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

Class A and C GPCR Dimers in Neurodegenerative Diseases

Neurodegenerative diseases affect over 30 million people worldwide with an ascending trend. Most individuals suffering from these irreversible brain damages belong to the elderly population, with onset between 50 and 60 years. Although the pathophysiology of such diseases is partially known, it remains unclear upon which point a disease turns degenerative. Moreover, current therapeutics can treat some of the symptoms but often have severe side effects and become less effective in long-term treatment. For many neurodegenerative diseases, the involvement of G proteincoupled receptors (GPCRs), which are key players of neuronal transmission and plasticity, has become clearer and holds great promise in elucidating their biological mechanism. With this review, we introduce and summarize class A and class C GPCRs, known to form heterodimers or oligomers to increase their signalling repertoire. Additionally, the examples discussed here were shown to display relevant alterations in brain signalling and had already been associated with the pathophysiology of certain neurodegenerative diseases. Lastly, we classified the heterodimers into two categories of crosstalk, positive or negative, for which there is known evidence.

Computational and experimental approaches to probe GPCR activation and signaling

G protein-coupled receptors (GPCRs) regulate different physiological functions, e.g., sensation, growth, digestion, reproductivity, nervous and immune systems response, and many others. In eukaryotes, they are also responsible for intercellular communication in response to pathogens. The major primary messengers binding to these cell-surface receptors constitute small-molecule or peptide hormones and neurotransmitters, nucleotides, lipids as well as small proteins. The simplicity of the way how GPCR signaling can be regulated by their endogenous agonists prompted the usage of GPCRs as major drug targets in modern pharmacology. Drugs targeting GPCRs inhibit pathological processes at the very beginning. This enables to significantly reduce the occurrence of morphological changes caused by diseases. Until recently, X-ray crystallography was the method of the first choice to obtain high-resolution structural information about GPCRs. Following X-ray crystallography, cryo-EM gained attention in GPCR studies as a quick and low-cost alternative. FRET microscopy is also widely used for GPCRs in the analysis of protein-protein interactions (PPIs) in intact cells as well as for screening purposes. Regarding computational methods, molecular dynamics (MD) for many years has proven its usefulness in studying the GPCR activation. MODELLER and Rosetta were widely used to generate preliminary homology models of GPCRs for MD simulation systems. Apart from the conventional all-atom approach with explicitly defined solvent, also other techniques have been applied to GPCRs, e.g., MARTINI or hybrid methods involving the coarse-grained representation, less demanding regarding computational resources, and thus offering much larger simulation timescales.

The Many Faces of G Protein-Coupled Receptor 143, an Atypical Intracellular Receptor

GPCRs transform extracellular stimuli into a physiological response by activating an intracellular signaling cascade initiated via binding to G proteins. Orphan G protein-coupled receptors (GPCRs) hold the potential to pave the way for development of new, innovative therapeutic strategies. In this review we will introduce G protein-coupled receptor 143 (GPR143), an enigmatic receptor in terms of classification within the GPCR superfamily and localization. GPR143 has not been assigned to any of the GPCR families due to the lack of common structural motifs. Hence we will describe the most important motifs of classes A and B and compare them to the protein sequence of GPR143. While a precise function for the receptor has yet to be determined, the protein is expressed abundantly in pigment producing cells. Many GPR143 mutations cause X-linked Ocular Albinism Type 1 (OA1, Nettleship-Falls OA), which results in hypopigmentation of the eyes and loss of visual acuity due to disrupted visual system development and function. In pigment cells of the skin, loss of functional GPR143 results in abnormally large melanosomes (organelles in which pigment is produced). Studies have shown that the receptor is localized internally, including at the melanosomal membrane, where it may function to regulate melanosome size and/or facilitate protein trafficking to the melanosome through the endolysosomal system. Numerous additional roles have been proposed for GPR143 in determining cancer predisposition, regulation of blood pressure, development of macular degeneration and signaling in the brain, which we will briefly describe as well as potential ligands that have been identified. Furthermore, GPR143 is a promiscuous receptor that has been shown to interact with multiple other melanosomal proteins and GPCRs, which strongly suggests that this orphan receptor is likely involved in many different physiological actions.

