Structurally Enabled Discovery of Adenosine A2A Receptor Antagonists

Therapeutic exploration potential of adenosine receptor antagonists through pharmacophore ligand-based modelling and pharmacokinetics studies against Parkinson disease

Parkinson's Disease (PD) is a neurodegenerative disorder that primarily affects persons aged 65 and older. It leads to a decline in motor function as a result of the buildup of abnormal protein deposits called Lewy bodies in the brain. Existing therapies exhibit restricted effectiveness and undesirable side effects. The objective was to discover potent medications that have demonstrated effectiveness in treating PD by employing computational methods. This work employed a comprehensive approach to evaluate 70 pyrimidine derivatives for their potential in treating PD. The evaluation involved the use of QSAR modelling, virtual screening, molecular docking, MD simulation, ADMET analysis, and antagonist inhibitor creation. Six compounds passed all the evaluation, while for MD simulation, carried out between the compound with best docking score and the reference drug, compound 57 was discovered to possess more stability compared to theophylline which is the reference drug, and it functions as a primary inhibitor of the adenosine A2A receptor. Additionally, the study determined that compound 57 satisfied the Rule of Five (Ro5) standards and exhibited robust physicochemical characteristics. The compound exhibited moderate to low levels of hERG inhibition. The conducted investigations highlighted promising outcomes of natural compounds that can orient towards the rational development of effective Parkinson's disease inhibitors.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-025-00305-9.

Novel Quinazoline Derivatives as Highly Effective A2A Adenosine Receptor Antagonists

The adenosine A2A receptor (A2AR) has been identified as a therapeutic target for treating neurodegenerative diseases and cancer. In recent years, we have highlighted the 2-aminoquinazoline heterocycle as an promising scaffold for designing new A2AR antagonists, exemplified by 6-bromo-4-(furan-2-yl)quinazolin-2-amine 1 (Ki (hA2AR) = 20 nM). Here, we report the synthesis of new 2-aminoquinazoline derivatives with substitutions at the C6- and C7-positions, and the introduction of aminoalkyl chains containing tertiary amines at the C2-position to enhance antagonist activity and solubility properties. Compound 5m showed a high affinity for hA2AR with a Ki value of 5 nM and demonstrated antagonist activity with an IC50 of 6 µM in a cyclic AMP assay. Introducing aminopentylpiperidine and 4-[(piperidin-1-yl)methyl]aniline substituents maintained the binding affinities (9x, Ki = 21 nM; 10d, Ki = 15 nM) and functional antagonist activities (9x, IC50 = 9 µM; 10d, IC50 = 5 µM) of the synthesized compounds while improving solubility. This study provides insights into the future development of A2AR antagonists for therapeutic applications.

Hit-to-Lead Optimization of Heterocyclic Carbonyloxycarboximidamides as Selective Antagonists at Human Adenosine A3 Receptor

Antagonism of the human adenosine A3 receptor (hA3R) has potential therapeutic application. Alchemical relative binding free energy calculations of K18 and K32 suggested that the combination of a 3-(2,6-dichlorophenyl)-isoxazolyl group with 2-pyridinyl at the ends of a carbonyloxycarboximidamide group should improve hA3R affinity. Of the 25 new analogues synthesized, 37 and 74 showed improved hA3R affinity compared to K18 (and K32). This was further improved through the addition of a bromine group to the 2-pyridinyl at the 5-position, generating compound 39. Alchemical relative binding free energy calculations, mutagenesis studies and MD simulations supported the compounds' binding pattern while suggesting that the bromine of 39 inserts deep into the hA3R orthosteric pocket, so highlighting the importance of rigidification of the carbonyloxycarboximidamide moiety. MD simulations highlighted the importance of rigidification of the carbonyloxycarboximidamide, while suggesting that the bromine of 39 inserts deep into the hA3R orthosteric pocket, which was supported through mutagenesis studies 39 also selectively antagonized endogenously expressed hA3R in nonsmall cell lung carcinoma cells, while pharmacokinetic studies indicated low toxicity enabling in vivo evaluation. We therefore suggest that 39 has potential for further development as a high-affinity hA3R antagonist.

Current Understanding of the Role of Adenosine Receptors in Cancer

Cancer, a complex array of diseases, involves the unbridled proliferation and dissemination of aberrant cells in the body, forming tumors that can infiltrate neighboring tissues and metastasize to distant sites. With over 200 types, each cancer has unique attributes, risks, and treatment avenues. Therapeutic options encompass surgery, chemotherapy, radiation therapy, hormone therapy, immunotherapy, targeted therapy, or a blend of these methods. Yet, these treatments face challenges like late-stage diagnoses, tumor diversity, severe side effects, drug resistance, targeted drug delivery hurdles, and cost barriers. Despite these hurdles, advancements in cancer research, encompassing biology, genetics, and treatment, have enhanced early detection methods, treatment options, and survival rates. Adenosine receptors (ARs), including A1, A2A, A2B, and A3 subtypes, exhibit diverse roles in cancer progression, sometimes promoting or inhibiting tumor growth depending on the receptor subtype, cancer type, and tumor microenvironment. Research on AR ligands has revealed promising anticancer effects in lab studies and animal models, hinting at their potential as cancer therapeutics. Understanding the intricate signaling pathways and interactions of adenosine receptors in cancer is pivotal for crafting targeted therapies that optimize benefits while mitigating drawbacks. This review delves into each adenosine receptor subtype's distinct roles and signaling pathways in cancer, shedding light on their potential as targets for improving cancer treatment outcomes.

