33(ykp001) mutant is dependent on the G protein GOA-1/Gα(o). Endogenous acetylcholine suppressed egg laying in C. elegans via a Gα(o)-signaling pathway by inhibiting serotonin biosynthesis or release from the hermaphrodite-specific neuron. Consistent with this, in vivo expression of the serotonin biosynthetic enzyme, TPH-1, was up-regulated in the str-33(ykp001) mutant. Taken together, these results suggest that the GPCR, STR-33, may be one of the neurotransmitter receptors that regulates locomotion and egg laying in C. elegans.

Computational modeling toward understanding agonist binding on dopamine 3

The dopamine 3 (D3) receptor is a promising therapeutic target for the treatment of nervous system disorders, such as Parkinson's disease, and current research interests primarily focus on the discovery/design of potent D3 agonists. Herein, a well-designed computational protocol, which combines pharmacophore identification, homology modeling, molecular docking, and molecular dynamics (MD) simulations, was employed to understand the agonist binding on D3 aiming to provide insights into the development of novel potent D3 agonists. We (1) identified the chemical features required in effective D3 agonists by pharmacophore modeling based upon 18 known diverse D3 agonists; (2) constructed the three-dimensional (3D) structure of D3 based on homology modeling and the pharmacophore hypothesis; (3) identified the binding modes of the agonists to D3 by the correlation between the predicted binding free energies and the experimental values; and (4) investigated the induced fit of D3 upon agonist binding through MD simulations. The pharmacophore models of the D3 agonists and the 3D structure of D3 can be used for either ligand- or receptor-based drug design. Furthermore, the MD simulations further give the insight that the long and flexible EL2 acts as a "door" for agonist binding, and the "ionic lock" at the bottom of TM3 and TM6 is essential to transduce the activation signal.

GPCRDB: information system for G protein-coupled receptors

The GPCRDB is a Molecular Class-Specific Information System (MCSIS) that collects, combines, validates and disseminates large amounts of heterogeneous data on G protein-coupled receptors (GPCRs). The GPCRDB contains experimental data on sequences, ligand-binding constants, mutations and oligomers, as well as many different types of computationally derived data such as multiple sequence alignments and homology models. The GPCRDB provides access to the data via a number of different access methods. It offers visualization and analysis tools, and a number of query systems. The data is updated automatically on a monthly basis. The GPCRDB can be found online at http://www.gpcr.org/7tm/.

Homology modelling and spectroscopy, a never-ending love story

Homology modelling is normally the technique of choice when experimental structure data are not available but three-dimensional coordinates are needed, for example, to aid with detailed interpretation of results of spectroscopic studies. Herein, the state of the art of homology modelling will be described in the light of a series of recent developments, and an overview will be given of the problems and opportunities encountered in this field. The major topic, the accuracy and precision of homology models, will be discussed extensively due to its influence on the reliability of conclusions drawn from the combination of homology models and spectroscopic data. Three real-world examples will illustrate how both homology modelling and spectroscopy can be beneficial for (bio)medical research.

Augmented training of hidden Markov models to recognize remote homologs via simulated evolution

MOTIVATION

While profile hidden Markov models (HMMs) are successful and powerful methods to recognize homologous proteins, they can break down when homology becomes too distant due to lack of sufficient training data. We show that we can improve the performance of HMMs in this domain by using a simple simulated model of evolution to create an augmented training set.

RESULTS

We show, in two different remote protein homolog tasks, that HMMs whose training is augmented with simulated evolution outperform HMMs trained only on real data. We find that a mutation rate between 15 and 20% performs best for recognizing G-protein coupled receptor proteins in different classes, and for recognizing SCOP super-family proteins from different families.

