Evaluation of homology modeling of G-protein-coupled receptors in light of the A(2A) adenosine receptor crystallographic structure

Computational Workflow for Refining AlphaFold Models in Drug Design Using Kinetic and Thermodynamic Binding Calculations: A Case Study for the Unresolved Inactive Human Adenosine A3 Receptor

A structure-based drug design pipeline that considers both thermodynamic and kinetic binding data of ligands against a receptor will enable the computational design of improved drug molecules. For unresolved GPCR-ligand complexes, a workflow that can apply both thermodynamic and kinetic binding data in combination with alpha-fold (AF)-derived or other homology models and experimentally resolved binding modes of relevant ligands in GPCR-homologs needs to be tested. Here, as test case, we studied a congeneric set of ligands that bind to a structurally unresolved G protein-coupled receptor (GPCR), the inactive human adenosine A3 receptor (hA3R). We tested three available homology models from which two have been generated from experimental structures of hA1R or hA2AR and one model was a multistate alphafold 2 (AF2)-derived model. We applied alchemical calculations with thermodynamic integration coupled with molecular dynamics (TI/MD) simulations to calculate the experimental relative binding free energies and residence time (τ)-random accelerated MD (τ-RAMD) simulations to calculate the relative residence times (RTs) for antagonists. While the TI/MD calculations produced, for the three homology models, good Pearson correlation coefficients, correspondingly, r = 0.74, 0.62, and 0.67 and mean unsigned error (mue) values of 0.94, 1.31, and 0.81 kcal mol-1, the τ-RAMD method showed r = 0.92 and 0.52 for the first two models but failed to produce accurate results for the multistate AF2-derived model. With subsequent optimization of the AF2-derived model by reorientation of the side chain of R1735.34 located in the extracellular loop 2 (EL2) that blocked ligand's unbinding, the computational model showed r = 0.84 for kinetic data and improved performance for thermodynamic data (r = 0.81, mue = 0.56 kcal mol-1). Overall, after refining the multistate AF2 model with physics-based tools, we were able to show a strong correlation between predicted and experimental ligand relative residence times and affinities, achieving a level of accuracy comparable to an experimental structure. The computational workflow used can be applied to other receptors, helping to rank candidate drugs in a congeneric series and enabling the prioritization of leads with stronger binding affinities and longer residence times.

BIO-GATS: A Tool for Automated GPCR Template Selection Through a Biophysical Approach for Homology Modeling

G protein-coupled receptors (GPCRs) are the largest family of membrane proteins with more than 800 members. GPCRs are involved in numerous physiological functions within the human body and are the target of more than 30% of the United States Food and Drug Administration (FDA) approved drugs. At present, over 400 experimental GPCR structures are available in the Protein Data Bank (PDB) representing 76 unique receptors. The absence of an experimental structure for the majority of GPCRs demand homology models for structure-based drug discovery workflows. The generation of good homology models requires appropriate templates. The commonly used methods for template selection are based on sequence identity. However, there exists low sequence identity among the GPCRs. Sequences with similar patterns of hydrophobic residues are often structural homologs, even with low sequence identity. Extending this, we propose a biophysical approach for template selection based principally on hydrophobicity correspondence between the target and the template. Our approach takes into consideration other relevant parameters, including resolution, similarity within the orthosteric binding pocket of GPCRs, and structure completeness, for template selection. The proposed method was implemented in the form of a free tool called Bio-GATS, to provide the user with easy selection of the appropriate template for a query GPCR sequence. Bio-GATS was successfully validated with recent published benchmarking datasets. An application to an olfactory receptor to select an appropriate template has also been provided as a case study.

In Silico Drug Design for Purinergic GPCRs: Overview on Molecular Dynamics Applied to Adenosine and P2Y Receptors

Molecular modeling has contributed to drug discovery for purinergic GPCRs, including adenosine receptors (ARs) and P2Y receptors (P2YRs). Experimental structures and homology modeling have proven to be useful in understanding and predicting structure activity relationships (SAR) of agonists and antagonists. This review provides an excursus on molecular dynamics (MD) simulations applied to ARs and P2YRs. The binding modes of newly synthesized A1AR- and A3AR-selective nucleoside derivatives, potentially of use against depression and inflammation, respectively, have been predicted to recapitulate their SAR and the species dependence of A3AR affinity. P2Y12R and P2Y1R crystallographic structures, respectively, have provided a detailed understanding of the recognition of anti-inflammatory P2Y14R antagonists and a large group of allosteric and orthosteric antagonists of P2Y1R, an antithrombotic and neuroprotective target. MD of A2AAR (an anticancer and neuroprotective target), A3AR, and P2Y1R has identified microswitches that are putatively involved in receptor activation. The approach pathways of different ligands toward A2AAR and P2Y1R binding sites have also been explored. A1AR, A2AAR, and A3AR were utilizes to study allosteric phenomena, but locating the binding site of structurally diverse allosteric modulators, such as an A3AR enhancer LUF6000, is challenging. Ligand residence time, a predictor of in vivo efficacy, and the structural role of water were investigated through A2AAR MD simulations. Thus, new MD and other modeling algorithms have contributed to purinergic GPCR drug discovery.

