Advances in the Development and Application of Computational Methodologies for Structural Modeling of G-Protein Coupled Receptors

Molecular Modeling of Histamine Receptors-Recent Advances in Drug Discovery

The recent developments of fast reliable docking, virtual screening and other algorithms gave rise to discovery of many novel ligands of histamine receptors that could be used for treatment of allergic inflammatory disorders, central nervous system pathologies, pain, cancer and obesity. Furthermore, the pharmacological profiles of ligands clearly indicate that these receptors may be considered as targets not only for selective but also for multi-target drugs that could be used for treatment of complex disorders such as Alzheimer's disease. Therefore, analysis of protein-ligand recognition in the binding site of histamine receptors and also other molecular targets has become a valuable tool in drug design toolkit. This review covers the period 2014-2020 in the field of theoretical investigations of histamine receptors mostly based on molecular modeling as well as the experimental characterization of novel ligands of these receptors.

Molecular modelling studies on 2-substituted octahydropyrazinopyridoindoles for histamine H2 receptor antagonism

The human histamine H2 receptor (hH2HR) is a G-protein coupled receptor protein with seven transmembrane (TM)-spanning helices primarily involved in regulation of gastric acid secretion. Antagonists targeting hH2HR are useful in the treatment of hyperacidic conditions such as peptic ulcers, gastresophageal reflux disease and gastrointestinal bleeding. We have previously reported the antagonism of 2-substituted pyrazinopyridoindoles at the human histamine H1 receptor and mode of binding of these compounds at the hH1HR using in silico methods. Interestingly, some of the compounds in the series also showed promising activity towards hH2HR that prompted us to investigate the mode of binding of these compounds at hH2HR. In the absence of the crystal structure of hH2HR a homology model has been constructed using multiple sequence alignment, using the X-ray crystal structures of Turkey β1-adrenergic receptor (tβ1AR), Human histamine H1 receptor (hH1HR), Human β2-adrenergic receptor (hβ2AR) and Human D3 dopamine receptor (hD3R). The important residues for binding were depicted in TMIII, TMV, TMVI and TMVII by the homology modelled hH2HR for 2-substituted pyrazinopyridoindoles. A comparative study for deducing the selectivity regarding the binding towards hH1HR and hH2HR has been carried out, which may be useful in designing of selective hH1HR/hH2HR antagonists in these classes of compounds.

Novel computational methodologies for structural modeling of spacious ligand binding sites of G-protein-coupled receptors: development and application to human leukotriene B4 receptor

This paper describes a novel method to predict the activated structures of G-protein-coupled receptors (GPCRs) with high accuracy, while aiming for the use of the predicted 3D structures in in silico virtual screening in the future. We propose a new method for modeling GPCR thermal fluctuations, where conformation changes of the proteins are modeled by combining fluctuations on multiple time scales. The core idea of the method is that a molecular dynamics simulation is used to calculate average 3D coordinates of all atoms of a GPCR protein against heat fluctuation on the picosecond or nanosecond time scale, and then evolutionary computation including receptor-ligand docking simulations functions to determine the rotation angle of each helix of a GPCR protein as a movement on a longer time scale. The method was validated using human leukotriene B4 receptor BLT1 as a sample GPCR. Our study demonstrated that the proposed method was able to derive the appropriate 3D structure of the active-state GPCR which docks with its agonists.

Multiple signaling routes involved in the regulation of adenylyl cyclase and extracellular regulated kinase by dopamine D(2) and D(3) receptors

Most G protein coupled receptors (GPCR) regulate multiple cellular processes by coupling to more than one kind of G protein. Furthermore, recent studies have reported G protein-independent/β-arrestin-dependent signaling pathway for some GPCRs. Dopamine D(2) and D(3) receptors (D(2)R, D(3)R), the major targets of currently used antipsychotic drugs, are co-expressed in some of the same dopaminergic neurons and regulate the same overlapping effectors. However, the specific subunits of G proteins that regulate each signaling pathway are not clearly identified. In addition, the existence of β-arrestin-dependent/G protein-independent signaling is not clear for these receptors. In this study, we determined the G protein subtypes and β-arrestin dependency involved in the signaling of D(2)R and D(3)R, which was measured by inhibition of adenylyl cyclase and extracellular signal-regulated kinase (ERK) activation. For the inhibition of cAMP production in HEK-293 cells, D(2)R used the Gαo subunit but D(3)R used the βγ subunit of Gi family proteins. For the regulation of ERK activation, D(2)R used the α subunits of Gi/o proteins both in HEK-293 cells and COS-7 cells, but D(3)R used Gαo and Gβγ in HEK-293 cells and COS-7 cells, respectively. β-Arrestin-dependent/G protein-independent ERK activation was not observed for both D(2)R and D(3)R. Agonist-induced β-arrestin translocation was observed with D(2)R but not with D(3)R, and β-arrestins exerted inhibitory influences on G protein-dependent ERK activation by D(2)R, but not D(3)R. These results show that the D(2)R and D(3)R, which have overlapping cellular expressions and functional roles, employ distinct G protein subunits depending on the cell types and the effectors they control.