Signal Transduction by VIP and PACAP Receptors

Homeostasis of the human immune system is regulated by many cellular components, including two neuropeptides, VIP and PACAP, primary stimuli for three class B G protein-coupled receptors, VPAC1, VPAC2, and PAC1. Vasoactive intestinal peptide (VIP) and pituitary adenylate cyclase-activating polypeptide (PACAP) regulate intestinal motility and secretion and influence the functioning of the endocrine and immune systems. Inhibition of VIP and PACAP receptors is an emerging concept for new pharmacotherapies for chronic inflammation and cancer, while activation of their receptors provides neuroprotection. A small number of known active compounds for these receptors still impose limitations on their use in therapeutics. Recent cryo-EM structures of VPAC1 and PAC1 receptors in their agonist-bound active state have provided insights regarding their mechanism of activation. Here, we describe major molecular switches of VPAC1, VPAC2, and PAC1 that may act as triggers for receptor activation and compare them with similar non-covalent interactions changing upon activation that were observed for other GPCRs. Interhelical interactions in VIP and PACAP receptors that are important for agonist binding and/or activation provide a molecular basis for the design of novel selective drugs demonstrating anti-inflammatory, anti-cancer, and neuroprotective effects. The impact of genetic variants of VIP, PACAP, and their receptors on signalling mediated by endogenous agonists is also described. This sequence diversity resulting from gene splicing has a significant impact on agonist selectivity and potency as well as on the signalling properties of VIP and PACAP receptors.

PanGPCR: predictions for multiple targets, repurposing and side effects

SUMMARY

Drug discovery targeting G protein-coupled receptors (GPCRs), the largest known class of therapeutic targets, is challenging. To facilitate the rapid discovery and development of GPCR drugs, we built a system, PanGPCR, to predict multiple potential GPCR targets and their expression locations in the tissues, side effects and possible repurposing of GPCR drugs. With PanGPCR, the compound of interest is docked to a library of 36 experimentally determined crystal structures comprising of 46 docking sites for human GPCRs, and a ranked list is generated from the docking studies to assess all GPCRs and their binding affinities. Users can determine a given compound's GPCR targets and its repurposing potential accordingly. Moreover, potential side effects collected from the SIDER (Side-Effect Resource) database and mapped to 45 tissues and organs are provided by linking predicted off-targets and their expressed sequence tag profiles. With PanGPCR, multiple targets, repurposing potential and side effects can be determined by simply uploading a small ligand.

AVAILABILITY AND IMPLEMENTATION

PanGPCR is freely accessible at https://gpcrpanel.cmdm.tw/index.html.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Homology Modeling Using GPCRM Web Service

Homology modeling methods are commonly used for quick and precise construction of a desired protein or its mutant using protein templates, which were determined by crystallography, cryo-EM, or NMR. Due to the increasing number of such structures, the obtained models are precise even in the case of small similarity between sequences of template and modeled proteins. The reason for that is a high evolutionary conservation in the structure regions responsible for keeping the function of proteins. This is also the case for G protein-coupled receptors (GPCRs), which constitute the largest family of membrane receptors with nearly 800 proteins. The GPCRM web service ( https://gpcrm.biomodellab.eu/ ) was set up for the nearly automatic generation of high-quality structures of modeled GPCRs. The three possible paths: "High similarity," "Quick path," and "Long path" allow the user to choose between a fast but less reliable path, up to more reliable but longer procedures. In the Advanced mode the service allows for user modifications including selection of template(s) and a manual adjustment of the sequence alignment.