The role of water and protein flexibility in the structure-based virtual screening of allosteric GPCR modulators: an mGlu5 receptor case study

Stabilizing unique receptor conformations, allosteric modulators of G-protein coupled receptors (GPCRs) might open novel treatment options due to their new pharmacological action, their enhanced specificity and selectivity in both binding and signaling. Ligand binding occurs at intrahelical allosteric sites and involves significant induced fit effects that include conformational changes in the local protein environment and water networks. Based on the analysis of available crystal structures of metabotropic glutamate receptor 5 (mGlu₅) we investigated these effects in the binding of mGlu₅ receptor negative allosteric modulators. A large set of retrospective virtual screens revealed that the use of multiple protein structures and the inclusion of selected water molecules improves virtual screening performance compared to conventional docking strategies. The role of water molecules and protein flexibility in ligand binding can be taken into account efficiently by the proposed docking protocol that provided reasonable enrichment of true positives. This protocol is expected to be useful also for identifying intrahelical allosteric modulators for other GPCR targets.

Breakthrough in GPCR Crystallography and Its Impact on Computer-Aided Drug Design

Recent crystallographic structures of G protein-coupled receptors (GPCRs) have greatly advanced our understanding of the recognition of their diverse agonist and antagonist ligands. We illustrate here how this applies to A_2A adenosine receptors (ARs) and to P2Y₁ and P2Y₁₂ receptors (P2YRs) for ADP. These X-ray structures have impacted the medicinal chemistry aimed at discovering new ligands for these two receptor families, including receptors that have not yet been crystallized but are closely related to the known structures. In this Chapter, we discuss recent structure-based drug design projects that led to the discovery of: (a) novel A₃AR agonists based on a highly rigidified (N)-methanocarba scaffold for the treatment of chronic neuropathic pain and other conditions, (b) fluorescent probes of the ARs and P2Y₁₄R, as chemical tools for structural probing of these GPCRs and for improving assay capabilities, and (c) new more drug-like antagonists of the inflammation-related P2Y₁₄R. We also describe the computationally enabled molecular recognition of positive (for A₃AR) and negative (P2Y₁R) allosteric modulators that in some cases are shown to be consistent with structure-activity relationship (SAR) data. Thus, computational modeling has become an essential tool for the design of purine receptor ligands.

Discovery of Novel Adenosine Receptor Antagonists through a Combined Structure- and Ligand-Based Approach Followed by Molecular Dynamics Investigation of Ligand Binding Mode

An intense effort is made by pharmaceutical and academic research laboratories to identify and develop selective antagonists for each adenosine receptor (AR) subtype as potential clinical candidates for "soft" treatment of various diseases. Crystal structures of subtypes A_2A and A₁ARs offer exciting opportunities for structure-based drug design. In the first part of the present work, Maybridge HitFinder library of 14400 compounds was utilized to apply a combination of structure-based against the crystal structure of A_2AAR and ligand-based methodologies. The docking poses were rescored by CHARMM energy minimization and calculation of the desolvation energy using Poisson-Boltzmann equation electrostatics. Out of the eight selected and tested compounds, five were found positive hits (63% success). Although the project was initially focused on targeting A_2AAR, the identified antagonists exhibited low micromolar or micromolar affinity against A_2A/A₃, ARs, or A₃AR, respectively. Based on these results, 19 compounds characterized by novel chemotypes were purchased and tested. Sixteen of them were identified as AR antagonists with affinity toward combinations of the AR family isoforms (A_2A/A₃, A₁/A₃, A₁/A_2A/A₃, and A₃). The second part of this work involves the performance of hundreds of molecular dynamics (MD) simulations of complexes between the ARs and a total of 27 ligands to resolve the binding interactions of the active compounds, which were not achieved by docking calculations alone. This computational work allowed the prediction of stable and unstable complexes which agree with the experimental results of potent and inactive compounds, respectively. Of particular interest is that the 2-amino-thiophene-3-carboxamides, 3-acylamino-5-aryl-thiophene-2-carboxamides, and carbonyloxycarboximidamide derivatives were found to be selective and possess a micromolar to low micromolar affinity for the A₃ receptor.

Better agonist for the opioid receptors

This commentary highlights the recent work published in journal Nature on the structural based discovery of novel analgesic compounds for opioid receptors with minimal effects. Manglik et al. selectively targeted the Gi based μOR pathway instead of the β-arrestin pathway of the opioids. The computational screening of millions of compounds showed a list of several competent ligands. From these ligands they synthesized the compounds with the best docking score, which were further optimized by adding side residues for better interaction with the μOR. A promising compound, PZM21, was a selective agonist of μOR. It has better analgesic properties with minimal side effects of respiratory depression and constipation. This work is a step towards better drug designing and synthesizing in terms of efficacy, specificity with least side effects of targeted GPCR proteins present in the human proteome.

In Silico Studies Targeting G-protein Coupled Receptors for Drug Research Against Parkinson's Disease

Parkinson's Disease (PD) is a long-term neurodegenerative brain disorder that mainly affects the motor system. The causes are still unknown, and even though currently there is no cure, several therapeutic options are available to manage its symptoms. The development of novel antiparkinsonian agents and an understanding of their proper and optimal use are, indeed, highly demanding. For the last decades, L-3,4-DihydrOxyPhenylAlanine or levodopa (L-DOPA) has been the gold-standard therapy for the symptomatic treatment of motor dysfunctions associated to PD. However, the development of dyskinesias and motor fluctuations (wearing-off and on-off phenomena) associated with long-term L-DOPA replacement therapy have limited its antiparkinsonian efficacy. The investigation for non-dopaminergic therapies has been largely explored as an attempt to counteract the motor side effects associated with dopamine replacement therapy. Being one of the largest cell membrane protein families, G-Protein-Coupled Receptors (GPCRs) have become a relevant target for drug discovery focused on a wide range of therapeutic areas, including Central Nervous System (CNS) diseases. The modulation of specific GPCRs potentially implicated in PD, excluding dopamine receptors, may provide promising non-dopaminergic therapeutic alternatives for symptomatic treatment of PD. In this review, we focused on the impact of specific GPCR subclasses, including dopamine receptors, adenosine receptors, muscarinic acetylcholine receptors, metabotropic glutamate receptors, and 5-hydroxytryptamine receptors, on the pathophysiology of PD and the importance of structure- and ligand-based in silico approaches for the development of small molecules to target these receptors.