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.

A2A adenosine receptor agonists, antagonists, inverse agonists and partial agonists

The Gs-coupled A2A adenosine receptor (A2AAR) has been explored extensively as a pharmaceutical target, which has led to numerous clinical trials. However, only one selective A2AAR agonist (regadenoson, Lexiscan) and one selective A2AAR antagonist (istradefylline, Nouriast) have been approved by the FDA, as a pharmacological agent for myocardial perfusion imaging (MPI) and as a cotherapy for Parkinson's disease (PD), respectively. Adenosine is widely used in MPI, as Adenoscan. Despite numerous unsuccessful clinical trials, medicinal chemical activity around A2AAR ligands has accelerated recently, particularly through structure-based drug design. New drug-like A2AAR antagonists for PD and cancer immunotherapy have been identified, and many clinical trials have ensued. For example, imaradenant (AZD4635), a compound that was designed computationally, based on A2AAR X-ray structures and biophysical mapping. Mixed A2AAR/A2BAR antagonists are also hopeful for cancer treatment. A2AAR antagonists may also have potential as neuroprotective agents for treatment of Alzheimer's disease.

The role of adenosine A2A receptors in Alzheimer's disease and tauopathies

Adenosine signals through four distinct G protein-coupled receptors that are located at various synapses, cell types and brain areas. Through them, adenosine regulates neuromodulation, neuronal signaling, learning and cognition as well as the sleep-wake cycle, all strongly impacted in neurogenerative disorders, among which Alzheimer's Disease (AD). AD is a complex form of cognitive deficits characterized by two pathological hallmarks: extracellular deposits of aggregated β-amyloid peptides and intraneuronal fibrillar aggregates of hyper- and abnormally phosphorylated Tau proteins. Both lesions contribute to the early dysfunction and loss of synapses which are strongly associated to the development of cognitive decline in AD patients. The present review focuses on the pathophysiological impact of the A_2ARs dysregulation observed in cognitive area from AD patients. We are reviewing not only evidence of the cellular changes in A_2AR levels in pathological conditions but also describe what is currently known about their consequences in term of synaptic plasticity, neuro-glial miscommunication and memory abilities. We finally summarize the proof-of-concept studies that support A_2AR as credible targets and the clinical interest to repurpose adenosine drugs for the treatment of AD and related disorders. This article is part of the Special Issue on "Purinergic Signaling: 50 years".

Structures of the arginine-vasopressin and oxytocin receptor signaling complexes

Arginine-vasopressin (AVP) and oxytocin (OT) are neurohypophysial hormones which share a high sequence and structure homology. These are two cyclic C-terminally amidated nonapeptides with different residues at position 3 and 8. In mammals, AVP and OT exert their multiple biological functions through a specific G protein-coupled receptor family: four receptors are identified, the V1a, V1b, V2 receptors (V1aR, V1bR and V2R) and the OT receptor (OTR). The chemical structure of AVP and OT was elucidated in the early 1950s. Thanks to X-ray crystallography and cryo-electron microscopy, it took however 70 additional years to determine the three-dimensional structures of the OTR and the V2R in complex with their natural agonist ligands and with different signaling partners, G proteins and β-arrestins. Today, the comparison of the different AVP/OT receptor structures gives structural insights into their orthosteric ligand binding pocket, their molecular mechanisms of activation, and their interfaces with canonical Gs, Gq and β-arrestin proteins. It also paves the way to future rational drug design and therapeutic compound development. Indeed, agonist, antagonist, biased agonist, or pharmacological chaperone analogues of AVP and OT are promising candidates to regulate different physiological functions and treat several pathologies.

Synthesis, QSAR modeling, and molecular docking of novel fused 7-deazaxanthine derivatives as adenosine A2A receptor antagonists

Predictive QSAR models for the search of new adenosine A_2A receptor antagonists were developed by using OCHEM platform. The predictive ability of the regression models has coefficient of determination q²  = 0.65-0.71 with cross-validation and independent test set. The inhibition activities of novel fused 7-deazaxanthine compounds were predicted by the developed QSAR models. A preparative method for the synthesis of pyrimido[5',4':4,5]pyrrolo[1,2-a][1,4]diazepine derivatives was developed, and 11 new adenosine A_2A receptor antagonists were obtained. Preliminary investigations into the toxicology of fused 7-deazaxanthine compounds toward commonly used model organism to assess toxicity invertebrate cladoceran D. magna were also described.

