GPCR-SSFE: a comprehensive database of G-protein-coupled receptor template predictions and homology models

The path to the G protein-coupled receptor structural landscape: Major milestones and future directions

G protein-coupled receptors (GPCRs) play a crucial role in cell function by transducing signals from the extracellular environment to the inside of the cell. They mediate the effects of various stimuli, including hormones, neurotransmitters, ions, photons, food tastants and odorants, and are renowned drug targets. Advancements in structural biology techniques, including X-ray crystallography and cryo-electron microscopy (cryo-EM), have driven the elucidation of an increasing number of GPCR structures. These structures reveal novel features that shed light on receptor activation, dimerization and oligomerization, dichotomy between orthosteric and allosteric modulation, and the intricate interactions underlying signal transduction, providing insights into diverse ligand-binding modes and signalling pathways. However, a substantial portion of the GPCR repertoire and their activation states remain structurally unexplored. Future efforts should prioritize capturing the full structural diversity of GPCRs across multiple dimensions. To do so, the integration of structural biology with biophysical and computational techniques will be essential. We describe in this review the progress of nuclear magnetic resonance (NMR) to examine GPCR plasticity and conformational dynamics, of atomic force microscopy (AFM) to explore the spatial-temporal dynamics and kinetic aspects of GPCRs, and the recent breakthroughs in artificial intelligence for protein structure prediction to characterize the structures of the entire GPCRome. In summary, the journey through GPCR structural biology provided in this review illustrates how far we have come in decoding these essential proteins architecture and function. Looking ahead, integrating cutting-edge biophysics and computational tools offers a path to navigating the GPCR structural landscape, ultimately advancing GPCR-based applications.

Mind the Gap—Deciphering GPCR Pharmacology Using 3D Pharmacophores and Artificial Intelligence

G protein-coupled receptors (GPCRs) are amongst the most pharmaceutically relevant and well-studied protein targets, yet unanswered questions in the field leave significant gaps in our understanding of their nuanced structure and function. Three-dimensional pharmacophore models are powerful computational tools in in silico drug discovery, presenting myriad opportunities for the integration of GPCR structural biology and cheminformatics. This review highlights success stories in the application of 3D pharmacophore modeling to de novo drug design, the discovery of biased and allosteric ligands, scaffold hopping, QSAR analysis, hit-to-lead optimization, GPCR de-orphanization, mechanistic understanding of GPCR pharmacology and the elucidation of ligand–receptor interactions. Furthermore, advances in the incorporation of dynamics and machine learning are highlighted. The review will analyze challenges in the field of GPCR drug discovery, detailing how 3D pharmacophore modeling can be used to address them. Finally, we will present opportunities afforded by 3D pharmacophore modeling in the advancement of our understanding and targeting of GPCRs.

GPCR-SSFE 2.0-a fragment-based molecular modeling web tool for Class A G-protein coupled receptors

G-protein coupled receptors (GPCRs) are key players in signal transduction and therefore a large proportion of pharmaceutical drugs target these receptors. Structural data of GPCRs are sparse yet important for elucidating the molecular basis of GPCR-related diseases and for performing structure-based drug design. To ameliorate this problem, GPCR-SSFE 2.0 (http://www.ssfa-7tmr.de/ssfe2/), an intuitive web server dedicated to providing three-dimensional Class A GPCR homology models has been developed. The updated web server includes 27 inactive template structures and incorporates various new functionalities. Uniquely, it uses a fingerprint correlation scoring strategy for identifying the optimal templates, which we demonstrate captures structural features that sequence similarity alone is unable to do. Template selection is carried out separately for each helix, allowing both single-template models and fragment-based models to be built. Additionally, GPCR-SSFE 2.0 stores a comprehensive set of pre-calculated and downloadable homology models and also incorporates interactive loop modeling using the tool SL2, allowing knowledge-based input by the user to guide the selection process. For visual analysis, the NGL viewer is embedded into the result pages. Finally, blind-testing using two recently published structures shows that GPCR-SSFE 2.0 performs comparably or better than other state-of-the art GPCR modeling web servers.

Structural bioinformatics analysis of variants on GPCR function

G protein-coupled receptors (GPCRs) are key membrane-embedded receptor proteins, with critical roles in cellular signal transduction. In the era of precision medicine, understanding the role of natural variants on GPCR function is critical, especially from a pharmacogenomics viewpoint. Studies involved in mapping variants to GPCR structures are briefly reviewed here. The endocannabinoid system involving the central nervous system (CNS), the human cannabinoid receptor 1 (CB1), is an important drug target and its variability has implications for disease susceptibility and altered drug and pain response. We have carried out a computational study to map deleterious non-synonymous single nucleotide polymorphisms (nsSNPs) to CB1. CB1 mutations were computationally evaluated from neutral to deleterious, and the top twelve deleterious mutations, with structural information, were found to be either close to the ligand binding region or the G-protein binding site. We have mapped these to the active and inactive CB1 X-ray crystallographic structures to correlate variants with available phenotypic information. We have also carried out molecular dynamics simulations to functionally characterize four selected mutants.