Assessing GPCR homology models constructed from templates of various transmembrane sequence identities: Binding mode prediction and docking enrichment

GPCR crystal structures have become more readily accessible in recent years. However, homology models of GPCRs continue to play an important role as many GPCR structures remain unsolved. The new crystal structures now available provide not only additional templates for homology modelling but also the opportunity to assess the performance of homology models against their respective crystal structures and gain insight into the performance of such models. In this study we have constructed homology models from templates of various transmembrane sequence identities for eight GPCR targets to better understand the relationship between transmembrane sequence identity and model quality. Model quality was assessed relative to the crystal structure in terms of structural accuracy as well as performance in two typical structure-based drug design applications: ligand binding pose prediction and docking enrichment in virtual screening. Crystal structures significantly outperformed homology models in both assessments. Accurate ligand binding pose prediction was possible but difficult to achieve using homology models, even with the use of induced fit docking. In virtual screening using homology models still conferred significant enrichment compared to random selection, with a clear benefit also observed in using models optimized through induced fit docking. Our results indicate that while homology models that are reasonably accurate structurally can be constructed, without significant refinement homology models will be outperformed by crystal structures in ligand binding pose prediction and docking enrichment regardless of the template used, primarily due to the extremely high level of structural accuracy needed for such applications.

Homology Modeling and Protein Interaction Map of CHRNA7 Neurogenesis Protein

CHRNA7 is a neurodevelopmental protein involved in differentiation and neurogenesis, which is also named as nicotinic acetylcholine receptors, cholinergic receptor, nicotinic, alpha 7 (neuronal). The protein encoded by this gene forms a homo-oligomeric channel. It is a major component of brain nicotinic receptors displays that are blocked by and sensitive to alpha-bungarotoxin. Studies reports involvement of CHRNA7 protein in different neurological diseases. Non-availability of 3-dimensional (3D) structure leads the study toward structure 3D prediction along with its interaction analysis. The current paper is focused on the structure prediction through homology modeling of CHRNA7 along with binding site prediction using Schrödinger software suite. In continuation of the study, protein-protein interaction analysis is carried out by using string database. Tertiary structure along with binding sites was obtained, and visualized CHRAN7 protein have interaction with CHRNA protein family along with JAK2, AKT1, PICK1 protein that are involved in neurological disease. Structure formation analysis is an important aspect of proteomics studies. Hence, this predicted structure can be used for further advance studies and drug designing. Protein interaction analysis shows that CHRNA7 protein also interact with AKT1 protein which regulate neuronal differentiation and development, that signifies the role of CHRNA7 protein in neurological diseases.

In search of novel ligands using a structure-based approach: a case study on the adenosine A2A receptor

In this work, we present a case study to explore the challenges associated with finding novel molecules for a receptor that has been studied in depth and has a wealth of chemical information available. Specifically, we apply a previously described protocol that incorporates explicit water molecules in the ligand binding site to prospectively screen over 2.5 million drug-like and lead-like compounds from the commercially available eMolecules database in search of novel binders to the adenosine A_2A receptor (A_2AAR). A total of seventy-one compounds were selected for purchase and biochemical assaying based on high ligand efficiency and high novelty (Tanimoto coefficient ≤0.25 to any A_2AAR tested compound). These molecules were then tested for their affinity to the adenosine A_2A receptor in a radioligand binding assay. We identified two hits that fulfilled the criterion of ~50 % radioligand displacement at a concentration of 10 μM. Next we selected an additional eight novel molecules that were predicted to make a bidentate interaction with Asn253^6.55, a key interacting residue in the binding pocket of the A_2AAR. None of these eight molecules were found to be active. Based on these results we discuss the advantages of structure-based methods and the challenges associated with finding chemically novel molecules for well-explored targets.

Adenosine receptor neurobiology: overview

Adenosine is a naturally occurring nucleoside that is distributed ubiquitously throughout the body as a metabolic intermediary. In the brain, adenosine functions as an important upstream neuromodulator of a broad spectrum of neurotransmitters, receptors, and signaling pathways. By acting through four G-protein-coupled receptors, adenosine contributes critically to homeostasis and neuromodulatory control of a variety of normal and abnormal brain functions, ranging from synaptic plasticity, to cognition, to sleep, to motor activity to neuroinflammation, and cell death. This review begun with an overview of the gene and genome structure and the expression pattern of adenosine receptors (ARs). We feature several new developments over the past decade in our understanding of AR functions in the brain, with special focus on the identification and characterization of canonical and noncanonical signaling pathways of ARs. We provide an update on functional insights from complementary genetic-knockout and pharmacological studies on the AR control of various brain functions. We also highlight several novel and recent developments of AR neurobiology, including (i) recent breakthrough in high resolution of three-dimension structure of adenosine A2A receptors (A2ARs) in several functional status, (ii) receptor-receptor heterodimerization, (iii) AR function in glial cells, and (iv) the druggability of AR. We concluded the review with the contention that these new developments extend and strengthen the support for A1 and A2ARs in brain as therapeutic targets for neurologic and psychiatric diseases.