On the applicability of GPCR homology models to computer-aided drug discovery: a comparison between in silico and crystal structures of the beta2-adrenergic receptor

The publication of the crystal structure of the beta2-adrenergic receptor (beta2-AR) proved that G protein-coupled receptors (GPCRs) share a structurally conserved rhodopsin-like 7TM core. Here, to probe to which extent realistic GPCR structures can be recreated through modeling, carazolol was docked at two rhodopsin-based homology models of the human beta 2-AR. The first featured a rhodopsin-like second extracellular loop, which interfered with ligand docking and with the orientation of several residues in the binding pocket. The second featured a second extracellular loop built completely de novo, which afforded a more accurate model of the binding pocket and a better docking of the ligand. Furthermore, incorporating available biochemical and computational data to the model by correcting the conformation of a single residue lining the binding pocket --Phe290(6.52)--, resulted in significantly improved docking poses. These results support the applicability of GPCR modeling to the design of site-directed mutagenesis experiments and to drug discovery.

The Angiotensin II AT1 Receptor Structure-Activity Correlations in the Light of Rhodopsin Structure

The most prevalent physiological effects of ANG II, the main product of the renin-angiotensin system, are mediated by the AT1 receptor, a rhodopsin-like AGPCR. Numerous studies of the cardiovascular effects of synthetic peptide analogs allowed a detailed mapping of ANG II's structural requirements for receptor binding and activation, which were complemented by site-directed mutagenesis studies on the AT1 receptor to investigate the role of its structure in ligand binding, signal transduction, phosphorylation, binding to arrestins, internalization, desensitization, tachyphylaxis, and other properties. The knowledge of the high-resolution structure of rhodopsin allowed homology modeling of the AT1 receptor. The models thus built and mutagenesis data indicate that physiological (agonist binding) or constitutive (mutated receptor) activation may involve different degrees of expansion of the receptor's central cavity. Residues in ANG II structure seem to control these conformational changes and to dictate the type of cytosolic event elicited during the activation. 1) Agonist aromatic residues (Phe8 and Tyr4) favor the coupling to G protein, and 2) absence of these residues can favor a mechanism leading directly to receptor internalization via phosphorylation by specific kinases of the receptor's COOH-terminal Ser and Thr residues, arrestin binding, and clathrin-dependent coated-pit vesicles. On the other hand, the NH2-terminal residues of the agonists ANG II and [Sar1]-ANG II were found to bind by two distinct modes to the AT1 receptor extracellular site flanked by the COOH-terminal segments of the EC-3 loop and the NH2-terminal domain. Since the [Sar1]-ligand is the most potent molecule to trigger tachyphylaxis in AT1 receptors, it was suggested that its corresponding binding mode might be associated with this special condition of receptors.

Modeling GPCRs

Many GPCR models have been built over the years for many different purposes, of which drug-design undoubtedly has been the most frequent one. The release of the structure of bovine rhodopsin in August 2000 enabled us to analyze models built before that period to learn things for the models we build today. We conclude that the GPCR modeling field is riddled with "common knowledge". Several characteristics of the bovine rhodopsin structure came as a big surprise, and had obviously not been predicted, which led to large errors in the models. Some of these surprises, however, could have been predicted if the modelers had more rigidly stuck to the rule that holds for all models, namely that a model should explain all experimental facts, and not just those facts that agree with the modeler's preconceptions.

A statistical score for assessing the quality of multiple sequence alignments

BACKGROUND

Multiple sequence alignment is the foundation of many important applications in bioinformatics that aim at detecting functionally important regions, predicting protein structures, building phylogenetic trees etc. Although the automatic construction of a multiple sequence alignment for a set of remotely related sequences cause a very challenging and error-prone task, many downstream analyses still rely heavily on the accuracy of the alignments.

RESULTS

To address the need for an objective evaluation framework, we introduce a statistical score that assesses the quality of a given multiple sequence alignment. The quality assessment is based on counting the number of significantly conserved positions in the alignment using importance sampling method in conjunction with statistical profile analysis framework. We first evaluate a novel objective function used in the alignment quality score for measuring the positional conservation. The results for the Src homology 2 (SH2) domain, Ras-like proteins, peptidase M13, subtilase and beta-lactamase families demonstrate that the score can distinguish sequence patterns with different degrees of conservation. Secondly, we evaluate the quality of the alignments produced by several widely used multiple sequence alignment programs using a novel alignment quality score and a commonly used sum of pairs method. According to these results, the Mafft strategy L-INS-i outperforms the other methods, although the difference between the Probcons, TCoffee and Muscle is mostly insignificant. The novel alignment quality score provides similar results than the sum of pairs method.