GPCR Homology Model Generation for Lead Optimization

The vast increase of recently solved GPCR X-ray structures forms the basis for GPCR homology modeling to atomistic accuracy. Nowadays, homology models can be employed for GPCR-ligand optimization and have been reported as invaluable tools for drug design in the last few years. Elucidation of the complex GPCR pharmacology and the associated GPCR conformations made clear that different homology models have to be constructed for different activation states of the GPCRs. Therefore, templates have to be chosen accordingly to their sequence homology as well as to their activation state. The subsequent ligand placement is nontrivial, as some recent X-ray structures show very unusual ligand binding sites and solvent involvement, expanding the space of the putative ligand binding site from the generic retinal binding pocket to the whole receptor. In the present study, a workflow is presented starting from the selection of the target sequence, guiding through the GPCR modeling process, and finishing with ligand placement and pose validation.

Characterization of Ligand Binding to GPCRs Through Computational Methods

The recent increase in available G protein-coupled receptor structures now contributes decisively to the structure-based ligand design. In this context, computational approaches in combination with medicinal chemistry and pharmacology are extremely helpful. Here, we provide an update on our structure-based computational protocols, used to answer key questions related to GPCR-ligand binding. All combined, these techniques can shed light on ligand binding modes, determine the molecular basis of conformational selection, for agonists and antagonists, as well as of subtype selectivity. To illustrate each of these questions, we will consider examples from existing projects on three families of class A (rhodopsin-like) GPCRs: one small-molecule (nucleotide-like) family, i.e., the adenosine receptors, and two peptide-binding receptors: neuropeptide-Y and angiotensin II receptors. The successful application of the same computational protocols to investigate this diverse group of receptor families gives an idea of the general applicability of our methodology in the characterization of GPCR-ligand binding.

Thyroid hormone transport across L-type amino acid transporters: What can molecular modelling tell us?

Thyroid hormones (THs) and their derivatives require transmembrane transporters (TTs) to mediate their translocation across the cell membrane. Among these TTs, the L-type amino acid transporters (LAT) not only transport amino acids (AAs) but also certain THs and their derivatives. This review summarizes available knowledge concerning structure function patterns of the TH transport by LAT1 and LAT2. For example, LAT2 imports 3,3'-T₂ and T₃, but not rT₃ and T₄. In contrast to amino acids, THs are not at all exported by LAT2. Homology modelling of LAT1 and LAT2 is based on available crystal structures from the same superfamily the amino acid/polyamine/organocation transporter (APC). Molecular model guided mutagenesis has been used to predict substrate interaction sites. A common recognition feature for amino acid- and TH-derivatives has been suggested in an interior cavity of LAT1 and LAT2. Therein additional distinct molecular determinants that are responsible for the bidirectional AA transport but allowing only unidirectional import of particular THs have been confirmed for LAT2 by mutagenesis. Characterized substrate features that are needed for TH translocation and distinct LAT2 properties will be highlighted to understand the molecular import and export mechanisms of this transporter in more detail.

Structural determinants of a conserved enantiomer-selective carvone binding pocket in the human odorant receptor OR1A1

Chirality is a common phenomenon within odorants. Most pairs of enantiomers show only moderate differences in odor quality. One example for enantiomers that are easily discriminated by their odor quality is the carvones: humans significantly distinguish between the spearmint-like (R)-(-)-carvone and caraway-like (S)-(+)-carvone enantiomers. Moreover, for the (R)-(-)-carvone, an anosmia is observed in about 8% of the population, suggesting enantioselective odorant receptors (ORs). With only about 15% de-orphaned human ORs, the lack of OR crystal structures, and few comprehensive studies combining in silico and experimental approaches to elucidate structure-function relations of ORs, knowledge on cognate odorant/OR interactions is still sparse. An adjusted homology modeling approach considering OR-specific proline-caused conformations, odorant docking studies, single-nucleotide polymorphism (SNP) analysis, site-directed mutagenesis, and subsequent functional studies with recombinant ORs in a cell-based, real-time luminescence assay revealed 11 amino acid positions to constitute an enantioselective binding pocket necessary for a carvone function in human OR1A1 and murine Olfr43, respectively. Here, we identified enantioselective molecular determinants in both ORs that discriminate between minty and caraway odor. Comparison with orthologs from 36 mammalian species demonstrated a hominid-specific carvone binding pocket with about 100% conservation. Moreover, we identified loss-of-function SNPs associated with the carvone binding pocket of OR1A1. Given carvone enantiomer-specific receptor activation patterns including OR1A1, our data suggest OR1A1 as a candidate receptor for constituting a carvone enantioselective phenotype, which may help to explain mechanisms underlying a (R)-(-)-carvone-specific anosmia in humans.