Docking and Virtual Screening Strategies for GPCR Drug Discovery

Progress in structure determination of G protein-coupled receptors (GPCRs) has made it possible to apply structure-based drug design (SBDD) methods to this pharmaceutically important target class. The quality of GPCR structures available for SBDD projects fall on a spectrum ranging from high resolution crystal structures (<2 Å), where all water molecules in the binding pocket are resolved, to lower resolution (>3 Å) where some protein residues are not resolved, and finally to homology models that are built using distantly related templates. Each GPCR project involves a distinct set of opportunities and challenges, and requires different approaches to model the interaction between the receptor and the ligands. In this review we will discuss docking and virtual screening to GPCRs, and highlight several refinement and post-processing steps that can be used to improve the accuracy of these calculations. Several examples are discussed that illustrate specific steps that can be taken to improve upon the docking and virtual screening accuracy. While GPCRs are a unique target class, many of the methods and strategies outlined in this review are general and therefore applicable to other protein families.

Structure-based drug design for G protein-coupled receptors

Our understanding of the structural biology of G protein-coupled receptors has undergone a transformation over the past 5 years. New protein-ligand complexes are described almost monthly in high profile journals. Appreciation of how small molecules and natural ligands bind to their receptors has the potential to impact enormously how medicinal chemists approach this major class of receptor targets. An outline of the key topics in this field and some recent examples of structure- and fragment-based drug design are described. A table is presented with example views of each G protein-coupled receptor for which there is a published X-ray structure, including interactions with small molecule antagonists, partial and full agonists. The possible implications of these new data for drug design are discussed.

Selecting an optimal number of binding site waters to improve virtual screening enrichments against the adenosine A2A receptor

A major challenge in structure-based virtual screening (VS) involves the treatment of explicit water molecules during docking in order to improve the enrichment of active compounds over decoys. Here we have investigated this in the context of the adenosine A2A receptor, where water molecules have previously been shown to be important for achieving high enrichment rates with docking, and where the positions of some binding site waters are known from a high-resolution crystal structure. The effect of these waters (both their presence and orientations) on VS enrichment was assessed using a carefully curated set of 299 high affinity A2A antagonists and 17,337 decoys. We show that including certain crystal waters greatly improves VS enrichment and that optimization of water hydrogen positions is needed in order to achieve the best results. We also show that waters derived from a molecular dynamics simulation - without any knowledge of crystallographic waters - can improve enrichments to a similar degree as the crystallographic waters, which makes this strategy applicable to structures without experimental knowledge of water positions. Finally, we used decision trees to select an ensemble of structures with different water molecule positions and orientations that outperforms any single structure with water molecules. The approach presented here is validated against independent test sets of A2A receptor antagonists and decoys from the literature. In general, this water optimization strategy could be applied to any target with waters-mediated protein-ligand interactions.

Crystal structures of the A2A adenosine receptor and their use in medicinal chemistry

New insights into drug design are derived from the X-ray crystallographic structures of G protein-coupled receptors (GPCRs), and the adenosine receptors (ARs) are at the forefront of this effort. The 3D knowledge of receptor binding and activation promises to enable drug discovery for GPCRs in general, and specifically for the ARs. The predictability of modeling based on the X-ray structures of the A_2AAR has been well demonstrated in the identification, design and modification of both known and novel AR agonists and antagonists. It is expected that structure-based design of drugs acting through ARs will provide new avenues to clinically useful agents.

Synthesis, biological activity and molecular modelling studies of tricyclic alkylimidazo-, pyrimido- and diazepinopurinediones

Syntheses and biological activities of imidazo-, pyrimido- and diazepino[2,1-f]purinediones containing N-alkyl substituents (with straight, branched or unsaturated chains) are described. Tricyclic derivatives were synthesized by the cyclization of 8-bromo-substituted 7-(2-bromoethyl)-, 7-(3-chloropropyl)- or 7-(4-bromobutyl)-theophylline with primary amines under various conditions. Compound 22 with an ethenyl substituent was synthesized by dehydrohalogenation of 9-(2-bromoethyl)-1,3-dimethyltetrahydropyrimido[2,1-f]purinedione. The obtained derivatives (5-35) were initially evaluated for their affinity at rat A1 and A2A adenosine receptors (AR), showing moderate affinity for both adenosine receptor subtypes. The best ligands were diazepinopurinedione 28 (K i = 0.28 μM) with fivefold A2A selectivity and the non-selective A1/A2A AR ligand pyrimidopurinedione 35 (K i A1 = 0.28 μM and K i A2A = 0.30 μM). The compounds were also evaluated for their affinity at human A1, A2A, A2B and A3 ARs. All of the obtained compounds were docked to the A2A AR X-ray structure in complex with the xanthine-based, potent adenosine receptor antagonist-XAC. The likely interactions of imidazo-, pyrimido- and diazepino[2,1-f]purinediones with the residues forming the A2A binding pocket were discussed. Furthermore, the new compounds were tested in vivo as anticonvulsants in maximal electroshock, subcutaneous pentylenetetrazole (ScMet) and TOX tests in mice (i.p.). Pyrimidopurinediones showed anticonvulsant activity mainly in the ScMet test. The best derivative was compound 11, showing 100 % protection at a dose of 100 mg/kg without symptoms of neurotoxicity. Compounds 6, 7, 8 and 14 with short substituents showed neurotoxicity and caused death. In rat tests (p.o.), 9 was characterized by a high protection index (>13.3). AR affinity did not apparently correlate with the antiepileptic potency of the compounds.