Dual A1/A3 Adenosine Receptor Antagonists: Binding Kinetics and Structure-Activity Relationship Studies Using Mutagenesis and Alchemical Binding Free Energy Calculations

Drugs targeting adenosine receptors (AR) can provide treatment for diseases. We report the identification of 7-(phenylamino)-pyrazolo[3,4-c]pyridines L2-L10, A15, and A17 as low-micromolar to low-nanomolar A₁R/A₃R dual antagonists, with 3-phenyl-5-cyano-7-(trimethoxyphenylamino)-pyrazolo[3,4-c]pyridine (A17) displaying the highest affinity at both receptors with a long residence time of binding, as determined using a NanoBRET-based assay. Two binding orientations of A17 produce stable complexes inside the orthosteric binding area of A₁R in molecular dynamics (MD) simulations, and we selected the most plausible orientation based on the agreement with alanine mutagenesis supported by affinity experiments. Interestingly, for drug design purposes, the mutation of L250^6.51 to alanine increased the binding affinity of A17 at A₁R. We explored the structure-activity relationships against A₁R using alchemical binding free energy calculations with the thermodynamic integration coupled with the MD simulation (TI/MD) method, applied on the whole G-protein-coupled receptor-membrane system, which showed a good agreement (r = 0.73) between calculated and experimental relative binding free energies.

Adenosine A2A receptor antagonists: from caffeine to selective non-xanthines

A long evolution of knowledge of the psychostimulant caffeine led in the 1960s to another purine natural product, adenosine and its A2A receptor. Adenosine is a short-lived autocrine/paracrine mediator that acts pharmacologically at four different adenosine receptors in a manner opposite to the pan-antagonist caffeine and serves as an endogenous allostatic regulator. Although detrimental in the developing brain, caffeine appears to be cerebroprotective in aging. Moderate caffeine consumption in adults, except in pregnancy, may also provide benefit in pain, diabetes, and kidney and liver disorders. Inhibition of A2A receptors is one of caffeine's principal effects and we now understand this interaction at the atomic level. The A2A receptor has become a prototypical example of utilizing high-resolution structures of GPCRs for the rational design of chemically diverse drug molecules. The previous focus on discovery of selective A2A receptor antagonists for neurodegenerative diseases has expanded to include immunotherapy for cancer, and clinical trials have ensued. LINKED ARTICLES: This article is part of a themed issue on Structure Guided Pharmacology of Membrane Proteins (BJP 75th Anniversary). To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v179.14/issuetoc.

Multifunctional Lipid Bilayer Nanocarriers for Cancer Immunotherapy in Heterogeneous Tumor Microenvironments, Combining Immunogenic Cell Death Stimuli with Immune Modulatory Drugs

In addition to the contribution of cancer cells, the solid tumor microenvironment (TME) has a critical role in determining tumor expansion, antitumor immunity, and the response to immunotherapy. Understanding the details of the complex interplay between cancer cells and components of the TME provides an unprecedented opportunity to explore combination therapy for intervening in the immune landscape to improve immunotherapy outcome. One approach is the introduction of multifunctional nanocarriers, capable of delivering drug combinations that provide immunogenic stimuli for improvement of tumor antigen presentation, contemporaneous with the delivery of coformulated drug or synthetic molecules that provide immune danger signals or interfere in immune-escape, immune-suppressive, and T-cell exclusion pathways. This forward-looking review will discuss the use of lipid-bilayer-encapsulated liposomes and mesoporous silica nanoparticles for combination immunotherapy of the heterogeneous immune landscapes in pancreatic ductal adenocarcinoma and triple-negative breast cancer. We describe how the combination of remote drug loading and lipid bilayer encapsulation is used for the synthesis of synergistic drug combinations that induce immunogenic cell death, interfere in the PD-1/PD-L1 axis, inhibit the indoleamine-pyrrole 2,3-dioxygenase (IDO-1) immune metabolic pathway, restore spatial access to activated T-cells to the cancer site, or reduce the impact of immunosuppressive stromal components. We show how an integration of current knowledge and future discovery can be used for a rational approach to nanoenabled cancer immunotherapy.

Deciphering conformational selectivity in the A2A adenosine G protein-coupled receptor by free energy simulations

Transmembranal G Protein-Coupled Receptors (GPCRs) transduce extracellular chemical signals to the cell, via conformational change from a resting (inactive) to an active (canonically bound to a G-protein) conformation. Receptor activation is normally modulated by extracellular ligand binding, but mutations in the receptor can also shift this equilibrium by stabilizing different conformational states. In this work, we built structure-energetic relationships of receptor activation based on original thermodynamic cycles that represent the conformational equilibrium of the prototypical A_2A adenosine receptor (AR). These cycles were solved with efficient free energy perturbation (FEP) protocols, allowing to distinguish the pharmacological profile of different series of A_2AAR agonists with different efficacies. The modulatory effects of point mutations on the basal activity of the receptor or on ligand efficacies could also be detected. This methodology can guide GPCR ligand design with tailored pharmacological properties, or allow the identification of mutations that modulate receptor activation with potential clinical implications.