Computational studies of G protein-coupled receptor complexes: Structure and dynamics

G protein-coupled receptors (GPCRs) are ubiquitously expressed transmembrane proteins associated with a wide range of diseases such as Alzheimer's, Parkinson, schizophrenia, and also implicated in in several abnormal heart conditions. As such, this family of receptors is regarded as excellent drug targets. However, due to the high number of intracellular signaling partners, these receptors have a complex interaction networks and it becomes challenging to modulate their function. Experimentally determined structures give detailed information on the salient structural properties of these signaling complexes but they are far away from providing mechanistic insights into the underlying process. This chapter presents some of the computational tools, namely molecular dynamics, molecular docking, and molecular modeling and related analyses methods that have been used to complement experimental findings.

Molecular features of the L-type amino acid transporter 2 determine different import and export profiles for thyroid hormones and amino acids

The L-type amino acid transporter 2 (LAT2) imports amino acids (AA) and also certain thyroid hormones (TH), e.g. 3,3'-T₂ and T₃, but not rT₃ and T₄. We utilized LAT2 mutations (Y130A, N133S, F242W) that increase 3,3'-T₂ import and focus here on import and export capacity for AA, T₄, T₃, BCH and derivatives thereof to delineate molecular features. Transport studies and analysis of competitive inhibition of import by radiolabelled TH and AA were performed in Xenopus laevis oocytes. Only Y130A, a pocket widening mutation, enabled import for T₄ and increased it for T₃. Mutant F242W showed increased 3,3'-T₂ import but no import rates for other TH derivatives. No export was detected for any TH by LAT2-wild type (WT). Mutations Y130A and N133S enabled only the export of 3,3'-T₂, while N133S also increased AA export. Thus, distinct molecular LAT2-features determine bidirectional AA transport but only an unidirectional 3,3'-T₂ and T₃ import.

Structural-Functional Features of the Thyrotropin Receptor: A Class A G-Protein-Coupled Receptor at Work

The thyroid-stimulating hormone receptor (TSHR) is a member of the glycoprotein hormone receptors, a sub-group of class A G-protein-coupled receptors (GPCRs). TSHR and its endogenous ligand thyrotropin (TSH) are of essential importance for growth and function of the thyroid gland and proper function of the TSH/TSHR system is pivotal for production and release of thyroid hormones. This receptor is also important with respect to pathophysiology, such as autoimmune (including ophthalmopathy) or non-autoimmune thyroid dysfunctions and cancer development. Pharmacological interventions directly targeting the TSHR should provide benefits to disease treatment compared to currently available therapies of dysfunctions associated with the TSHR or the thyroid gland. Upon TSHR activation, the molecular events conveying conformational changes from the extra- to the intracellular side of the cell across the membrane comprise reception, conversion, and amplification of the signal. These steps are highly dependent on structural features of this receptor and its intermolecular interaction partners, e.g., TSH, antibodies, small molecules, G-proteins, or arrestin. For better understanding of signal transduction, pathogenic mechanisms such as autoantibody action and mutational modifications or for developing new pharmacological strategies, it is essential to combine available structural data with functional information to generate homology models of the entire receptor. Although so far these insights are fragmental, in the past few decades essential contributions have been made to investigate in-depth the involved determinants, such as by structure determination via X-ray crystallography. This review summarizes available knowledge (as of December 2016) concerning the TSHR protein structure, associated functional aspects, and based on these insights we suggest several receptor complex models. Moreover, distinct TSHR properties will be highlighted in comparison to other class A GPCRs to understand the molecular activation mechanisms of this receptor comprehensively. Finally, limitations of current knowledge and lack of information are discussed highlighting the need for intensified efforts toward TSHR structure elucidation.

Docking and Molecular Dynamics of Steviol Glycoside-Human Bitter Receptor Interactions

Stevia is one of the sweeteners with the greatest consumer demand because of its natural origin and minimal calorie content. Steviol glycosides (SG) are the main active compounds present in the leaves of Stevia rebaudiana and are responsible for its sweetness. However, recent in vitro studies in HEK 293 cells revealed that SG specifically activate the hT2R4 and hT2R14 bitter taste receptors, triggering this mouth feel. The objective of this study was to characterize the interaction of SG with these two receptors at the molecular level. The results showed that SG have only one site for orthosteric binding to these receptors. The binding free energy (ΔG_binding) between the receptor and SG was negatively correlated with SG bitterness intensity, for both hT2R4 (r = -0.95) and hT2R14 (r = -0.89). We also determined, by steered molecular dynamics simulations, that the force required to extract stevioside from the receptors was greater than that required for rebaudioside A, in accordance with the ΔG values obtained by molecular docking. Finally, we identified the loop responsible for the activation by SG of both receptors. As a whole, these results contribute to a better understanding of the resulting off-flavor perception of these natural sweeteners in foods and beverages, allowing for better prediction, and control, of the resulting bitterness.