Genome-wide Membrane Protein Structure Prediction

Transmembrane proteins allow cells to extensively communicate with the external world in a very accurate and specific way. They form principal nodes in several signaling pathways and attract large interest in therapeutic intervention, as the majority pharmaceutical compounds target membrane proteins. Thus, according to the current genome annotation methods, a detailed structural/functional characterization at the protein level of each of the elements codified in the genome is also required. The extreme difficulty in obtaining high-resolution three-dimensional structures, calls for computational approaches. Here we review to which extent the efforts made in the last few years, combining the structural characterization of membrane proteins with protein bioinformatics techniques, could help describing membrane proteins at a genome-wide scale. In particular we analyze the use of comparative modeling techniques as a way of overcoming the lack of high-resolution three-dimensional structures in the human membrane proteome.

Structure-based approaches to ligands for G-protein-coupled adenosine and P2Y receptors, from small molecules to nanoconjugates

Adenosine receptor (ARs) and P2Y receptors (P2YRs) that respond to extracellular nucleosides/nucleotides are associated with new directions for therapeutics. The X-ray structures of the A2AAR complexes with agonists and antagonists are examined in relationship to the G-protein-coupled receptor (GPCR) superfamily and applied to drug discovery. Much of the data on AR ligand structure from early SAR studies now are explainable from the A2AAR X-ray crystallography. The ligand-receptor interactions in related GPCR complexes can be identified by means of modeling approaches, e.g., molecular docking. Thus, molecular recognition in binding and activation processes has been studied effectively using homology modeling and applied to ligand design. Virtual screening has yielded new nonnucleoside AR antagonists, and existing ligands have been improved with knowledge of the receptor interactions. New agonists are being explored for central nervous system and peripheral therapeutics based on in vivo activity, such as chronic neuropathic pain. Ligands for receptors more distantly related to the X-ray template, i.e., P2YRs, have been introduced and are mainly used as pharmacological tools for elucidating the physiological role of extracellular nucleotides. Other ligand tools for drug discovery include fluorescent probes, radioactive probes, multivalent probes, and functionalized nanoparticles.

Molecular modeling of vasopressin receptor and in silico screening of V1b receptor antagonists

INTRODUCTION

G protein-coupled receptors (GPCRs) are integral membrane proteins which contain seven-transmembrane-spanning alpha-helices. GPCR-mediated signaling has been associated with various human diseases, positioning GPCRs as attractive targets in the drug discovery field. Recently, through advances in protein engineering and crystallography, the number of resolved GPCR structures has increased dramatically. This growing availability of GPCR structures has greatly accelerated structure-based drug design (SBDD) and in silico screening for GPCR-targeted drug discovery.

AREAS COVERED

The authors introduce the current status of X-ray crystallography of GPCRs and what has been revealed from the resolved crystal structures. They also review the recent advances in SBDD and in silico screening for GPCR-targeted drug discovery and discuss a docking study, using homology modeling, with the discovery of potent antagonists of the vasopressin 1b receptor.

EXPERT OPINION

Several innovative protein engineering techniques and crystallographic methods have greatly accelerated SBDD, not only for already-resolved GPCRs but also for those structures which remain unclear. These technological advances are expected to enable the determination of GPCR-fragment complexes, making it practical to perform fragment-based drug discovery. This paves the way for a new era of GPCR-targeted drug discovery.

Insight into the binding mode and the structural features of the pyrimidine derivatives as human A2A adenosine receptor antagonists

The interaction of 278 monocyclic and bicyclic pyrimidine derivatives with human A2A adenosine receptor (AR) was investigated by employing molecular dynamics, thermodynamic analysis and three-dimensional quantitative structure-activity relationship (3D-QSAR) approaches. The binding analysis reveals that the pyrimidine derivatives are anchored in TM2, 3, 5, 6 and 7 of A2A AR by the aromatic stacking and hydrogen bonding interactions. The key residues involving Phe168, Glu169, and Asn253 stabilize the monocyclic and bicyclic cores of inhibitors. The thermodynamic analysis by molecular mechanics/Poisson Boltzmann surface area (MM-PBSA) approach also confirms the reasonableness of the binding modes. In addition, the ligand-/receptor-based comparative molecular similarity indices analysis (CoMSIA) models of high statistical significance were generated and the resulting contour maps correlate well with the structural features of the antagonists essential for high A2A AR affinity. A minor/bulky group with negative charge at C2/C6 of pyrimidine ring respectively enhances the activity for all these pyrimidine derivatives. Particularly, the higher electron density of the ring in the bicyclic derivatives, the more potent the antagonists. The obatined results might be helpful in rational design of novel candidate of A2A adenosine receptor antagonist for treatment of Parkinson's disease.