The design of new ligands as chemical modulators of G protein-coupled receptors (GPCRs) has benefited considerably during the last years of advances in both the structural and computational biology disciplines. Within the last area, the use of free energy calculation methods has arisen as a computational tool to predict ligand affinities to explain structure-affinity relationships and guide lead optimization campaigns. However, our comprehension of the structural determinants of ligands with different pharmacological profile is scarce, and knowledge of the chemical modifications associated with an agonistic or antagonistic profile would be extremely valuable. We herein report an original implementation of the thermodynamic cycles associated with free energy perturbation (FEP) simulations, to mimic the conformational equilibrium between active and inactive GPCRs, and establish a framework to describe pharmacological profiles as a function of the ligands selectivity for a given receptor conformation. The advantage of this method resides into its simplicity of use, and the only consideration of active and inactive conformations of the receptor, with no simulation of the transitions between them. This model can accurately predict the pharmacological profile of series of full and partial agonists as opposed to antagonists of the A_2A adenosine receptor, and moreover, how certain mutations associated with modulation of basal activity can influence this pharmacological profiles, which enables our understanding of such clinically relevant mutations.

From structure to clinic: Design of a muscarinic M1 receptor agonist with potential to treatment of Alzheimer's disease

Current therapies for Alzheimer's disease seek to correct for defective cholinergic transmission by preventing the breakdown of acetylcholine through inhibition of acetylcholinesterase, these however have limited clinical efficacy. An alternative approach is to directly activate cholinergic receptors responsible for learning and memory. The M1-muscarinic acetylcholine (M1) receptor is the target of choice but has been hampered by adverse effects. Here we aimed to design the drug properties needed for a well-tolerated M1-agonist with the potential to alleviate cognitive loss by taking a stepwise translational approach from atomic structure, cell/tissue-based assays, evaluation in preclinical species, clinical safety testing, and finally establishing activity in memory centers in humans. Through this approach, we rationally designed the optimal properties, including selectivity and partial agonism, into HTL9936-a potential candidate for the treatment of memory loss in Alzheimer's disease. More broadly, this demonstrates a strategy for targeting difficult GPCR targets from structure to clinic.

Identification of V6.51L as a selectivity hotspot in stereoselective A2B adenosine receptor antagonist recognition

The four adenosine receptors (ARs) A₁AR, A_2AAR, A_2BAR_, and A₃AR are G protein-coupled receptors (GPCRs) for which an exceptional amount of experimental and structural data is available. Still, limited success has been achieved in getting new chemical modulators on the market. As such, there is a clear interest in the design of novel selective chemical entities for this family of receptors. In this work, we investigate the selective recognition of ISAM-140, a recently reported A_2BAR reference antagonist. A combination of semipreparative chiral HPLC, circular dichroism and X-ray crystallography was used to separate and unequivocally assign the configuration of each enantiomer. Subsequently affinity evaluation for both A_2A and A_2B receptors demonstrate the stereospecific and selective recognition of (S)-ISAM140 to the A_2BAR. The molecular modeling suggested that the structural determinants of this selectivity profile would be residue V250^6.51 in A_2BAR, which is a leucine in all other ARs including the closely related A_2AAR. This was herein confirmed by radioligand binding assays and rigorous free energy perturbation (FEP) calculations performed on the L249V^6.51 mutant A_2AAR receptor. Taken together, this study provides further insights in the binding mode of these A_2BAR antagonists, paving the way for future ligand optimization.

Recent Developments in New Therapeutic Agents against Alzheimer and Parkinson Diseases: In-Silico Approaches

Neurodegenerative diseases (ND), including Alzheimer's (AD) and Parkinson's Disease (PD), are becoming increasingly more common and are recognized as a social problem in modern societies. These disorders are characterized by a progressive neurodegeneration and are considered one of the main causes of disability and mortality worldwide. Currently, there is no existing cure for AD nor PD and the clinically used drugs aim only at symptomatic relief, and are not capable of stopping neurodegeneration. Over the last years, several drug candidates reached clinical trials phases, but they were suspended, mainly because of the unsatisfactory pharmacological benefits. Recently, the number of compounds developed using in silico approaches has been increasing at a promising rate, mainly evaluating the affinity for several macromolecular targets and applying filters to exclude compounds with potentially unfavorable pharmacokinetics. Thus, in this review, an overview of the current therapeutics in use for these two ND, the main targets in drug development, and the primary studies published in the last five years that used in silico approaches to design novel drug candidates for AD and PD treatment will be presented. In addition, future perspectives for the treatment of these ND will also be briefly discussed.

A unique ligand-steered strategy for CC chemokine receptor 2 homology modeling to facilitate structure-based virtual screening

CC chemokine receptor 2 (CCR2) antagonists that disrupt CCR2/MCP-1 interaction are expected to treat a variety of inflammatory and autoimmune diseases. The lack of CCR2 crystal structure limits the application of structure-based drug design (SBDD) to this target. Although a few three-dimensional theoretical models have been reported, their accuracy remains to be improved in terms of templates and modeling approaches. In this study, we developed a unique ligand-steered strategy for CCR2 homology modeling. It starts with an initial model based on the X-ray structure of the closest homolog so far, that is, CXCR4. Then, it uses Elastic Network Normal Mode Analysis (EN-NMA) and flexible docking (FD) by AutoDock Vina software to generate ligand-induced fit models. It selects optimal model(s) as well as scoring function(s) via extensive evaluation of model performance based on a unique benchmarking set constructed by our in-house tool, that is, MUBD-DecoyMaker. The model of 81_04 presents the optimal enrichment when combined with the scoring function of PMF04, and the proposed binding mode between CCR2 and Teijin lead by this model complies with the reported mutagenesis data. To highlight the advantage of our strategy, we compared it with the only reported ligand-steered strategy for CCR2 homology modeling, that is, Discovery Studio/Ligand Minimization. Lastly, we performed prospective virtual screening based on 81_04 and CCR2 antagonist bioassay. The identification of two hit compounds, that is, E859-1281 and MolPort-007-767-945, validated the efficacy of our model and the ligand-steered strategy.