Identifying ligands at orphan GPCRs: current status using structure-based approaches

GPCRs are the most successful pharmaceutical targets in history. Nevertheless, the pharmacology of many GPCRs remains inaccessible as their endogenous or exogenous modulators have not been discovered. Tools that explore the physiological functions and pharmacological potential of these 'orphan' GPCRs, whether they are endogenous and/or surrogate ligands, are therefore of paramount importance. Rates of receptor deorphanization determined by traditional reverse pharmacology methods have slowed, indicating a need for the development of more sophisticated and efficient ligand screening approaches. Here, we discuss the use of structure-based ligand discovery approaches to identify small molecule modulators for exploring the function of orphan GPCRs. These studies have been buoyed by the growing number of GPCR crystal structures solved in the past decade, providing a broad range of template structures for homology modelling of orphans. This review discusses the methods used to establish the appropriate signalling assays to test orphan receptor activity and provides current examples of structure-based methods used to identify ligands of orphan GPCRs. Linked Articles This article is part of a themed section on Molecular Pharmacology of G Protein-Coupled Receptors. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v173.20/issuetoc.

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.

GPCR-ModSim: A comprehensive web based solution for modeling G-protein coupled receptors

GPCR-ModSim (http://open.gpcr-modsim.org) is a centralized and easy to use service dedicated to the structural modeling of G-protein Coupled Receptors (GPCRs). 3D molecular models can be generated from amino acid sequence by homology-modeling techniques, considering different receptor conformations. GPCR-ModSim includes a membrane insertion and molecular dynamics (MD) equilibration protocol, which can be used to refine the generated model or any GPCR structure uploaded to the server, including if desired non-protein elements such as orthosteric or allosteric ligands, structural waters or ions. We herein revise the main characteristics of GPCR-ModSim and present new functionalities. The templates used for homology modeling have been updated considering the latest structural data, with separate profile structural alignments built for inactive, partially-active and active groups of templates. We have also added the possibility to perform multiple-template homology modeling in a unique and flexible way. Finally, our new MD protocol considers a series of distance restraints derived from a recently identified conserved network of helical contacts, allowing for a smoother refinement of the generated models which is particularly advised when there is low homology to the available templates. GPCR- ModSim has been tested on the GPCR Dock 2013 competition with satisfactory results.

Structural modeling of G-protein coupled receptors: An overview on automatic web-servers

Despite the significant efforts and discoveries during the last few years in G protein-coupled receptor (GPCR) expression and crystallization, the receptors with known structures to date are limited only to a small fraction of human GPCRs. The lack of experimental three-dimensional structures of the receptors represents a strong limitation that hampers a deep understanding of their function. Computational techniques are thus a valid alternative strategy to model three-dimensional structures. Indeed, recent advances in the field, together with extraordinary developments in crystallography, in particular due to its ability to capture GPCRs in different activation states, have led to encouraging results in the generation of accurate models. This, prompted the community of modelers to render their methods publicly available through dedicated databases and web-servers. Here, we present an extensive overview on these services, focusing on their advantages, drawbacks and their role in successful applications. Future challenges in the field of GPCR modeling, such as the predictions of long loop regions and the modeling of receptor activation states are presented as well.

Structure-Based Sequence Alignment of the Transmembrane Domains of All Human GPCRs: Phylogenetic, Structural and Functional Implications

The understanding of G-protein coupled receptors (GPCRs) is undergoing a revolution due to increased information about their signaling and the experimental determination of structures for more than 25 receptors. The availability of at least one receptor structure for each of the GPCR classes, well separated in sequence space, enables an integrated superfamily-wide analysis to identify signatures involving the role of conserved residues, conserved contacts, and downstream signaling in the context of receptor structures. In this study, we align the transmembrane (TM) domains of all experimental GPCR structures to maximize the conserved inter-helical contacts. The resulting superfamily-wide GpcR Sequence-Structure (GRoSS) alignment of the TM domains for all human GPCR sequences is sufficient to generate a phylogenetic tree that correctly distinguishes all different GPCR classes, suggesting that the class-level differences in the GPCR superfamily are encoded at least partly in the TM domains. The inter-helical contacts conserved across all GPCR classes describe the evolutionarily conserved GPCR structural fold. The corresponding structural alignment of the inactive and active conformations, available for a few GPCRs, identifies activation hot-spot residues in the TM domains that get rewired upon activation. Many GPCR mutations, known to alter receptor signaling and cause disease, are located at these conserved contact and activation hot-spot residue positions. The GRoSS alignment places the chemosensory receptor subfamilies for bitter taste (TAS2R) and pheromones (Vomeronasal, VN1R) in the rhodopsin family, known to contain the chemosensory olfactory receptor subfamily. The GRoSS alignment also enables the quantification of the structural variability in the TM regions of experimental structures, useful for homology modeling and structure prediction of receptors. Furthermore, this alignment identifies structurally and functionally important residues in all human GPCRs. These residues can be used to make testable hypotheses about the structural basis of receptor function and about the molecular basis of disease-associated single nucleotide polymorphisms.