Homology models of melatonin receptors: challenges and recent advances

Melatonin exerts many of its actions through the activation of two G protein-coupled receptors (GPCRs), named MT1 and MT2. So far, a number of different MT1 and MT2 receptor homology models, built either from the prototypic structure of rhodopsin or from recently solved X-ray structures of druggable GPCRs, have been proposed. These receptor models differ in the binding modes hypothesized for melatonin and melatonergic ligands, with distinct patterns of ligand-receptor interactions and putative bioactive conformations of ligands. The receptor models will be described, and they will be discussed in light of the available information from mutagenesis experiments and ligand-based pharmacophore models. The ability of these ligand-receptor complexes to rationalize structure-activity relationships of known series of melatonergic compounds will be commented upon.

Structure-based virtual screening of MT2 melatonin receptor: influence of template choice and structural refinement

Developing GPCR homology models for structure-based virtual screening requires the choice of a suitable template and refinement of binding site residues. We explored this systematically for the MT2 melatonin receptor, with the aim to build a receptor homology model that is optimized for the enrichment of active melatoninergic ligands. A set of 12 MT2 melatonin receptor models was built using different GPCR X-ray structural templates and submitted to a virtual screening campaign on a set of compounds composed of 29 known melatonin receptor ligands and 2560 drug-like decoys. To evaluate the effect of including a priori information in receptor models, 12 representative melatonin receptor ligands were placed into the MT2 receptor models in poses consistent with known mutagenesis data and with assessed pharmacophore models. The receptor structures were then adapted to the ligands by induced-fit docking. Most of the 144 ligand-adapted MT2 receptor models showed significant improvements in screening enrichments compared to the unrefined homology models, with some template/refinement combinations giving excellent enrichment factors. The discriminating ability of the models was further tested on the 29 active ligands plus a set of 21 inactive or low-affinity compounds from the same chemical classes. Rotameric states of side chains for some residues, presumed to be involved in the binding process, were correlated with screening effectiveness, suggesting the existence of specific receptor conformations able to recognize active compounds. The top MT2 receptor model was able to identify 24 of 29 active ligands among the first 2% of the screened database. This work provides insights into the use of refined GPCR homology models for virtual screening.

X-ray structural information of GPCRs in drug design: what are the limitations and where do we go?

INTRODUCTION

In 2007, the X-ray structural determination of non-rhodopsin G-Protein coupled receptors (GPCRs), considered the most extensively targeted protein class for marketed drugs, commenced. With the relatively rapid availability of additional structures, an assessment of the progression made is needed in addition to the assessment of the understandings gleaned, deployment successes and forthcoming prospects.

AREAS COVERED

The author reviews the approaches and tools that have made it possible to determine the three dimensional structures of GPCRs using X-ray crystallography. Furthermore, the author describes the methods suited for crystallization of membrane bound GPCR proteins including the lipidic cubic phase and various protein modification approaches. The author also provides highlights, from the literature, of the structures determined to date including targets solved, the nature of the content provided (such as selectivity, activating vs. inactivating determinants) and how these structural features relate to drug design strategies.

EXPERT OPINION

The GPCR X-ray structures that have been so far determined have yielded significant information. This has presented dramatic evidence concerning their ability to impact the discovery of compounds through their action as traditional, orthosteric modulators. It is, however, noted that more challenging design strategies, such as identifying biased agonists and the use of sites remote from the orthosteric site for allosteric modulation, are still in their infancy.

Identifying subset errors in multiple sequence alignments

Multiple sequence alignment (MSA) accuracy is important, but there is no widely accepted method of judging the accuracy that different alignment algorithms give. We present a simple approach to detecting two types of error, namely block shifts and the misplacement of residues within a gap. Given a MSA, subsets of very similar sequences are generated through the use of a redundancy filter, typically using a 70-90% sequence identity cut-off. Subsets thus produced are typically small and degenerate, and errors can be easily detected even by manual examination. The errors, albeit minor, are inevitably associated with gaps in the alignment, and so the procedure is particularly relevant to homology modelling of protein loop regions. The usefulness of the approach is illustrated in the context of the universal but little known [K/R]KLH motif that occurs in intracellular loop 1 of G protein coupled receptors (GPCR); other issues relevant to GPCR modelling are also discussed.

Homology model-assisted elucidation of binding sites in GPCRs

G protein-coupled receptors (GPCRs) are important mediators of cell signaling and a major family of drug targets. Despite recent breakthroughs, experimental elucidation of GPCR structures remains a formidable challenge. Homology modeling of 3D structures of GPCRs provides a practical tool for elucidating the structural determinants governing the interactions of these important receptors with their ligands. The working model of the binding site can then be used for virtual screening of additional ligands that may fit this site, for determining and comparing specificity profiles of related receptors, and for structure-based design of agonists and antagonists. The current review presents the protocol and enumerates the steps for modeling and validating the residues involved in ligand binding. The main stages include (a) modeling the receptor structure using an automated fragment-based approach, (b) predicting potential binding pockets, (c) docking known binders, (d) analyzing predicted interactions and comparing with positions that have been shown to bind ligands in other receptors, (e) validating the structural model by mutagenesis.

Stabilised G protein-coupled receptors in structure-based drug design: a case study with adenosine A2A receptor

The first example of structure-based drug design with stabilised GPCRs has enabled the identification of a preclinical candidate for the treatment of Parkinson's disease.