Crystal Structure and Subsequent Ligand Design of a Nonriboside Partial Agonist Bound to the Adenosine A2A Receptor

In this study, we determined the crystal structure of an engineered human adenosine A_2A receptor bound to a partial agonist and compared it to structures cocrystallized with either a full agonist or an antagonist/inverse agonist. The interaction between the partial agonist, belonging to a class of dicyanopyridines, and amino acids in the ligand binding pocket inspired us to develop a small library of derivatives and assess their affinity in radioligand binding studies and potency and intrinsic activity in a functional, label-free, intact cell assay. It appeared that some of the derivatives retained the partial agonist profile, whereas other ligands turned into inverse agonists. We rationalized this remarkable behavior with additional computational docking studies.

Free Energy Calculations for Protein-Ligand Binding Prediction

Computational prediction of protein-ligand binding involves initial determination of the binding mode and subsequent evaluation of the strength of the protein-ligand interactions, which directly correlates with ligand binding affinities. As a consequence of increasing computer power, rigorous approaches to calculate protein-ligand binding affinities, such as free energy perturbation (FEP) methods, are becoming an essential part of the toolbox of computer-aided drug design. In this chapter, we provide a general overview of these methods and introduce the QFEP modules, which are open-source API workflows based on our molecular dynamics (MD) package Q. The module QligFEP allows estimation of relative binding affinities along ligand series, while QresFEP is a module to estimate binding affinity shifts caused by single-point mutations of the protein. We herein provide guidelines for the use of each of these modules based on data extracted from ligand-design projects. While these modules are stand-alone, the combined use of the two workflows in a drug-design project yields complementary perspectives of the ligand binding problem, providing two sides of the same coin. The selected case studies illustrate how to use QFEP to approach the two key questions associated with ligand binding prediction: identifying the most favorable binding mode from different alternatives and establishing structure-affinity relationships that allow the rational optimization of hit compounds.

Purinergic Signaling: Impact of GPCR Structures on Rational Drug Design

The purinergic signaling system includes membrane-bound receptors for extracellular purines and pyrimidines, and enzymes/transporters that regulate receptor activation by endogenous agonists. Receptors include: adenosine (A1 , A2A , A2B, and A3 ) and P2Y (P2Y1 , P2Y2 , P2Y4 , P2Y6 , P2Y11 , P2Y12 , P2Y13 , and P2Y14 ) receptors (all GPCRs), as well as P2X receptors (ion channels). Receptor activation, especially accompanying physiological stress or damage, creates a temporal sequence of signaling to counteract this stress and either mobilize (P2Rs) or suppress (ARs) immune responses. Thus, modulation of this large signaling family has broad potential for treating chronic diseases. Experimentally determined structures represent each of the three receptor families. We focus on selective purinergic agonists (A1 , A3 ), antagonists (A3 , P2Y14 ), and allosteric modulators (P2Y1 , A3 ). Examples of applying structure-based design, including the rational modification of known ligands, are presented for antithrombotic P2Y1 R antagonists and anti-inflammatory P2Y14 R antagonists and A3 AR agonists. A3 AR agonists are a potential, nonaddictive treatment for chronic neuropathic pain.

Illuminating the Path to Target GPCR Structures and Functions

G-Protein-coupled receptors (GPCRs) are ubiquitous within eukaryotes, responsible for a wide array of physiological and pathological processes. Indeed, the fact that they are the most drugged target in the human genome is indicative of their importance. Despite the clear interest in GPCRs, most information regarding their activity has been so far obtained by analyzing the response from a "bulk medium". As such, this Perspective summarizes some of the common methods for this indirect observation. Nonetheless, by inspecting approaches applying super-resolution imaging, we argue that imaging is perfectly situated to obtain more detailed structural and spatial information, assisting in the development of new GPCR-targeted drugs and clinical strategies. The benefits of direct optical visualization of GPCRs are analyzed in the context of potential future directions in the field.

X-Ray Crystallography and Free Energy Calculations Reveal the Binding Mechanism of A2A Adenosine Receptor Antagonists

We present a robust protocol based on iterations of free energy perturbation (FEP) calculations, chemical synthesis, biophysical mapping and X-ray crystallography to reveal the binding mode of an antagonist series to the A2A adenosine receptor (AR). Eight A2A AR binding site mutations from biophysical mapping experiments were initially analyzed with sidechain FEP simulations, performed on alternate binding modes. The results distinctively supported one binding mode, which was subsequently used to design new chromone derivatives. Their affinities for the A2A AR were experimentally determined and investigated through a cycle of ligand-FEP calculations, validating the binding orientation of the different chemical substituents proposed. Subsequent X-ray crystallography of the A2A AR with a low and a high affinity chromone derivative confirmed the predicted binding orientation. The new molecules and structures here reported were driven by free energy calculations, and provide new insights on antagonist binding to the A2A AR, an emerging target in immuno-oncology.