CONCLUSION

The results indicate that the proposed statistical score is useful in assessing the quality of multiple sequence alignments.

Validation of a histamine H3 receptor model through structure-activity relationships for classical H3 antagonists

Histamine H(3) receptor is a G protein-coupled receptor whose activation inhibits the synthesis and release of histamine and other neurotransmitters from nerve endings and is involved in the modulation of different central nervous system functions. H(3) antagonists have been proposed for their potential usefulness in diseases characterized by impaired neurotransmission and they have demonstrated beneficial effects on learning and food intake in animal models. In the present work, a 3D model of the rat histamine H(3) receptor, built by comparative modeling from the crystallographic coordinates of bovine rhodopsin, is presented with the discussion of its ability to predict the potency of known and new H(3) antagonists. A putative binding site for classical, imidazole-derived H(3) antagonists was identified by molecular docking. Comparison with a known pharmacophore model and the binding affinity of a new rigid H(3) antagonist (compound 1, pK(i)=8.02) allowed the characterization of a binding scheme which could also account for the different affinities observed in a recently reported series of potent H(3) antagonists, characterized by a 2-aminobenzimidazole moiety. Molecular dynamics simulations were employed to assess the stability and reliability of the proposed binding mode. Two new conformationally constrained benzimidazole derivatives were prepared and their binding affinity was tested on rat brain membranes; compound 9, designed to reproduce the conformation of a known potent H(3) antagonist, showed higher potency than compound 8, as expected from the binding scheme hypothesized.

The study of G-protein coupled receptor oligomerization with computational modeling and bioinformatics

To achieve a structural context for the analysis of G-protein coupled receptor (GPCR) oligomers, molecular modeling must be used to predict the corresponding interaction interfaces. The task is complicated by the paucity of detailed structural data at atomic resolution, and the large number of possible modes in which the bundles of seven transmembrane (TM) segments of the interacting GPCR monomers can be packed together into dimers and/or higher-order oligomers. Approaches and tools offered by bioinformatics can be used to reduce the complexity of this task and, combined with computational modeling, can serve to yield testable predictions for the structural properties of oligomers. Most of the bioinformatics methods take advantage of the evolutionary relation that exists among GPCRs, as expressed in their sequences and measurable in the common elements of their structural and functional features. These common elements are responsible for the presence of detectable patterns of motifs and correlated mutations evident from the alignment of the sequences of these complex biological systems. The decoding of these patterns in terms of structural and functional determinants can provide indications about the most likely interfaces of dimerization/oligomerization of GPCRs. We review here the main approaches from bioinformatics, enhanced by computational molecular modeling, that have been used to predict likely interfaces of dimerization/oligomerization of GPCRs, and compare results from their application to rhodopsin-like GPCRs. A compilation of the most frequently predicted GPCR oligomerization interfaces points to specific regions of TMs 4-6.

High-throughput modeling of human G-protein coupled receptors: amino acid sequence alignment, three-dimensional model building, and receptor library screening

The current study describes the development of a computer package (GPCRmod) aimed at the high-throughput modeling of the therapeutically important family of human G-protein coupled receptors (GPCRs). GPCRmod first proposes a reliable alignment of the seven transmembrane domains (7 TMs) of most druggable human GPCRs based on pattern/motif recognition for each of the 7 TMs that are considered independently. It then converts the alignment into knowledge-based three-dimensional (3-D) models starting from a set of 3-D backbone templates and two separate rotamer libraries for side chain positioning. The 7 TMs of 277 human GPCRs have been accurately aligned, unambiguously clustered in three different classes (rhodopsin-like, secretin-like, metabotropic glutamate-like), and converted into high-quality 3-D models at a remarkable throughput (ca. 3s/model). A 3-D GPCR target library of 277 receptors has consequently been setup. Its utility for "in silico" inverse screening purpose has been demonstrated by recovering among top scorers the receptor of a selective GPCR antagonist as well as the receptors of a promiscuous antagonist. The current GPCR target library thus constitutes a 3-D database of choice to address as soon as possible the "virtual selectivity" profile of any GPCR antagonist or inverse agonist in an early hit optimization process.