G-protein coupled receptors (GPCRs) are a large superfamily of integral membrane proteins that share a characteristic 7 transmembrane helix fold. They detect various molecules outside of the cell and signal their presence to the inside of the cell. At least half of the 800 human GPCRs are potential drug targets, so understanding their structure and function is critical. Experimental structures are now available for at least one receptor from each GPCR class. The structure of the 7 helix fold is highly conserved even for receptors with very low sequence similarity. We analyze the available experimental structures and compare the common inter-helical contacts. Our analysis leads to a unified sequence-structure alignment of the GPCR superfamily that can then be used as the starting point for structure prediction of all other GPCRs. A key result of our analysis is a list of conserved contact residues and activation “hot-spots” residues that are critical for GPCR folding and function. We propose that mutations and natural variants of amino acids at these locations in the GPCRs can dramatically influence their activation state and alter intracellular signaling. This provides hypotheses for the molecular mechanisms underlying disease causing mutants for any GPCR.

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.

Structural basis for constitutive activity and agonist-induced activation of the enteroendocrine fat sensor GPR119

BACKGROUND AND PURPOSE

GPR119 is a Gαs-coupled 7TM receptor activated by endogenous lipids such as oleoylethanolamide (OEA) and by the dietary triglyceride metabolite 2-monoacylglycerol. GPR119 stimulates enteroendocrine hormone and insulin secretion. But despite massive drug discovery efforts in the field, very little is known about the basic molecular pharmacology of GPR119.

EXPERIMENTAL APPROACH

GPR119 receptor signalling was studied in transfected cells. Mutational mapping (30 mutations in 23 positions) was performed on residues required for ligand-independent and agonist-induced GPR119 activation (AR231453 and OEA). Novel Rosetta-based receptor modelling was applied, using a composite template approach with segments from different X-ray structures and fully flexible ligand docking.

KEY RESULTS

The increased signalling induced by increasing the cell surface expression of GPR119 in the absence of agonist and the inhibitory effect of two synthetic inverse agonists demonstrated that GRP119 signals with a high degree of constitutive activity through the Gαs pathway. The mutational maps for AR231453 and OEA were very similar and, surprisingly, also similar to the mutational map for residues affecting the constitutive signalling - albeit with key differences. Surprisingly, almost all residues in extracellular loop-2b were important for the constitutive activity. The molecular modelling and docking demonstrated that AR231453 binds in a 'vertical' pocket in between mutational hits reaching from the centre of the receptor out to extracellular loop-2b.

CONCLUSIONS AND IMPLICATIONS

The high constitutive activity of GPR119 should be taken into account in future drug discovery efforts, which can now be guided by the detailed knowledge of the physiochemical properties of the extended ligand-binding pocket.

Analysis of Human Dopamine D3 Receptor Quaternary Structure

The dopamine D3 receptor is a class A, rhodopsin-like G protein-coupled receptor that can form dimers and/or higher order oligomers. However, the molecular basis for production of these complexes is not well defined. Using combinations of molecular modeling, site-directed mutagenesis, and homogenous time-resolved FRET, the interfaces that allow dopamine D3 receptor monomers to interact were defined and used to describe likely quaternary arrangements of the receptor. These were then compared with published crystal structures of dimeric β1-adrenoreceptor, μ-opioid, and CXCR4 receptors. The data indicate important contributions of residues from within each of transmembrane domains I, II, IV, V, VI, and VII as well as the intracellular helix VIII in the formation of D3-D3 receptor interfaces within homo-oligomers and are consistent with the D3 receptor adopting a β1-adrenoreceptor-like quaternary arrangement. Specifically, results suggest that D3 protomers can interact with each other via at least two distinct interfaces: the first one comprising residues from transmembrane domains I and II along with those from helix VIII and a second one involving transmembrane domains IV and V. Moreover, rather than existing only as distinct dimeric species, the results are consistent with the D3 receptor also assuming a quaternary structure in which two transmembrane domain I-II-helix VIII dimers interact to form a "rhombic" tetramer via an interface involving residues from transmembrane domains VI and VII. In addition, the results also provide insights into the potential contribution of molecules of cholesterol to the overall organization and potential stability of the D3 receptor and possibly other GPCR quaternary structures.

In silico optimization of pharmacokinetic properties and receptor binding affinity simultaneously: a 'parallel progression approach to drug design' applied to β-blockers

The present work exploits the potential of in silico approaches for minimizing attrition of leads in the later stages of drug development. We propose a theoretical approach, wherein 'parallel' information is generated to simultaneously optimize the pharmacokinetics (PK) and pharmacodynamics (PD) of lead candidates. β-blockers, though in use for many years, have suboptimal PKs; hence are an ideal test series for the 'parallel progression approach'. This approach utilizes molecular modeling tools viz. hologram quantitative structure activity relationships, homology modeling, docking, predictive metabolism, and toxicity models. Validated models have been developed for PK parameters such as volume of distribution (log Vd) and clearance (log Cl), which together influence the half-life (t1/2) of a drug. Simultaneously, models for PD in terms of inhibition constant pKi have been developed. Thus, PK and PD properties of β-blockers were concurrently analyzed and after iterative cycling, modifications were proposed that lead to compounds with optimized PK and PD. We report some of the resultant re-engineered β-blockers with improved half-lives and pKi values comparable with marketed β-blockers. These were further analyzed by the docking studies to evaluate their binding poses. Finally, metabolic and toxicological assessment of these molecules was done through in silico methods. The strategy proposed herein has potential universal applicability, and can be used in any drug discovery scenario; provided that the data used is consistent in terms of experimental conditions, endpoints, and methods employed. Thus the 'parallel progression approach' helps to simultaneously fine-tune various properties of the drug and would be an invaluable tool during the drug development process.