How Do Molecular Dynamics Data Complement Static Structural Data of GPCRs

G protein-coupled receptors (GPCRs) are implicated in nearly every physiological process in the human body and therefore represent an important drug targeting class. Advances in X-ray crystallography and cryo-electron microscopy (cryo-EM) have provided multiple static structures of GPCRs in complex with various signaling partners. However, GPCR functionality is largely determined by their flexibility and ability to transition between distinct structural conformations. Due to this dynamic nature, a static snapshot does not fully explain the complexity of GPCR signal transduction. Molecular dynamics (MD) simulations offer the opportunity to simulate the structural motions of biological processes at atomic resolution. Thus, this technique can incorporate the missing information on protein flexibility into experimentally solved structures. Here, we review the contribution of MD simulations to complement static structural data and to improve our understanding of GPCR physiology and pharmacology, as well as the challenges that still need to be overcome to reach the full potential of this technique.

Adenosine A2A Receptor Antagonists for Cancer Immunotherapy

Currently, the most promising therapeutic modality for cancer treatment is the blockade of immune checkpoint pathways, which has revolutionized cancer therapy in the past 15 years. Strategies targeting and modulating adenosine A_2A receptor (A_2AR), an emerging alternative immune checkpoint, have shown the potential to produce significant therapeutic effects. In this review, we describe the immunosuppressive activities of A_2AR and A_2BR in the tumor microenvironment (TME), followed by a summary and discussion of the structure-activity relationship (SAR) of the A_2AR (and dual A_2AR/A_2BR) antagonists that have been experimentally confirmed to exert oncoimmunological effects. This review also provides an update on the compounds under clinical evaluation and insights into the ligand binding modes of the receptor.

Agonists and Antagonists for Purinergic Receptors

Membrane receptors that are activated by the purine nucleoside adenosine (adenosine receptors) or by purine or pyrimidine nucleotides (P2Y and P2X receptors) transduce extracellular signals to the cytosol. They play important roles in physiology and disease. The G protein-coupled adenosine receptors comprise four subtypes: A₁, A_2A, A_2B, and A₃. The G-protein-coupled P2Y receptors are subdivided into eight subtypes: P2Y₁, P2Y₂, P2Y₄, P2Y₆, P2Y₁₁, P2Y₁₂, P2Y₁₃, and P2Y₁₄, while the P2X receptors represent ATP-gated homomeric or heteromeric ion channels consisting of three subunits; the most important subunits are P2X1, P2X2, P2X3, P2X4, and P2X7. This chapter provides guidance for selecting suitable tool compounds for studying these large and important purine receptor families.

The In Silico Drug Discovery Toolbox: Applications in Lead Discovery and Optimization

BACKGROUND

Discovery and development of a new drug is a long lasting and expensive journey that takes around 20 years from starting idea to approval and marketing of new medication. Despite R&D expenditures have been constantly increasing in the last few years, the number of new drugs introduced into market has been steadily declining. This is mainly due to preclinical and clinical safety issues, which still represent about 40% of drug discontinuation. To cope with this issue, a number of in silico techniques are currently being used for an early stage evaluation/prediction of potential safety issues, allowing to increase the drug-discovery success rate and reduce costs associated with the development of a new drug.

METHODS

In the present review, we will analyse the early steps of the drug-discovery pipeline, describing the sequence of steps from disease selection to lead optimization and focusing on the most common in silico tools used to assess attrition risks and build a mitigation plan.

RESULTS

A comprehensive list of widely used in silico tools, databases, and public initiatives that can be effectively implemented and used in the drug discovery pipeline has been provided. A few examples of how these tools can be problem-solving and how they may increase the success rate of a drug discovery and development program have been also provided. Finally, selected examples where the application of in silico tools had effectively contributed to the development of marketed drugs or clinical candidates will be given.

CONCLUSION

The in silico toolbox finds great application in every step of early drug discovery: (i) target identification and validation; (ii) hit identification; (iii) hit-to-lead; and (iv) lead optimization. Each of these steps has been described in details, providing a useful overview on the role played by in silico tools in the decision-making process to speed-up the discovery of new drugs.

Molecular Dynamics Simulations of Adenosine Receptors: Advances, Applications and Trends

:

Adenosine receptors (ARs) are transmembrane proteins that belong to the G protein-coupled receptors (GPCRs) superfamily and mediate the biological functions of adenosine. To date, four AR subtypes are known, namely A1, A2A, A2B and A3 that exhibit different signaling pathways, tissue localization, and mechanisms of activation. Moreover, the widespread ARs and their implication in numerous physiological and pathophysiological conditions had made them pivotal therapeutic targets for developing clinically effective agents.