Toward the active conformations of rhodopsin and the beta2-adrenergic receptor

Using sets of experimental distance restraints, which characterize active or inactive receptor conformations, and the X-ray crystal structure of the inactive form of bovine rhodopsin as a starting point, we have constructed models of both the active and inactive forms of rhodopsin and the beta2-adrenergic G-protein coupled receptors (GPCRs). The distance restraints were obtained from published data for site-directed crosslinking, engineered zinc binding, site-directed spin-labeling, IR spectroscopy, and cysteine accessibility studies conducted on class A GPCRs. Molecular dynamics simulations in the presence of either "active" or "inactive" restraints were used to generate two distinguishable receptor models. The process for generating the inactive and active models was validated by the hit rates, yields, and enrichment factors determined for the selection of antagonists in the inactive model and for the selection of agonists in the active model from a set of nonadrenergic GPCR drug-like ligands in a virtual screen using ligand docking software. The simulation results provide new insights into the relationships observed between selected biochemical data, the crystal structure of rhodopsin, and the structural rearrangements that occur during activation.

Molecular mechanisms of ligand binding, signaling, and regulation within the superfamily of G-protein-coupled receptors: molecular modeling and mutagenesis approaches to receptor structure and function

The superfamily of G-protein-coupled receptors (GPCRs) could be subclassified into 7 families (A, B, large N-terminal family B-7 transmembrane helix, C, Frizzled/Smoothened, taste 2, and vomeronasal 1 receptors) among mammalian species. Cloning and functional studies of GPCRs have revealed that the superfamily of GPCRs comprises receptors for chemically diverse native ligands including (1) endogenous compounds like amines, peptides, and Wnt proteins (i.e., secreted proteins activating Frizzled receptors); (2) endogenous cell surface adhesion molecules; and (3) photons and exogenous compounds like odorants. The combined use of site-directed mutagenesis and molecular modeling approaches have provided detailed insight into molecular mechanisms of ligand binding, receptor folding, receptor activation, G-protein coupling, and regulation of GPCRs. The vast majority of family A, B, C, vomeronasal 1, and taste 2 receptors are able to transduce signals into cells through G-protein coupling. However, G-protein-independent signaling mechanisms have also been reported for many GPCRs. Specific interaction motifs in the intracellular parts of these receptors allow them to interact with scaffold proteins. Protein engineering techniques have provided information on molecular mechanisms of GPCR-accessory protein, GPCR-GPCR, and GPCR-scaffold protein interactions. Site-directed mutagenesis and molecular dynamics simulations have revealed that the inactive state conformations are stabilized by specific interhelical and intrahelical salt bridge interactions and hydrophobic-type interactions. Constitutively activating mutations or agonist binding disrupts such constraining interactions leading to receptor conformations that associates with and activate G-proteins.

Mutagenesis of the AT1 receptor reveals different binding modes of angiotensin II and [Sar1]-angiotensin II

Homology modeling of the structure of the AT1 receptor, based on the high resolution rhodopsin crystal structure, indicated that it is unlikely that the binding of AngII to AT1 involves simultaneously all the receptor's residues reported in the literature to participate in this process. Site-directed mutagenesis using Ala substitution of charged residues Lys20, Arg23, Glu91 and Arg93 was performed to evaluate the participation of their side-chains in ligand binding and in triggering the cell's response. A comparative analysis by competition binding and functional assays using angiotensin II and the analog [Sar1]-angiotensin II suggests an important role for Arg23 of AT1 receptor in binding of the natural agonist. It is discussed whether some receptor's residues participate directly in the binding with AngII or whether they are part of a regulatory site.