Modeling of mammalian olfactory receptors and docking of odorants

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

The use of G-protein coupled receptor models in lead optimization

With the emerging new crystal structures of G-protein coupled receptors (GPCRs), the number of reported in silico receptor models vastly increases every year. The use of these models in lead optimization (LO) is investigated here. Although there are many studies where GPCR models are used to identify new chemotypes by virtual screening, the classical application in LO is rarely reported. The reason for this may be that the quality of a model, which is appropriate for atomistic modeling, must be very high, and the biology of GPCR ligand-dependent signaling is still not fully understood. However, the few reported studies show that GPCR models can be used efficiently in LO for various problems, such as affinity optimization or tuning of physicochemical parameters.

Molecular dynamics simulations and docking studies on 3D models of the heterodimeric and homodimeric 5-HT2A receptor subtype

Background: G-protein coupled receptors may exist as functional homodimers, heterodimers and even as higher aggregates. In this work, we investigate the 5-HT2A receptor, which is a known target for antipsychotic drugs. Recently, 5-HT2A has been shown to form functional homodimers and heterodimers with the mGluR2 receptor. The objective of this study is to build up 3D models of the 5-HT2A/mGluR2 heterodimer and of the 5-HT2A-5-HT2A homodimer, and to evaluate the impact of the dimerization interface on the shape of the 5-HT2A binding pocket by using molecular dynamics simulations and docking studies. Results and discussion: The heterodimer, homodimer and monomeric 5-HT2A receptors were simulated by molecular dynamics for 40 ns each. The trajectories were clustered and representative structures of six clusters for each system were generated. Inspection of the these representative structures clearly indicate an effect of the dimerization interface on the topology of the binding pocket. Docking studies allowed to generate receiver operating characteristic curves for a set of 5-HT2A ligands, indicating that different complexes prefer different classes of 5-HT2A ligands. Conclusion: This study clearly indicates that the presence of a dimerization interface must explicitly be considered when studying G-protein coupled receptors known to exist as dimers. Molecular dynamics simulation and cluster analysis are appropriate tools to study the phenomenon.

A practical introduction to molecular dynamics simulations: applications to homology modeling

In this chapter, practical concepts and guidelines are provided for the use of molecular dynamics (MD) simulation for the refinement of homology models. First, an overview of the history and a theoretical background of MD are given. Literature examples of successful MD refinement of homology models are reviewed before selecting the Cytochrome P450 2J2 structure as a case study. We describe the setup of a system for classical MD simulation in a detailed stepwise fashion and how to perform the refinement described in the publication of Li et al. (Proteins 71:938-949, 2008). This tutorial is based on version 11 of the AMBER Molecular Dynamics software package (http://ambermd.org/). However, the approach discussed is equally applicable to any condensed phase MD simulation environment.

Putative active states of a prototypic g-protein-coupled receptor from biased molecular dynamics

A major current focus of structural work on G-protein-coupled receptors (GPCRs) pertains to the investigation of their active states. However, for virtually all GPCRs, active agonist-bound intermediate states have been difficult to characterize experimentally owing to their higher conformational flexibility, and thus intrinsic instability, as compared to inactive inverse agonist-bound states. In this work, we explored possible activation pathways of the prototypic GPCR bovine rhodopsin by means of biased molecular dynamics simulations. Specifically, we used an explicit atomistic representation of the receptor and its environment, and sampled the conformational transition from the crystal structure of a photoactivated deprotonated state of rhodopsin to the low pH crystal structure of opsin in the presence of 11-trans-retinal, using adiabatic biased molecular dynamics simulations. We then reconstructed the system free-energy landscape along the predetermined transition trajectories using a path collective variable approach based on metadynamics. Our results suggest that the two experimental endpoints of rhodopsin/opsin are connected by at least two different pathways, and that the conformational transition is populated by at least four metastable states of the receptor, characterized by a different amplitude of the outward movement of transmembrane helix 6.