Expanding the horizons of G protein-coupled receptor structure-based ligand discovery and optimization using homology models

We show the key role of structural homology models in GPCR structure-based lead discovery and optimization, highlighting methodological aspects, recent progress and future directions.

In silico modeling of human α2C-adrenoreceptor interaction with filamin-2

Vascular smooth muscle α2C-adrenoceptors (α2C-ARs) mediate vasoconstriction of small blood vessels, especially arterioles. Studies of endogenous receptors in human arteriolar smooth muscle cells (referred to as microVSM) and transiently transfected receptors in heterologous HEK293 cells show that the α2C-ARs are perinuclear receptors that translocate to the cell surface under cellular stress and elicit a biological response. Recent studies in microVSM unraveled a crucial role of Rap1A-Rho-ROCK-F-actin pathways in receptor translocation, and identified protein-protein interaction of α2C-ARs with the actin binding protein filamin-2 as an essential step in the process. To better understand the molecular nature and specificity of this interaction, in this study, we constructed comparative models of human α2C-AR and human filamin-2 proteins. Finally, we performed in silico protein-protein docking to provide a structural platform for the investigation of human α2C-AR and filamin-2 interactions. We found that electrostatic interactions seem to play a key role in this complex formation which manifests in interactions between the C-terminal arginines of α2C-ARs (particularly R454 and R456) and negatively charged residues from filamin-2 region between residues 1979 and 2206. Phylogenetic and sequence analysis showed that these interactions have evolved in warm-blooded animals.

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.

Constitutive activity in gonadotropin receptors

Constitutively active mutants (CAMs) of gonadotropin receptors are, in general, rare conditions. Luteinizing hormone-choriogonadotropin receptor (LHCGR) CAMs provoke the dramatic phenotype of familial gonadotropin-independent isosexual male-limited precocious puberty, whereas in females, there is not yet any identified phenotype. Only one isolated follicle-stimulating hormone receptor (FSHR) CAM (Asp567Gly) has so far been detected in a single male patient, besides other FSHR weak CAMs linked to pregnancy-associated ovarian hyperstimulation syndrome or to impaired desensitization and internalization. Several animal models have been developed for studying enhanced gonadotropin action; in addition to unraveling valuable new information about the possible phenotypes of isolated FSHR and LHCGR CAMs in women, the information obtained from these mouse models has served multiple translational goals, including the development of new diagnostic and therapeutic targets as well as the prediction of phenotypes for mutations not yet identified in humans. Mutagenesis and computational studies have shed important information on the physiopathogenic mechanisms leading to constitutive activity of gonadotropin receptors; a common feature in these receptor CAMs is the release of stabilizing interhelical interactions between transmembrane domains (TMDs) 3 and 6 leading to an increase, with respect to the wild-type receptor, in the solvent accessibility at the cytosolic extension of TMDs 3, 5, and 6, which involves the highly conserved Glu/Asp-Arg-Tyr/Trp sequence. In this chapter, we summarize the structural features, functional consequences, and mechanisms that lead to constitutive activation of gonadotropin receptor CAMs and provide information on pharmacological approaches that might potentially modulate gonadotropin receptor CAM function.

Molecular dynamics simulations on the Tre1 G protein-coupled receptor: exploring the role of the arginine of the NRY motif in Tre1 structure

BACKGROUND

The arginine of the D/E/NRY motif in Rhodopsin family G protein-coupled receptors (GPCRs) is conserved in 96% of these proteins. In some GPCRs, this arginine in transmembrane 3 can form a salt bridge with an aspartic acid or glutamic acid in transmembrane 6. The Drosophila melanogaster GPCR Trapped in endoderm-1 (Tre1) is required for normal primordial germ cell migration. In a mutant form of the protein, Tre1sctt, eight amino acids RYILIACH are missing, resulting in a severe disruption of primordial germ cell development. The impact of the loss of these amino acids on Tre1 structure is unknown. Since the missing amino acids in Tre1sctt include the arginine that is part of the D/E/NRY motif in Tre1, molecular dynamics simulations were performed to explore the hypothesis that these amino acids are involved in salt bridge formation and help maintain Tre1 structure.