G protein-coupled adenosine (P1) and P2Y receptors: ligand design and receptor interactions

The medicinal chemistry and pharmacology of the four subtypes of adenosine receptors (ARs) and the eight subtypes of P2Y receptors (P2YRs, activated by a range of purine and pyrimidine mono- and dinucleotides) has recently advanced significantly leading to selective ligands. X-ray crystallographic structures of both agonist- and antagonist-bound forms of the A(2A)AR have provided unprecedented three-dimensional detail concerning molecular recognition in the binding site and the conformational changes in receptor activation. It is apparent that this ubiquitous cell signaling system has implications for understanding and treating many diseases. ATP and other nucleotides are readily released from intracellular sources under conditions of injury and organ stress, such as hypoxia, ischemia, or mechanical stress, and through channels and vesicular release. Adenosine may be generated extracellularly or by cellular release. Therefore, depending on pathophysiological factors, in a given tissue, there is often a tonic activation of one or more of the ARs or P2YRs that can be modulated by exogenous agents for a beneficial effect. Thus, this field has provided fertile ground for pharmaceutical development, leading to clinical trials of selective receptor ligands as imaging agents or for conditions including cardiac arrhythmias, ischemia/reperfusion injury, diabetes, pain, thrombosis, Parkinson's disease, rheumatoid arthritis, psoriasis, dry eye disease, pulmonary diseases such as cystic fibrosis, glaucoma, cancer, chronic hepatitis C, and other diseases.

New insights for drug design from the X-ray crystallographic structures of G-protein-coupled receptors

Methodological advances in X-ray crystallography have made possible the recent solution of X-ray structures of pharmaceutically important G protein-coupled receptors (GPCRs), including receptors for biogenic amines, peptides, a nucleoside, and a sphingolipid. These high-resolution structures have greatly increased our understanding of ligand recognition and receptor activation. Conformational changes associated with activation common to several receptors entail outward movements of the intracellular side of transmembrane helix 6 (TM6) and movements of TM5 toward TM6. Movements associated with specific agonists or receptors have also been described [e.g., extracellular loop (EL) 3 in the A(2A) adenosine receptor]. The binding sites of different receptors partly overlap but differ significantly in ligand orientation, depth, and breadth of contact areas in TM regions and the involvement of the ELs. A current challenge is how to use this structural information for the rational design of novel potent and selective ligands. For example, new chemotypes were discovered as antagonists of various GPCRs by subjecting chemical libraries to in silico docking in the X-ray structures. The vast majority of GPCR structures and their ligand complexes are still unsolved, and no structures are known outside of family A GPCRs. Molecular modeling, informed by supporting information from site-directed mutagenesis and structure-activity relationships, has been validated as a useful tool to extend structural insights to related GPCRs and to analyze docking of other ligands in already crystallized GPCRs.

Structure-guided design of A(3) adenosine receptor-selective nucleosides: combination of 2-arylethynyl and bicyclo[3.1.0]hexane substitutions

(N)-Methanocarba adenosine 5'-methyluronamides containing known A(3) AR (adenosine receptor)-enhancing modifications, i.e., 2-(arylethynyl)adenine and N(6)-methyl or N(6)-(3-substituted-benzyl), were nanomolar full agonists of human (h) A(3)AR and highly selective (K(i) ∼0.6 nM, N(6)-methyl 2-(halophenylethynyl) analogues 13 and 14). Combined 2-arylethynyl-N(6)-3-chlorobenzyl substitutions preserved A(3)AR affinity/selectivity in the (N)-methanocarba series (e.g., 3,4-difluoro full agonist MRS5698 31, K(i) 3 nM, human and mouse A(3)) better than that for ribosides. Polyaromatic 2-ethynyl N(6)-3-chlorobenzyl analogues, such as potent linearly extended 2-p-biphenylethynyl MRS5679 34 (K(i) hA(3) 3.1 nM; A(1), A(2A), inactive) and fluorescent 1-pyrene adduct MRS5704 35 (K(i) hA(3) 68.3 nM), were conformationally rigid; receptor docking identified a large, mainly hydrophobic binding region. The vicinity of receptor-bound C2 groups was probed by homology modeling based on recent X-ray structure of an agonist-bound A(2A)AR, with a predicted helical rearrangement requiring an agonist-specific outward displacement of TM2 resembling opsin. Thus, the X-ray structure of related A(2A)AR is useful in guiding the design of new A(3)AR agonists.

Revisiting the homology modeling of G-protein coupled receptors: β1-adrenoceptor as an example

G-protein coupled receptors (GPCRs) are recognized to constitute the largest family of membrane proteins. Due to the disproportion in the quantity of crystal structures and their amino acid sequences, homology modeling contributes a reasonable and feasible approach to GPCR theoretical coordinates. With the brand new crystal structures resolved recently, herein we deliberated how to designate them as templates to carry out homology modeling in four aspects: (1) various sequence alignment methods; (2) protein weight matrix; (3) different sets of multiple templates; (4) active and inactive state of templates. The accuracy of models was evaluated by comparing the similarity of stereo conformation and molecular docking results between models and the experimental structure of Meleagris gallopavo β(1)-adrenergic receptor (Mg_Adrb1) that we desired to develop as an example. Our results proposed that: (1) Cobalt and MAFFT, two algorithms of sequence alignment, were suitable for single- and multiple-template modeling, respectively; (2) Blosum30 is applicable to align sequences in the case of low sequence identity; (3) multiple-template modeling is not always better than single-template one; (4) the state of template is an influential factor in simulating the GPCR structures as well.

Do crystal structures obviate the need for theoretical models of GPCRs for structure-based virtual screening?