Mass spectrometry-based GPCR proteomics: comprehensive characterization of the human cannabinoid 1 receptor

The human cannabinoid 1 receptor (hCB1), a ubiquitous G protein-coupled receptor (GPCR), transmits cannabinergic signals that participate in diverse (patho)physiological processes. Pharmacotherapeutic hCB1 targeting is considered a tractable approach for treating such prevalent diseases as obesity, mood disorders, and drug addiction. The hydrophobic nature of the transmembrane helices of hCB1 presents a formidable difficulty to its direct structural analysis. Comprehensive experimental characterization of functional hCB1 by mass spectrometry (MS) is essential to the targeting of affinity probes that can be used to define directly hCB1 binding domains using a ligand-assisted experimental approach. Such information would greatly facilitate the rational design of hCB1-selective agonists/antagonists with therapeutic potential. We report the first high-coverage MS analysis of the primary sequence of the functional hCB1 receptor, one of the few such comprehensive MS-based analyses of any GPCR. Recombinant C-terminal hexa-histidine-tagged hCB1 (His6-hCB1) was expressed in cultured insect (Spodoptera frugiperda) cells, solubilized by a procedure devised to enhance receptor purity following metal-affinity chromatography, desalted by buffer exchange, and digested in solution with (chymo)trypsin. "Bottom-up" nanoLC-MS/MS of the (chymo)tryptic digests afforded a degree of overall hCB1 coverage (>94%) thus far reported for only two other GPCRs. This MS-compatible procedure devised for His6-hCB1 sample preparation, incorporating in-solution (chymo)trypsin digestion in the presence of a low concentration of CYMAL-5 detergent, may be applicable to the MS-based proteomic characterization of other GPCRs. This work should help enable future ligand-assisted structural characterization of hCB1 binding motifs at the amino-acid level using rationally designed and targeted covalent cannabinergic probes.

Progress in elucidating the structural and dynamic character of G Protein-Coupled Receptor oligomers for use in drug discovery

G Protein-Coupled Receptors (GPCRs) are the most targeted group of proteins for the development of therapeutic drugs. Until the last decade, structural information about this family of membrane proteins was relatively scarce, and their mechanisms of ligand binding and signal transduction were modeled on the assumption that GPCRs existed and functioned as monomeric entities. New crystal structures of native and engineered GPCRs, together with important biochemical and biophysical data that reveal structural details of the activation mechanism(s) of this receptor family, provide a valuable framework to improve dynamic molecular models of GPCRs with the ultimate goal of elucidating their allostery and functional selectivity. Since the dynamic movements of single GPCR protomers are likely to be affected by the presence of neighboring interacting subunits, oligomeric arrangements should be taken into account to improve the predictive ability of computer-assisted structural models of GPCRs for effective use in drug design.

G-protein-coupled receptor-focused drug discovery using a target class platform approach

In recent years, several large pharmaceutical companies have taken a novel approach to drug discovery biology and chemistry in that they channel their efforts with respect to particular target classes, such as G-protein-coupled receptors (GPCRs), toward dedicated, specialized teams. Benefits of such an organizational structure are the prospects of establishing several target-family-specific experimental techniques and skill sets, thereby enabling a comprehensive functional profiling of drug candidates in different pharmacological respects. In this context, the recently increased number of reports on GPCR ligand-biased signaling has further spurred the efforts in the pharmaceutical industry toward broader biological characterization of the test compounds, for example employing high-content screening to analyze different GPCR ligand-induced signaling pathways. The knowledge of the disease-relevant functional properties of the small molecule GPCR ligands enables target-specific chemical optimization and GPCR-subclass-directed library design. In the case of GPCRs, where little--although at present slowly expanding--structural information on the targets is available, the modeling of GPCR structures crucially depends on biological validation (typically supported by site-directed mutagenesis of the GPCR ligand binding site). In this review, we aim to recapitulate efforts in the pharmaceutical industry to address GPCR-directed drug discovery in a target-class-directed platform approach: establishing GPCR-specific biological assay panels and creating computational chemistry methods for finding and optimizing small molecules modulating the activity of GPCRs.