Drug Repositioning For Allosteric Modulation of VIP and PACAP Receptors

Vasoactive intestinal peptide (VIP) and pituitary adenylate cyclase-activating polypeptide (PACAP) are two neuropeptides that contribute to the regulation of intestinal motility and secretion, exocrine and endocrine secretions, and homeostasis of the immune system. Their biological effects are mediated by three receptors named VPAC1, VPAC2 and PAC1 that belong to class B GPCRs. VIP and PACAP receptors have been identified as potential therapeutic targets for the treatment of chronic inflammation, neurodegenerative diseases and cancer. However, pharmacological use of endogenous ligands for these receptors is limited by their lack of specificity (PACAP binds with high affinity to VPAC1, VPAC2 and PAC1 receptors while VIP recognizes both VPAC1 and VPAC2 receptors), their poor oral bioavailability (VIP and PACAP are 27- to 38-amino acid peptides) and their short half-life. Therefore, the development of non-peptidic small molecules or specific stabilized peptidic ligands is of high interest. Structural similarities between VIP and PACAP receptors are major causes of difficulties in the design of efficient and selective compounds that could be used as therapeutics. In this study we performed structure-based virtual screening against the subset of the ZINC15 drug library. This drug repositioning screen provided new applications for a known drug: ticagrelor, a P2Y12 purinergic receptor antagonist. Ticagrelor inhibits both VPAC1 and VPAC2 receptors which was confirmed in VIP-binding and calcium mobilization assays. A following analysis of detailed ticagrelor binding modes to all three VIP and PACAP receptors with molecular dynamics revealed its allosteric mechanism of action. Using a validated homology model of inactive VPAC1 and a recently released cryo-EM structure of active VPAC1 we described how ticagrelor could block conformational changes in the region of 'tyrosine toggle switch' required for the receptor activation. We also discuss possible modifications of ticagrelor comparing other P2Y12 antagonist - cangrelor, closely related to ticagrelor but not active for VPAC1/VPAC2. This comparison with inactive cangrelor could lead to further improvement of the ticagrelor activity and selectivity for VIP and PACAP receptor sub-types.

A Molecular Dynamics Study of Vasoactive Intestinal Peptide Receptor 1 and the Basis of Its Therapeutic Antagonism

Vasoactive intestinal peptide receptor 1 (VPAC1) is a member of a secretin-like subfamily of G protein-coupled receptors. Its endogenous neuropeptide (VIP), secreted by neurons and immune cells, modulates various physiological functions such as exocrine and endocrine secretions, immune response, smooth muscles relaxation, vasodilation, and fetal development. As a drug target, VPAC1 has been selected for therapy of inflammatory diseases but drug discovery is still hampered by lack of its crystal structure. In this study we presented the homology model of this receptor constructed with the well-known web service GPCRM. The VPAC1 model is composed of extracellular and transmembrane domains that form a complex with an endogenous hormone VIP. Using the homology model of VPAC1 the mechanism of action of potential drug candidates for VPAC1 was described. Only two series of small-molecule antagonists of confirmed biological activity for VPAC1 have been described thus far. Molecular docking and a series of molecular dynamics simulations were performed to elucidate their binding to VPAC1 and resulting antagonist effect. The presented work provides the basis for the possible binding mode of VPAC1 antagonists and determinants of their molecular recognition in the context of other class B GPCRs. Until the crystal structure of VPAC1 will be released, the presented homology model of VPAC1 can serve as a scaffold for drug discovery studies and is available from the author upon request.

GPCRM: a homology modeling web service with triple membrane-fitted quality assessment of GPCR models

Due to the involvement of G protein-coupled receptors (GPCRs) in most of the physiological and pathological processes in humans they have been attracting a lot of attention from pharmaceutical industry as well as from scientific community. Therefore, the need for new, high quality structures of GPCRs is enormous. The updated homology modeling service GPCRM (http://gpcrm.biomodellab.eu/) meets those expectations by greatly reducing the execution time of submissions (from days to hours/minutes) with nearly the same average quality of obtained models. Additionally, due to three different scoring functions (Rosetta, Rosetta-MP, BCL::Score) it is possible to select accurate models for the required purposes: the structure of the binding site, the transmembrane domain or the overall shape of the receptor. Currently, no other web service for GPCR modeling provides this possibility. GPCRM is continually upgraded in a semi-automatic way and the number of template structures has increased from 20 in 2013 to over 90 including structures the same receptor with different ligands which can influence the structure not only in the on/off manner. Two types of protein viewers can be used for visual inspection of obtained models. The extended sortable tables with available templates provide links to external databases and display ligand-receptor interactions in visual form.