RESULTS

Structural predictions of wild type Tre1 (Tre1+) and Tre1sctt were subjected to over 250 ns of molecular dynamics simulations. The ability of the model systems to form a salt bridge between the arginine of the D/E/NRY motif and an aspartic acid residue in transmembrane 6 was analyzed. The results indicate that a stable salt bridge can form in the Tre1+ systems and a weak salt bridge or no salt bridge, using an alternative arginine, is likely in the Tre1sctt systems.

CONCLUSIONS

The weak salt bridge or lack of a salt bridge in the Tre1sctt systems could be one possible explanation for the disrupted function of Tre1sctt in primordial germ cell migration. These results provide a framework for studying the importance of the arginine of the D/E/NRY motif in the structure and function of other GPCRs that are involved in cell migration, such as CXCR4 in the mouse, zebrafish, and chicken.

Assessment and challenges of ligand docking into comparative models of G-protein coupled receptors

The rapidly increasing number of high-resolution X-ray structures of G-protein coupled receptors (GPCRs) creates a unique opportunity to employ comparative modeling and docking to provide valuable insight into the function and ligand binding determinants of novel receptors, to assist in virtual screening and to design and optimize drug candidates. However, low sequence identity between receptors, conformational flexibility, and chemical diversity of ligands present an enormous challenge to molecular modeling approaches. It is our hypothesis that rapid Monte-Carlo sampling of protein backbone and side-chain conformational space with Rosetta can be leveraged to meet this challenge. This study performs unbiased comparative modeling and docking methodologies using 14 distinct high-resolution GPCRs and proposes knowledge-based filtering methods for improvement of sampling performance and identification of correct ligand-receptor interactions. On average, top ranked receptor models built on template structures over 50% sequence identity are within 2.9 Å of the experimental structure, with an average root mean square deviation (RMSD) of 2.2 Å for the transmembrane region and 5 Å for the second extracellular loop. Furthermore, these models are consistently correlated with low Rosetta energy score. To predict their binding modes, ligand conformers of the 14 ligands co-crystalized with the GPCRs were docked against the top ranked comparative models. In contrast to the comparative models themselves, however, it remains difficult to unambiguously identify correct binding modes by score alone. On average, sampling performance was improved by 10³ fold over random using knowledge-based and energy-based filters. In assessing the applicability of experimental constraints, we found that sampling performance is increased by one order of magnitude for every 10 residues known to contact the ligand. Additionally, in the case of DOR, knowledge of a single specific ligand-protein contact improved sampling efficiency 7 fold. These findings offer specific guidelines which may lead to increased success in determining receptor-ligand complexes.

Current progress in Structure-Based Rational Drug Design marks a new mindset in drug discovery

The past decade has witnessed a paradigm shift in preclinical drug discovery with structure-based drug design (SBDD) making a comeback while high-throughput screening (HTS) methods have continued to generate disappointing results. There is a deficit of information between identified hits and the many criteria that must be fulfilled in parallel to convert them into preclinical candidates that have a real chance to become a drug. This gap can be bridged by investigating the interactions between the ligands and their receptors. Accurate calculations of the free energy of binding are still elusive; however progresses were made with respect to how one may deal with the versatile role of water. A corpus of knowledge combining X-ray structures, bioinformatics and molecular modeling techniques now allows drug designers to routinely produce receptor homology models of increasing quality. These models serve as a basis to establish and validate efficient rationales used to tailor and/or screen virtual libraries with enhanced chances of obtaining hits. Many case reports of successful SBDD show how synergy can be gained from the combined use of several techniques. The role of SBDD with respect to two different classes of widely investigated pharmaceutical targets: (a) protein kinases (PK) and (b) G-protein coupled receptors (GPCR) is discussed. Throughout these examples prototypical situations covering the current possibilities and limitations of SBDD are presented.

Towards improved quality of GPCR models by usage of multiple templates and profile-profile comparison

G-protein coupled receptors (GPCRs) are targets of nearly one third of the drugs at the current pharmaceutical market. Despite their importance in many cellular processes the crystal structures are available for less than 20 unique GPCRs of the Rhodopsin-like class. Fortunately, even though involved in different signaling cascades, this large group of membrane proteins has preserved a uniform structure comprising seven transmembrane helices that allows quite reliable comparative modeling. Nevertheless, low sequence similarity between the GPCR family members is still a serious obstacle not only in template selection but also in providing theoretical models of acceptable quality. An additional level of difficulty is the prediction of kinks and bulges in transmembrane helices. Usage of multiple templates and generation of alignments based on sequence profiles may increase the rate of success in difficult cases of comparative modeling in which the sequence similarity between GPCRs is exceptionally low. Here, we present GPCRM, a novel method for fast and accurate generation of GPCR models using averaging of multiple template structures and profile-profile comparison. In particular, GPCRM is the first GPCR structure predictor incorporating two distinct loop modeling techniques: Modeller and Rosetta together with the filtering of models based on the Z-coordinate. We tested our approach on all unique GPCR structures determined to date and report its performance in comparison with other computational methods targeting the Rhodopsin-like class. We also provide a database of precomputed GPCR models of the human receptors from that class.