Statistical sequence analyses of G-protein-coupled receptors: Structural and functional characteristics viewed with periodicities of entropy, hydrophobicity, and volume

G-protein-coupled receptors (GPCRs) play a crucial role in signal transduction and receive a wide variety of ligands. GPCRs are a major target in drug design, as nearly 50% of all contemporary medicines act on GPCRs. GPCRs are membrane proteins possessing a common structural feature, seven transmembrane helices. In order to design an effective drug to act on a GPCR, knowledge of the three-dimensional (3D) structure of the target GPCR is indispensable. However, as GPCRs are membrane bound, their 3D structures are difficult to obtain. Thus we conducted statistical sequence analyses to find information about 3D structure and ligand binding using the receptors' primary sequences. We present statistical sequence analyses of 270 human GPCRs with regard to entropy (Shannon entropy in sequence alignment), hydrophobicity and volume, which are associated with the alpha-helical periodicity of the accessibility to the surrounding lipid. We found periodicity such that the phase changes once in the middle of each transmembrane region, both in the entropy plot and in the hydrophobicity plot. The phase shift in the entropy plot reflects the variety of ligands and the generality of the mechanism of signal transduction. The two periodic regions in the hydrophobicity plot indicate the regions facing the hydrophobic lipid chain and the polar phospholipid headgroup. We also found a simple periodicity in the plot of volume deviation, which suggests conservation of the stable structural packing among the transmembrane helices.

Modulation of ligand selectivity associated with activation of the transmembrane region of the human follitropin receptor

Recently, three naturally occurring mutations in the serpentine region of the FSH receptor (FSHr) (D567N and T449I/A) have been identified in three families with spontaneous ovarian hyperstimulation syndrome (OHSS). All mutant receptors displayed abnormally high sensitivity to human chorionic gonadotropin and, in addition, D567N and T449A displayed concomitant increase in sensitivity to TSH and detectable constitutive activity. In the present study, we have used a combination of site-directed mutagenesis experiments and molecular modeling to explore the mechanisms responsible for the phenotype of the three OHSS FSHr mutants. Our results suggest that all mutations lead to weakening of interhelical locks between transmembrane helix (TM)-VI and TM-III, or TM-VI and TM-VII, which contributes to maintaining the receptor in the inactive state. They also indicate that broadening of the functional specificity of the mutant FSHr constructs is correlated to their increase in constitutive activity. This relation between basal activity and functional specificity is a characteristic of the FSHr, which is not shared by the other glycoprotein hormone receptors. It leads to the interesting suggestion that different pathways have been followed during primate evolution to avoid promiscuous stimulation of the TSHr and FSHr by human chorionic gonadotropin. In the hFSHr, specificity would be exerted both by the ectodomain and the serpentine portion.

Heavier-than-air flying machines are impossible

Many G protein-coupled receptor (GPCR) models have been built over the years. The release of the structure of bovine rhodopsin in August 2000 enabled us to analyze models built before that period to learn more about the models we build today. We conclude that the GPCR modelling field is riddled with 'common knowledge' similar to Lord Kelvin's remark in 1895 that "heavier-than-air flying machines are impossible", and we summarize what we think are the (im)possibilities of modelling GPCRs using the coordinates of bovine rhodopsin as a template. Associated WWW pages: www.gpcr.org/articles/2003_mod

Identification of functionally conserved residues with the use of entropy-variability plots

We introduce sequence entropy-variability plots as a method of analyzing families of protein sequences, and demonstrate this for three well-known sequence families: globins, ras-like proteins, and serine-proteases. The location of an aligned residue position in the entropy-variability plot correlates with structural characteristics, and with known facts about the roles of individual amino acids in the function of these proteins. The large numbers of known sequences in these families allowed us to introduce new filtering methods for variability patterns. The results are discussed in terms of a simple evolutionary model for functional proteins.