Ligand Binding Mechanisms in Human Cone Visual Pigments

Vertebrate vision starts with light absorption by visual pigments in rod and cone photoreceptor cells of the retina. Rhodopsin, in rod cells, responds to dim light, whereas three types of cone opsins (red, green, and blue) function under bright light and mediate color vision. Cone opsins regenerate with retinal much faster than rhodopsin, but the molecular mechanism of regeneration is still unclear. Recent advances in the area pinpoint transient intermediate opsin conformations, and a possible secondary retinal-binding site, as determinant factors for regeneration. In this Review, we compile previous and recent findings to discuss possible mechanisms of ligand entry in cone opsins, involving a secondary binding site, which may have relevant functional and evolutionary implications.

Potential off-target effects of beta-blockers on gut hormone receptors: In silico study including GUT-DOCK-A web service for small-molecule docking

The prolonged use of many currently available drugs results in the severe side effect of the disruption of glucose metabolism leading to type 2 diabetes mellitus (T2DM. Gut hormone receptors including glucagon receptor (GCGR) and the incretin hormone receptors: glucagon-like peptide 1 receptor (GLP1R) and gastric inhibitory polypeptide receptor (GIPR) are important drug targets for the treatment of T2DM, as they play roles in the regulation of glucose and insulin levels and of food intake. In this study, we hypothesized that we could compensate for the negative influences of specific drugs on glucose metabolism by the positive incretin effect enhanced by the off-target interactions with incretin GPCR receptors. As a test case, we chose to examine beta-blockers because beta-adrenergic receptors and incretin receptors are expressed in a similar location, making off-target interactions possible. The binding affinity of drugs for incretin receptors was approximated by using two docking scoring functions of Autodock VINA (GUT-DOCK) and Glide (Schrodinger) and juxtaposing these values with the medical information on drug-induced T2DM. We observed that beta-blockers with the highest theoretical binding affinities for gut hormone receptors were reported as the least harmful to glucose homeostasis in clinical trials. Notably, a recently discovered beta-blocker compound 15 ([4-((2S)-3-(((S)-3-(3-bromophenyl)-1-(methylamino)-1-oxopropan-2-yl)amino)-2-(2-cyclohexyl-2-phenylacetamido)-3-oxopropyl)benzamide was among the top-scoring drugs, potentially supporting its use in the treatment of hypertension in diabetic patients. Our recently developed web service GUT-DOCK (gut-dock.miningmembrane.com) allows for the execution of similar studies for any drug-like molecule. Specifically, users can compute the binding affinities for various class B GPCRs, gut hormone receptors, VIPR1 and PAC1R.

Drug-induced diabetes type 2: In silico study involving class B GPCRs

A disturbance of glucose homeostasis leading to type 2 diabetes mellitus (T2DM) is one of the severe side effects that may occur during a prolonged use of many drugs currently available on the market. In this manuscript we describe the most common cases of drug-induced T2DM, discuss available pharmacotherapies and propose new ones. Among various pharmacotherapies of T2DM, incretin therapies have recently focused attention due to the newly determined crystal structure of incretin hormone receptor GLP1R. Incretin hormone receptors: GLP1R and GIPR together with the glucagon receptor GCGR regulate food intake and insulin and glucose secretion. Our study showed that incretin hormone receptors, named also gut hormone receptors as they are expressed in the gastrointestinal tract, could potentially act as unintended targets (off-targets) for orally administrated drugs. Such off-target interactions, depending on their effect on the receptor (stimulation or inhibition), could be beneficial, like in the case of incretin mimetics, or unwanted if they cause, e.g., decreased insulin secretion. In this in silico study we examined which well-known pharmaceuticals could potentially interact with gut hormone receptors in the off-target way. We observed that drugs with the strongest binding affinity for gut hormone receptors were also reported in the medical information resources as the least disturbing the glucose homeostasis among all drugs in their class. We suggested that those strongly binding molecules could potentially stimulate GIPR and GLP1R and/or inhibit GCGR which could lead to increased insulin secretion and decreased hepatic glucose production. Such positive effect on the glucose homeostasis could compensate for other, adverse effects of pharmacotherapy which lead to drug-induced T2DM. In addition, we also described several top hits as potential substitutes of peptidic incretin mimetics which were discovered in the drug repositioning screen using gut hormone receptors structures against the ZINC15 compounds subset.