Recent highly expected structural characterizations of agonist-bound and antagonist-bound beta-2 adrenoreceptor (β2AR) by X-ray crystallography have been widely regarded as critical advances to enable more effective structure-based discovery of GPCRs ligands. It appears that this very important development may have undermined many previous efforts to develop 3D theoretical models of GPCRs. To address this question directly, we have compared several historical β2AR models versus the inactive state and nanobody-stabilized active state of β2AR crystal structures in terms of their structural similarity and effectiveness of use in virtual screening for β2AR specific agonists and antagonists. Theoretical models, incluing both homology and de novo types, were collected from five different groups who have published extensively in the field of GPCRs modeling. All models were built before X-ray structures became available. In general, β2AR theoretical models differ significantly from the crystal structure in terms of TMH definition and the global packing. Nevertheless, surprisingly, several models afforded hit rates resulting from virtual screening of large chemical library enriched by known β2AR ligands that exceeded those using X-ray structures. The hit rates were particularly higher for agonists. Furthemore, the screening performance of models is associated with local structural quality, such as the RMSDs for binding pocket residues and the ability to capture accurately, most if not all critical protein/ligand interactions. These results suggest that carefully built models of GPCRs could capture critical chemical and structural features of the binding pocket, and thus may be even more useful for practical structure-based drug discovery than X-ray structures.

Signatures of natural selection in a primate bitter taste receptor

Bitter taste receptors (TAS2Rs) enable animals to detect and avoid toxins in the environment, including noxious defense compounds produced by plants. This suggests that TAS2Rs are under complex pressures from natural selection. To investigate these pressures, we examined signatures of selection in the primate TAS2R38 gene. Whole-gene (1,002 bp) sequences from 40 species representing all major primate taxa uncovered extensive variation. Nucleotide substitutions occurred at 448 positions, resulting in 201 amino acid changes. Two single-nucleotide deletions, one three-nucleotide in-frame deletion, and one premature stop codon were also observed. The rate of non-synonymous substitution (ω = dN/dS), was high in TAS2R38 (ω = 0.60) compared to other genes, but significantly lower than expected under neutrality (P = 4.0 × 10(-9)), indicating that purifying selection has maintained the basic structure of the receptor. However, differences were present among receptor subregions. Non-synonymous rates were significantly lower than expected in transmembrane domains (ω = 0.55, P = 1.18 × 10(-12)) and internal loops (ω = 0.51, P = 7.04 × 10(-5)), but not external loops (ω = 1.16, P = 0.53), and evidence of positive selection was found in external loop 2, which exhibited a high rate (ω = 2.53) consistent with rapid shifts in ligand targeting. These patterns point to a history of rapid yet constrained change in bitter taste responses in the course of primate evolution.

Structure of the adenosine A(2A) receptor in complex with ZM241385 and the xanthines XAC and caffeine

Methylxanthines, including caffeine and theophylline, are among the most widely consumed stimulant drugs in the world. These effects are mediated primarily via blockade of adenosine receptors. Xanthine analogs with improved properties have been developed as potential treatments for diseases such as Parkinson's disease. Here we report the structures of a thermostabilized adenosine A(2A) receptor in complex with the xanthines xanthine amine congener and caffeine, as well as the A(2A) selective inverse agonist ZM241385. The receptor is crystallized in the inactive state conformation as defined by the presence of a salt bridge known as the ionic lock. The complete third intracellular loop, responsible for G protein coupling, is visible consisting of extended helices 5 and 6. The structures provide new insight into the features that define the ligand binding pocket of the adenosine receptor for ligands of diverse chemotypes as well as the cytoplasmic regions that interact with signal transduction proteins.

A novel nonribose agonist, LUF5834, engages residues that are distinct from those of adenosine-like ligands to activate the adenosine A(2a) receptor

The recent publication of both the antagonist- and agonist-bound structures of the adenosine A(2A) receptor have revealed much about how a ligand may bind to a receptor and cause the conformational changes associated with agonist-mediated activation. In particular, the agonist-bound structure revealed key interactions between the ribose group of adenosine-derived agonists and amino acids in the receptor binding pocket that lead to receptor activation. However, agonists without a ribose group also exist, and we wondered whether such compounds occupy the same agonist binding site. Therefore we used a mutagenesis approach in this study to investigate the mode of binding of 2-amino-4-(4-hydroxyphenyl)- 6-(1H-imidazol-2-ylmethylsulfanyl)pyridine-3,5-dicarbonitrile (LUF5834), a potent partial agonist without a ribose moiety, compared with the adenosine-derived reference agonist 2-[p-(2-carboxyethyl)phenyl-ethylamino]-5'-N-ethylcarboxamidoadenosine (CGS21680). Mutation of the orthosteric residue Phe168 to alanine abrogated the function of both agonists. However, mutation to alanine of residues Thr88 and Ser277 shown by the crystal structures to interact with the ribose group of adenosine-like ligands had no effect on the potency of LUF5834. Furthermore, alanine mutation of Asn253, which makes a hydrogen-bonding interaction with the exocyclic nitrogen of the adenine ring, had minimal effect on LUF5834 affinity but removed agonist activity of this ligand. Mutation of other residues, such as the highly conserved Trp246 or Glu13, had significant deleterious effects on the function of CGS21680 but little effect on LUF5834. In summary, our findings suggest that this class of agonist interacts with distinct residues to activate the receptor compared with classic adenosine derived agonists.