Sequence analysis reveals how G protein-coupled receptors transduce the signal to the G protein

Sequence entropy-variability plots based on alignments of very large numbers of sequences-can indicate the location in proteins of the main active site and modulator sites. In the previous article in this issue, we applied this observation to a series of well-studied proteins and concluded that it was possible to detect most of the residues with a known functional role. Here, we apply the method to rhodopsin-like G protein-coupled receptors. Our conclusion is that G protein binding is the main evolutionary constraint on these receptors, and that other ligands, such as agonists, act as modulators. The activation of the receptors can be described as a simple, two-step process, and the residues involved in signal transduction can be identified.

A perspective on enzyme catalysis

The seminal hypotheses proposed over the years for enzymatic catalysis are scrutinized. The historical record is explored from both biochemical and theoretical perspectives. Particular attention is given to the impact of molecular motions within the protein on the enzyme's catalytic properties. A case study for the enzyme dihydrofolate reductase provides evidence for coupled networks of predominantly conserved residues that influence the protein structure and motion. Such coupled networks have important implications for the origin and evolution of enzymes, as well as for protein engineering.

Structural models for dimerization of G-protein coupled receptors: the opioid receptor homodimers

Among the most exciting functional features of G-protein coupled receptors (GPCRs) that are coming into focus lately are those relating to the role and structural characteristics of their oligomerization (mostly homo- and heterodimers). The structural underpinnings of these novel functional insights are still not clear, as current experimental techniques have not yet succeeded in identifying the dimerization interfaces between GPCR monomers. Two computational approaches have recently been designed in our lab to provide reasonable three-dimensional (3D) molecular models of the transmembrane (TM) regions of GPCR dimers based on a combination of the structural information of receptor monomers and analyses of correlated mutations in receptor families. The modeling of GPCR heterodimers has been described recently. We present here a related approach for modeling of GPCR homodimers that identifies the interfaces in the most likely configurations of the complexes. The approach is illustrated for the three cloned opioid receptor subtypes (OPRD, OPRM, and OPRK).

Prediction of heterodimerization interfaces of G-protein coupled receptors with a new subtractive correlated mutation method

Recent studies employing differential epitope tagging, selective immunoprecipitation of receptor complexes and fluorescence or bioluminescence resonance energy transfer techniques provide direct evidence for heterodimerization between both closely and distantly related members of the G-protein coupled receptor (GPCR) family. Since heterodimerization appears to play a role in modulating agonist affinity, efficacy and/or trafficking properties, the molecular models of GPCRs required to understand receptor function must consider these oligomerization hypotheses. To advance knowledge in this field, we present here a computational approach based on correlated mutation analysis and the structural information contained in three-dimensional molecular models of the transmembrane regions of GPCRs built using the rhodopsin crystal structure as a template. The new subtractive correlated mutation method reveals likely heterodimerization interfaces amongst the different alternatives for the positioning of two tightly packed bundles of seven transmembrane domains next to each other in contact heterodimers of GPCRs. Predictions are applied to GPCRs in the class of opioid receptors. However, in the absence of a known structure of any GPCR dimer, the features of the method and predictions are also illustrated and analyzed for a dimeric complex of known structure.

Orphan G protein-coupled receptors and beyond

Since the first discovery of mammalian receptors for adrenaline (beta(2)) and acetylcholine (M(1)) in 1986, many G protein-coupled receptors for known ligands have been cloned by protein purification, PCR (polymerase chain reaction) and low stringency hybridization, and they have been identified by expression cloning techniques. Now we are almost out of the known ligands pool. However, through the achievement of the Human Genome Project, numerous orphan receptors (whose natural ligands are not yet found) are also available for analysis. In this review, I would like to review recent achievements in the discovery of natural ligands, to describe useful orphan receptor strategies, and to predict the future of reverse pharmacology.