Comparative Modeling and Evaluation of Leukotriene B4 Receptors for Selective Drug Discovery Towards the Treatment of Inflammatory Diseases

Leukotriene B4 (LTB4) exerts its biological effects through stimulation of specific G protein-coupled receptors (GPCRs)-namely BLT1 and BLT2. Due to the absence of human BLT1 and BLT2 crystal structures, the current study was set to predict the 3D structures of these two receptors for structure-based anti-inflammatory drug discovery. Homology modeling of the BLT1 receptor was first constructed, based on various X-ray and NMR GPCR templates, followed by molecular dynamics (MD) refinement. Using a single-template approach, nine well-established alignment methods and ten secondary structure prediction methods during the backbone generation were implemented and assessed. The binding sites of the BLT1 receptor were then mapped using fifteen chemical probes with the help of FTMAP and AutoDock Vina 4.2 software. Model validation was performed through the docking of eight specific antagonists that have experimental inhibition constants (k_i) towards BLT1. The antagonists-BLT1 docked structures were then subjected to AMBER-based molecular mechanical minimization and the corresponding binding energies were calculated using molecular mechanics-generalized Born surface area (MM/GBSA) approach. According to the results, the most energetically stable models were constructed using SAlign method for the alignment process and PSIPRED for secondary structure prediction. In comparison, the refined BLT1 model built on 2KS9 as an NMR template has the lowest DOPE energy compared to those built on 4EA3 and 4XT1 as X-ray templates. According to the mapping results, two main binding sites were identified: one was among TMs II, III and VII and the other was among TMs III, IV and V. For the antagonists, correlation between binding energies and experimental data was in a good agreement, with a correlation coefficient (R² value) of 0.91. Due to the great amino acid sequence similarity between BLT1 and BLT2 receptors (calculated as 45.2%), BLT2 model was constructed based on the predicted BLT1 model.

Approaches for Differentiation and Interconverting GPCR Agonists and Antagonists

Predicting the functional preferences of the ligands was always a highly demanding task, much harder that predicting whether a ligand can bind to the receptor. This is because of significant similarities of agonists, antagonists and inverse agonists which are binding usually in the same binding site of the receptor and only small structural changes can push receptor toward a particular activation state. For G protein-coupled receptors, due to a large progress in crystallization techniques and also in receptor thermal stabilization, it was possible to obtain a large number of high-quality structures of complexes of these receptors with agonists and non-agonists. Additionally, the long-time-scale molecular dynamics simulations revealed how the activation processes of GPCRs can take place. Using both theoretical and experimental knowledge it was possible to employ many clever and sophisticated methods which can help to differentiate agonists and non-agonists, so one can interconvert them in search of the optimal drug.

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.

Using molecular dynamics for the refinement of atomistic models of GPCRs by homology modeling

Despite GPCRs sharing a common seven helix bundle, analysis of the diverse crystallographic structures available reveal specific features that might be relevant for ligand design. Despite the number of crystallographic structures of GPCRs steadily increasing, there are still challenges that hamper the availability of new structures. In the absence of a crystallographic structure, homology modeling remains one of the important techniques for constructing 3D models of proteins. In the present study we investigated the use of molecular dynamics simulations for the refinement of GPCRs models constructed by homology modeling. Specifically, we investigated the relevance of template selection, ligand inclusion as well as the length of the simulation on the quality of the GPCRs models constructed. For this purpose we chose the crystallographic structure of the rat muscarinic M3 receptor as reference and constructed diverse atomistic models by homology modeling, using different templates. Specifically, templates used in the present work include the human muscarinic M2; the more distant human histamine H1 and the even more distant bovine rhodopsin as shown in the GPCRs phylogenetic tree. We also investigated the use or not of a ligand in the refinement process. Hence, we conducted the refinement process of the M3 model using the M2 muscarinic as template with tiotropium or NMS docked in the orthosteric site and compared with the results obtained with a model refined without any ligand bound.