:

The crystallographic success in identifying the 3D crystal structures of A2A and A1 ARs has dramatically enriched our understanding of their structural and functional properties such as ligand binding and signal transduction. This, in turn, has provided a structural basis for a larger contribution of computational methods, particularly molecular dynamics (MD) simulations, toward further investigation of their molecular properties and designing bioactive ligands with therapeutic potential. MD simulation has been proved to be an invaluable tool in investigating ARs and providing answers to some critical questions. For example, MD has been applied in studying ARs in terms of ligand-receptor interactions, molecular recognition, allosteric modulations, dimerization, and mechanisms of activation, collectively aiding in the design of subtype selective ligands.

:

In this review, we focused on the advances and different applications of MD simulations utilized to study the structural and functional aspects of ARs that can foster the structure-based design of drug candidates. In addition, relevant literature was briefly discussed which establishes a starting point for future advances in the field of drug discovery to this pivotal group of drug targets.

The lipid phase preference of the adenosine A2A receptor depends on its ligand binding state

Giant unilamellar protein vesicles (GUPs) were formed with the adenosine A2A receptor (A2AR) incorporated in the lipid bilayer and protein partitioning into the liquid ordered and liquid disordered phases was observed. When no ligand is bound, A2AR partitions preferentially into the liquid disordered phase of GUPs, while ligand-bound A2AR partitions into the liquid ordered phase.

Development of Adenosine A2A Receptor Antagonists for the Treatment of Parkinson's Disease: A Recent Update and Challenge

Parkinson's disease (PD) is a neurodegenerative disease with significant unmet medical needs. The current dopamine-centered treatments aim to restore motor functions of patients without slowing the disease progression. Long-term usage of these drugs is associated with diminished efficacy, motor fluctuation, and dyskinesia. Furthermore, the nonmotor features associated with PD such as sleep disorder, pain, and psychiatric symptoms are poorly addressed by the dopaminergic treatments. Adenosine receptor A_2A antagonists have emerged as potential treatment for PD in the past decade. Here we summarize the recent work (2015-2018) on adenosine receptor A_2A antagonists and discuss the challenge and opportunity for the treatment of PD.

Ultra-large library docking for discovering new chemotypes

Despite intense interest in expanding chemical space, libraries containing hundreds-of-millions to billions of diverse molecules have remained inaccessible. Here we investigate structure-based docking of 170 million make-on-demand compounds from 130 well-characterized reactions. The resulting library is diverse, representing over 10.7 million scaffolds that are otherwise unavailable. For each compound in the library, docking against AmpC β-lactamase (AmpC) and the D4 dopamine receptor were simulated. From the top-ranking molecules, 44 and 549 compounds were synthesized and tested for interactions with AmpC and the D4 dopamine receptor, respectively. We found a phenolate inhibitor of AmpC, which revealed a group of inhibitors without known precedent. This molecule was optimized to 77 nM, which places it among the most potent non-covalent AmpC inhibitors known. Crystal structures of this and other AmpC inhibitors confirmed the docking predictions. Against the D4 dopamine receptor, hit rates fell almost monotonically with docking score, and a hit-rate versus score curve predicted that the library contained 453,000 ligands for the D4 dopamine receptor. Of 81 new chemotypes discovered, 30 showed submicromolar activity, including a 180-pM subtype-selective agonist of the D4 dopamine receptor.

Pharmacology of Adenosine Receptors: The State of the Art

Adenosine is a ubiquitous endogenous autacoid whose effects are triggered through the enrollment of four G protein-coupled receptors: A₁, A_2A, A_2B, and A₃. Due to the rapid generation of adenosine from cellular metabolism, and the widespread distribution of its receptor subtypes in almost all organs and tissues, this nucleoside induces a multitude of physiopathological effects, regulating central nervous, cardiovascular, peripheral, and immune systems. It is becoming clear that the expression patterns of adenosine receptors vary among cell types, lending weight to the idea that they may be both markers of pathologies and useful targets for novel drugs. This review offers an overview of current knowledge on adenosine receptors, including their characteristic structural features, molecular interactions and cellular functions, as well as their essential roles in pain, cancer, and neurodegenerative, inflammatory, and autoimmune diseases. Finally, we highlight the latest findings on molecules capable of targeting adenosine receptors and report which stage of drug development they have reached.

GPCR drug discovery: integrating solution NMR data with crystal and cryo-EM structures

The 826 G protein-coupled receptors (GPCRs) in the human proteome regulate key physiological processes and thus have long been attractive drug targets. With the crystal structures of more than 50 different human GPCRs determined over the past decade, an initial platform for structure-based rational design has been established for drugs that target GPCRs, which is currently being augmented with cryo-electron microscopy (cryo-EM) structures of higher-order GPCR complexes. Nuclear magnetic resonance (NMR) spectroscopy in solution is one of the key approaches for expanding this platform with dynamic features, which can be accessed at physiological temperature and with minimal modification of the wild-type GPCR covalent structures. Here, we review strategies for the use of advanced biochemistry and NMR techniques with GPCRs, survey projects in which crystal or cryo-EM structures have been complemented with NMR investigations and discuss the impact of this integrative approach on GPCR biology and drug discovery.

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.

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.