The serotonin binding site of human and murine 5-HT2B receptors: molecular modeling and site-directed mutagenesis

Bacteriorhodopsin and rhodopsin crystal structures were used as templates to build structural models of the mouse and human serotonin (5-HT)-2B receptors (5-HT(2B)Rs). Serotonin was docked to the receptors, and the amino acids predicted to participate to its binding were subjected to mutagenesis. 5-HT binding affinity and 5-HT-induced inositol triphosphate production were measured in LMTK(-) cells transfected with either wild-type or mutated receptor genes. According to these measurements, the bacteriorhodopsin-based models of the 5-HT(2B)Rs appear more confident than the rhodopsin-based ones. Residues belonging to the transmembrane domains 3 and 6, i.e. Asp(3.32), Ser(3.36), Phe(6.52), and Asn(6.55), make direct contacts with 5-HT. In addition, Trp(3.28), Phe(3.35), Phe(6.52), and Phe(7.38) form an aromatic box surrounding 5-HT. The specificity of human and mouse 5-HT(2B)Rs may be reflected by different rearrangements of the aromatic network upon 5-HT binding. Two amino acids close to Pro(5.50) in the human transmembrane domain 5 sequence were permuted to introduce a "mouse-like" sequence. This change was enough to confer the human 5-HT(2B)R properties similar to those of the mouse. Taken together, the computed models and the site-directed mutagenesis experiments give a structural explanation to (i) the different 5-HT pK(D) values measured with the human and mouse 5-HT(2B)Rs (7.9 and 5.8, respectively) and (ii) the specificity of 5-HT binding to 5-HT(2B)Rs as compared with other serotonergic G-protein coupled receptors.

Molecular modelling and site-directed mutagenesis of human GALR1 galanin receptor defines determinants of receptor subtype specificity

Human galanin is a 30 amino acid neuropeptide that elicits a range of biological activities by interaction with G protein-coupled receptors. We have generated a model of the human GALR1 galanin receptor subtype (hGALR1) based on the alpha carbon maps of frog rhodopsin and investigated the significance of potential contact residues suggested by the model using site-directed mutagenesis. Mutation of Phe186 within the second extracellular loop to Ala resulted in a 6-fold decrease in affinity for galanin, representing a change in free energy consistent with hydrophobic interaction. Our model suggests interaction between Phe186 of hGALR1 and Ala7 or Leu11 of galanin. Receptor subtype specificity was investigated by replacement of residues in hGALR1 with the corresponding residues in hGALR2 and use of the hGALR2-specific ligands hGalanin(2-30) and [D-Trp2]hGalanin(1-30). The His267Ile mutant receptor exhibited a pharmacological profile corresponding to that of hGALR1, suggesting that His267 is not involved in a receptor-ligand interaction. The mutation Phe115Ala resulted in a decreased binding affinity for hGalanin and for hGALR2-specific analogues, indicating Phe115 to be of structural importance to the ligand binding pocket of hGALR1 but not involved in direct ligand interaction. Analysis of Glu271Trp suggested that Glu271 of hGALR1 interacts with the N-terminus of galanin and that the Trp residue in the corresponding position in hGALR2 is involved in receptor subtype specificity of binding. Our model supports previous reports of Phe282 of hGALR1 interacting with Trp2 of galanin and His264 of hGALR1 interacting with Tyr9 of galanin.

Exploring the recognized bio-mimicry materials for gas sensing

This study was undertaken to synthesize peptides that are partially similar to the binding sites of human olfactory receptor protein. First, a putative 3-D model structure of human olfactory receptor protein (P30953) was modeled using a molecular simulation method. The computer docking simulation was then performed to determine the most plausible binding sites between the model structure and target gases, trimethylamine, ammonia, acetic acid, and o-xylene. According to the simulation result, a series of polypeptide sequences, horp61 for TMA, horp103 for o-xylene, horp109 for ammonia, and horp193 for acetic acid as recognized molecules were designed for gas sensing purposes. Preparing these peptides as corresponding gas sensing probes, the results showed a high relative sensitivity response of 6.7 for TMA (probe horp61), 5.1 for o-xylene (probe horp103), 11 for ammonia (probe horp109), and 28 for acetic acid (probe horp193), respectively. These results indicate that peptide mimicking of binding domain on olfactory receptor opens a new window and offers a novel strategy for the further development of recognized materials for gas sensing.

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

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