Rosetta Broker for membrane protein structure prediction: concentrative nucleoside transporter 3 and corticotropin-releasing factor receptor 1 test cases

Background

Membrane proteins are difficult targets for structure prediction due to the limited structural data deposited in Protein Data Bank. Most computational methods for membrane protein structure prediction are based on the comparative modeling. There are only few de novo methods targeting that distinct protein family. In this work an example of such de novo method was used to structurally and functionally characterize two representatives of distinct membrane proteins families of solute carrier transporters and G protein-coupled receptors. The well-known Rosetta program and one of its protocols named Broker was used in two test cases. The first case was de novo structure prediction of three N-terminal transmembrane helices of the human concentrative nucleoside transporter 3 (hCNT3) homotrimer belonging to the solute carrier 28 family of transporters (SLC28). The second case concerned the large scale refinement of transmembrane helices of a homology model of the corticotropin-releasing factor receptor 1 (CRFR1) belonging to the G protein-coupled receptors family.

Results

The inward-facing model of the hCNT3 homotrimer was used to propose the functional impact of its single nucleotide polymorphisms. Additionally, the 100 ns molecular dynamics simulation of the unliganded hCNT3 model confirmed its validity and revealed mobility of the selected binding site and homotrimer interface residues. The large scale refinement of transmembrane helices of the CRFR1 homology model resulted in the significant improvement of its accuracy with respect to the crystal structure of CRFR1, especially in the binding site area. Consequently, the antagonist CP-376395 could be docked with Autodock VINA to the CRFR1 model without any steric clashes.

Conclusions

The presented work demonstrated that Rosetta Broker can be a versatile tool for solving various issues referring to protein biology. Two distinct examples of de novo membrane protein structure prediction presented here provided important insights into three major areas of protein biology. Namely, the dynamics of the inward-facing hCNT3 homotrimer system, the structural changes of the CRFR1 receptor upon the antagonist binding and finally, the role of single nucleotide polymorphisms in both, hCNT3 and CRFR1 proteins, were investigated.

Electronic supplementary material

The online version of this article (doi:10.1186/s12900-017-0078-8) contains supplementary material, which is available to authorized users.

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.

In silico Exploration of the Conformational Universe of GPCRs

The structural plasticity of G protein coupled receptors (GPCRs) leads to a conformational universe going from inactive to active receptor states with several intermediate states. Many of them have not been captured yet and their role for GPCR activation is not well understood. The study of this conformational space and the transition dynamics between different receptor populations is a major challenge in molecular biophysics. The rational design of effector molecules that target such receptor populations allows fine-tuning receptor signalling with higher specificity to produce drugs with safer therapeutic profiles. In this minireview, we outline highly conserved receptor regions which are considered determinant for the establishment of distinct receptor states. We then discuss in-silico approaches such as dimensionality reduction methods and Markov State Models to explore the GPCR conformational universe and exploit the obtained conformations through structure-based drug design.

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.

A Hybrid Approach to Structure and Function Modeling of G Protein-Coupled Receptors

The recent GPCR Dock 2013 assessment of serotonin receptor 5-HT1B and 5-HT2B, and smoothened receptor SMO targets, exposed the strengths and weaknesses of the currently used computational approaches. The test cases of 5-HT1B and 5-HT2B demonstrated that both the receptor structure and the ligand binding mode can be predicted with the atomic-detail accuracy, as long as the target-template sequence similarity is relatively high. On the other hand, the observation of a low target-template sequence similarity, e.g., between SMO from the frizzled GPCR family and members of the rhodopsin family, hampers the GPCR structure prediction and ligand docking. Indeed, in GPCR Dock 2013, accurate prediction of the SMO target was still beyond the capabilities of most research groups. Another bottleneck in the current GPCR research, as demonstrated by the 5-HT2B target, is the reliable prediction of global conformational changes induced by activation of GPCRs. In this work, we report details of our protocol used during GPCR Dock 2013. Our structure prediction and ligand docking protocol was especially successful in the case of 5-HT1B and 5-HT2B-ergotamine complexes for which we provide one of the most accurate predictions. In addition to a description of the GPCR Dock 2013 results, we propose a novel hybrid computational methodology to improve GPCR structure and function prediction. This computational methodology employs two separate rankings for filtering GPCR models. The first ranking is ligand-based while the second is based on the scoring scheme of the recently published BCL method. In this work, we prove that the use of knowledge-based potentials implemented in BCL is an efficient way to cope with major bottlenecks in the GPCR structure prediction. Thereby, we also demonstrate that the knowledge-based potentials for membrane proteins were significantly improved, because of the recent surge in available experimental structures.