AVAILABILITY

GPCRM SERVER AND DATABASE: http://gpcrm.biomodellab.eu.

G-protein coupled receptor 83 (GPR83) signaling determined by constitutive and zinc(II)-induced activity

The G-protein coupled receptor 83 (GPR83) is an orphan G-protein coupled receptor for which the natural ligand(s) and signaling pathway(s) remain to be identified. Previous studies suggest a role of GPR83 in the regulation of thermogenesis and the control of circulating adiponectin. The aim of this study was to gain insights into the molecular underpinnings underlying GPR83 signaling. In particular, we aimed to assess the underlying G-protein activated signaling pathway of GPR83 and how this pathway is affected by mutational activation and zinc(II) challenge. Finally, we assessed the capacity of GPR83 for homodimerization. Our results show for the first time that mouse (m) GPR83 has high basal Gq/11 activity without affecting Gi or Gs signaling. Furthermore, we found that, under physiological conditions, zinc(II) (but not calcium(II) and magnesium(II)) potently activates mGPR83, thus identifying zinc(II) as an endogenous molecule with agonistic capability to activate mGPR83. In line with the observation that zinc(II)-ions activate mGPR83, we identified a cluster of ion-binding sensitive amino acids (e.g. His145, His204, Cys207, Glu217) in an activation sensitive receptor region of mGPR83. The occurrence of a constitutive activating mutant and a zinc(II)-binding residue at the N-terminal part corroborate the importance of this region in mGPR83 signal regulation. Finally, our results indicate that mGPR83 forms homodimers, which extend the current knowledge and molecular facets of GPR83 signaling.

Identification of structural motifs critical for epstein-barr virus-induced molecule 2 function and homology modeling of the ligand docking site

Epstein-Barr virus-induced molecule 2 (EBI2) (also known as G-protein-coupled receptor 183) is a G-protein-coupled receptor (GPCR) that is best known for its role in B cell migration and localization. Our recent deorphanization effort led to the discovery of 7α,25-dihydroxycholesterol (7α,25-OHC) as the endogenous ligand for EBI2, which provides a tool for mechanistic studies of EBI2 function. Because EBI2 is the first GPCR known to bind and to be activated by an oxysterol, the goal of this study was to understand the molecular and structural bases for its ligand-dependent activation; this was achieved by identifying structural moieties in EBI2 or in 7α,25-OHC that might affect receptor-ligand interactions. By using a series of chemically related OHC analogs, we demonstrated that all three hydroxyl groups in 7α,25-OHC contributed to ligand-induced activation of the receptor. To determine the location and composition of the ligand binding domain in EBI2, we used a site-directed mutagenesis approach and generated mutant receptors with single amino acid substitutions at selected positions of interest. Biochemical and pharmacological profiling of these mutant receptors allowed for structure-function analyses and revealed critical motifs that likely interact with 7α,25-OHC. By using a hybrid β(2)-adrenergic receptor-C-X-C chemokine receptor type 4 structure as a template, we created a homology model for EBI2 and optimized the docking of 7α,25-OHC into the putative ligand binding site, so that the hydroxyl groups interact with residues Arg87, Asn114, and Glu183. This model of ligand docking yields important structural insight into the molecular mechanisms mediating EBI2 function and may facilitate future efforts to design novel therapeutic agents that target EBI2.

Binding sites in membrane proteins--diversity, druggability and prospects

The identification of novel drug targets is one of the major challenges in proteomics. Computational methods developed over the last decade have enhanced the process of drug design in both terms of time and quality. The main task is the design of selective compounds, which bind targets more specifically, dependent on the desired mode of action of the particular drug. This makes it necessary to create compounds, which either exhibit their functions on one single protein to exclude undesired cross-reactivity or to use the advantageous effect of less selective drugs that target numerous proteins and therefore exhibit their functions on whole protein classes. Main aspects in the assignment of interactions between ligands and putative targets involve the amino acid composition of the binding site, evolutionary conservation and similarity in sequence and structure of known targets. Similarities or differences within classified protein families can be the key to their function and give first hints to functional drug design. Hereby, binding site-based classification outnumbers sequence-based classifications since similar binding sites can also be found in more distant proteins. Membrane proteins are 'difficult targets', because of their special physicochemical characteristics and the general lack of structural information. Here, we describe recent advances in modeling methods dedicated to membrane proteins. Different descriptors of similarity between compounds and the similarity between binding sites are under development and elucidate important aspects like dynamics or entropy. The importance of computational drug design is undisputable. Nevertheless, the process of design is complicated by increasing complexity, which underlines the importance of accurate knowledge about the addressed target class(es) and particularly their binding sites. One main objective by considering named topics is to predict putative side effects and errant functions (off-target effects) of novel drugs, which requires a holistic (systems biology) view on drug-target-pathway relations. In the following, we give a brief summary about the recent discussion on drug-target interactions with emphasis on membrane proteins.