Exploring G Protein-Coupled Receptors (GPCRs) Ligand Space via Cheminformatics Approaches: Impact on Rational Drug Design

The primary goal of rational drug discovery is the identification of selective ligands which act on single or multiple drug targets to achieve the desired clinical outcome through the exploration of total chemical space. To identify such desired compounds, computational approaches are necessary in predicting their drug-like properties. G Protein-Coupled Receptors (GPCRs) represent one of the largest and most important integral membrane protein families. These receptors serve as increasingly attractive drug targets due to their relevance in the treatment of various diseases, such as inflammatory disorders, metabolic imbalances, cardiac disorders, cancer, monogenic disorders, etc. In the last decade, multitudes of three-dimensional (3D) structures were solved for diverse GPCRs, thus referring to this period as the "golden age for GPCR structural biology." Moreover, accumulation of data about the chemical properties of GPCR ligands has garnered much interest toward the exploration of GPCR chemical space. Due to the steady increase in the structural, ligand, and functional data of GPCRs, several cheminformatics approaches have been implemented in its drug discovery pipeline. In this review, we mainly focus on the cheminformatics-based paradigms in GPCR drug discovery. We provide a comprehensive view on the ligand- and structure-based cheminformatics approaches which are best illustrated via GPCR case studies. Furthermore, an appropriate combination of ligand-based knowledge with structure-based ones, i.e., integrated approach, which is emerging as a promising strategy for cheminformatics-based GPCR drug design is also discussed.

Visualizing Dynamics of Cell Signaling In Vivo with a Phase Separation-Based Kinase Reporter

Visualizing dynamics of kinase activity in living animals is essential for mechanistic understanding of cell and developmental biology. We describe GFP-based kinase reporters that phase-separate upon kinase activation via multivalent protein-protein interactions, forming intensively fluorescent droplets. Called SPARK (separation of phases-based activity reporter of kinase), these reporters have large dynamic range (fluorescence change), high brightness, fast kinetics, and are reversible. The SPARK-based protein kinase A (PKA) reporter reveals oscillatory dynamics of PKA activities upon G protein-coupled receptor activation. The SPARK-based extracellular signal-regulated kinase (ERK) reporter unveils transient dynamics of ERK activity during tracheal metamorphosis in live Drosophila. Because of intensive brightness and simple signal pattern, SPARKs allow easy examination of kinase signaling in living animals in a qualitative way. The modular design of SPARK will facilitate development of reporters of other kinases.

A perspective on multi-target drug discovery and design for complex diseases

Diseases of infection, of neurodegeneration (such as Alzheimer’s and Parkinson’s diseases), and of malignancy (cancers) have complex and varied causative factors. Modern drug discovery has the power to identify potential modulators for multiple targets from millions of compounds. Computational approaches allow the determination of the association of each compound with its target before chemical synthesis and biological testing is done. These approaches depend on the prior identification of clinically and biologically validated targets. This Perspective will focus on the molecular and computational approaches that underpin drug design by medicinal chemists to promote understanding and collaboration with clinical scientists.

High-throughput in situ X-ray screening of and data collection from protein crystals at room temperature and under cryogenic conditions

Protein crystallography has significantly advanced in recent years, with in situ data collection, in which crystals are placed in the X-ray beam within their growth medium, being a major point of focus. In situ methods eliminate the need to harvest crystals, a previously unavoidable drawback, particularly for often small membrane-protein crystals. Here, we present a protocol for the high-throughput in situ X-ray screening of and data collection from soluble and membrane-protein crystals at room temperature (20-25°C) and under cryogenic conditions. The Mylar in situ method uses Mylar-based film sandwich plates that are inexpensive, easy to make, and compatible with automated imaging, and that show very low background scattering. They support crystallization in microbatch and vapor-diffusion modes, as well as in lipidic cubic phases (LCPs). A set of 3D-printed holders for differently sized patches of Mylar sandwich films makes the method robust and versatile, allows for storage and shipping of crystals, and enables automated mounting at synchrotrons, as well as goniometer-based screening and data collection. The protocol covers preparation of in situ plates and setup of crystallization trials; 3D printing and assembly of holders; opening of plates, isolation of film patches containing crystals, and loading them onto holders; basic screening and data-collection guidelines; and unloading of holders, as well as reuse and recycling of them. In situ plates are prepared and assembled in 1 h; holders are 3D-printed and assembled in ≤90 min; and an in situ plate is opened, and a film patch containing crystals is isolated and loaded onto a holder in 5 min.

Computational Methods Used in Hit-to-Lead and Lead Optimization Stages of Structure-Based Drug Discovery

GPCR modeling approaches are widely used in the hit-to-lead (H2L) and lead optimization (LO) stages of drug discovery. The aims of these modeling approaches are to predict the 3D structures of the receptor-ligand complexes, to explore the key interactions between the receptor and the ligand and to utilize these insights in the design of new molecules with improved binding, selectivity or other pharmacological properties. In this book chapter, we present a brief survey of key computational approaches integrated with hierarchical GPCR modeling protocol (HGMP) used in hit-to-lead (H2L) and in lead optimization (LO) stages of structure-based drug discovery (SBDD). We outline the differences in modeling strategies used in H2L and LO of SBDD and illustrate how these tools have been applied in three drug discovery projects.

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.