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.

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

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

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.

What can we learn from molecular dynamics simulations for GPCR drug design?

Recent years have seen a tremendous progress in the elucidation of experimental structural information for G-protein coupled receptors (GPCRs). Although for the vast majority of pharmaceutically relevant GPCRs structural information is still accessible only by homology models the steadily increasing amount of structural information fosters the application of structure-based drug design tools for this important class of drug targets. In this article we focus on the application of molecular dynamics (MD) simulations in GPCR drug discovery programs. Typical application scenarios of MD simulations and their scope and limitations will be described on the basis of two selected case studies, namely the binding of small molecule antagonists to the human CC chemokine receptor 3 (CCR3) and a detailed investigation of the interplay between receptor dynamics and solvation for the binding of small molecules to the human muscarinic acetylcholine receptor 3 (hM3R).

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.

Impact of template choice on homology model efficiency in virtual screening

Homology modeling is a reliable method of predicting the three-dimensional structures of proteins that lack NMR or X-ray crystallographic data. It employs the assumption that a structural resemblance exists between closely related proteins. Despite the availability of many crystal structures of possible templates, only the closest ones are chosen for homology modeling purposes. To validate the aforementioned approach, we performed homology modeling of four serotonin receptors (5-HT1AR, 5-HT2AR, 5-HT6R, 5-HT7R) for virtual screening purposes, using 10 available G-Protein Coupled Receptors (GPCR) templates with diverse evolutionary distances to the targets, with various approaches to alignment construction and model building. The resulting models were further validated in two steps by means of ligand docking and enrichment calculation, using Glide software. The final quality of the models was determined in virtual screening-like experiments by the AUROC score of the resulting ROC curves. The outcome of this research showed that no correlation between sequence identity and model quality was found, leading to the conclusion that the closest phylogenetic relative is not always the best template for homology modeling.

Structural features of the G-protein/GPCR interactions

BACKGROUND

The details of the functional interaction between G proteins and the G protein coupled receptors (GPCRs) have long been subjected to extensive investigations with structural and functional assays and a large number of computational studies.

SCOPE OF REVIEW

The nature and sites of interaction in the G-protein/GPCR complexes, and the specificities of these interactions selecting coupling partners among the large number of families of GPCRs and G protein forms, are still poorly defined.

MAJOR CONCLUSIONS

Many of the contact sites between the two proteins in specific complexes have been identified, but the three dimensional molecular architecture of a receptor-Gα interface is only known for one pair. Consequently, many fundamental questions regarding this macromolecular assembly and its mechanism remain unanswered.

GENERAL SIGNIFICANCE

In the context of current structural data we review the structural details of the interfaces and recognition sites in complexes of sub-family A GPCRs with cognate G-proteins, with special emphasis on the consequences of activation on GPCR structure, the prevalence of preassembled GPCR/G-protein complexes, the key structural determinants for selective coupling and the possible involvement of GPCR oligomerization in this process.

Modelling and enhanced molecular dynamics to steer structure-based drug discovery

The ever-increasing gap between the availabilities of the genome sequences and the crystal structures of proteins remains one of the significant challenges to the modern drug discovery efforts. The knowledge of structure-dynamics-functionalities of proteins is important in order to understand several key aspects of structure-based drug discovery, such as drug-protein interactions, drug binding and unbinding mechanisms and protein-protein interactions. This review presents a brief overview on the different state of the art computational approaches that are applied for protein structure modelling and molecular dynamics simulations of biological systems. We give an essence of how different enhanced sampling molecular dynamics approaches, together with regular molecular dynamics methods, assist in steering the structure based drug discovery processes.