Biophysical fragment screening of the β1-adrenergic receptor: identification of high affinity arylpiperazine leads using structure-based drug design

Ligand Binding Affinity Prediction for Membrane Proteins with Alchemical Free Energy Calculation Methods

Alchemical relative binding free energy (ΔΔG) calculations have shown high accuracy in predicting ligand binding affinity and have been used as important tools in computer-aided drug discovery and design. However, there has been limited research on the application of ΔΔG methods to membrane proteins despite the fact that these proteins represent a significant proportion of drug targets, play crucial roles in biological processes, and are implicated in numerous diseases. In this study, to predict the binding affinity of ligands to G protein-coupled receptors (GPCRs), we employed two ΔΔG calculation methods: thermodynamic integration (TI) with AMBER and the alchemical transfer method (AToM) with OpenMM. We calculated ΔΔG values for 53 transformations involving four class A GPCRs and evaluated the performance of AMBER-TI and AToM-OpenMM. In addition, we conducted tests using different numbers of windows and varying simulation times to achieve reliable ΔΔG results and to optimize resource utilization. Overall, both AMBER-TI and AToM-OpenMM show good agreement with the experimental data. Our results validate the applicability of AMBER-TI and AToM-OpenMM for optimization of lead compounds targeting membrane proteins.

G Protein-Coupled Receptor-Ligand Pose and Functional Class Prediction

G protein-coupled receptor (GPCR) transmembrane protein family members play essential roles in physiology. Numerous pharmaceuticals target GPCRs, and many drug discovery programs utilize virtual screening (VS) against GPCR targets. Improvements in the accuracy of predicting new molecules that bind to and either activate or inhibit GPCR function would accelerate such drug discovery programs. This work addresses two significant research questions. First, do ligand interaction fingerprints provide a substantial advantage over automated methods of binding site selection for classical docking? Second, can the functional status of prospective screening candidates be predicted from ligand interaction fingerprints using a random forest classifier? Ligand interaction fingerprints were found to offer modest advantages in sampling accurate poses, but no substantial advantage in the final set of top-ranked poses after scoring, and, thus, were not used in the generation of the ligand-receptor complexes used to train and test the random forest classifier. A binary classifier which treated agonists, antagonists, and inverse agonists as active and all other ligands as inactive proved highly effective in ligand function prediction in an external test set of GPR31 and TAAR2 candidate ligands with a hit rate of 82.6% actual actives within the set of predicted actives.

Identification of a Novel Subtype-Selective α1B-Adrenoceptor Antagonist

α1A-, α1B-, and α1D-adrenoceptors (α1-ARs) are members of the adrenoceptor G protein-coupled receptor family that are activated by adrenaline (epinephrine) and noradrenaline. α1-ARs are clinically targeted using antagonists that have minimal subtype selectivity, such as prazosin and tamsulosin, to treat hypertension and benign prostatic hyperplasia, respectively. Abundant expression of α1-ARs in the heart and central nervous system (CNS) makes these receptors potential targets for the treatment of cardiovascular and CNS disorders, such as heart failure, epilepsy, and Alzheimer's disease. Our understanding of the precise physiological roles of α1-ARs, however, and their involvement in disease has been hindered by the lack of sufficiently subtype-selective tool compounds, especially for α1B-AR. Here, we report the discovery of 4-[(2-hydroxyethyl)amino]-6-methyl-2H-chromen-2-one (Cpd1), as an α1B-AR antagonist that has 10-15-fold selectivity over α1A-AR and α1D-AR. Through computational and site-directed mutagenesis studies, we have identified the binding site of Cpd1 in α1B-AR and propose the molecular basis of α1B-AR selectivity, where the nonconserved V19745.52 residue plays a major role, with contributions from L3146.55 within the α1B-AR pocket. By exploring the structure-activity relationships of Cpd1 at α1B-AR, we have also identified 3-[(cyclohexylamino)methyl]-6-methylquinolin-2(1H)-one (Cpd24), which has a stronger binding affinity than Cpd1, albeit with reduced selectivity for α1B-AR. Cpd1 and Cpd24 represent potential leads for α1B-AR-selective drug discovery and novel tool molecules to further study the physiology of α1-ARs.

A chromatographic method for determining the interaction between a drug and two target proteins by fabricating a dual-heterogeneous surface

Characterization of the drug-target interactions is pivotal throughout the whole procedure of drug development. Most of the current assays, particularly, chromatographic methods lack the capacity to reveal drug adsorption on the muti-target surface. To this end, we derived a reliable and workable mathematical equation for revealing drug bindings to dual targets on the heterogeneous surface starting from the mass balance equation. The derivatization relied on the correlation of drug injection amounts with their retention factors. Experimental validation was performed by determining the binding parameters of three canonical drugs on a heterogeneous surface, which was fabricated by fusing angiotensin receptor type I and type II receptors (AT1R and AT2R) at the terminuses of circularly permuted HaloTag (cpHaloTag) and immobilizing the whole fusion protein onto 6-bromohexanoic acid modified silica gel. We proved that immobilized AT1R-cpHalo-AT2R maintained the original ligand- and antibody-binding activities of the two receptors in three weeks. The association constants of valsartan, candesartan, and telmisartan to AT1R were (6.26±0.14) × 105, (9.66±0.71) × 105, and (3.17±0.03) × 105 L/mol. In the same column, their association constants to AT2R were (1.25±0.04) × 104, (2.30±0.08) × 104, and (8.51±0.06) × 103 L/mol. The patterns of the association constants to AT1R/AT2R (candesartan>valsartan>telmisartan) were in good line with the data by performing nonlinear chromatography on control columns containing immobilized AT1R or AT2R alone. This provided proof of the fact that the derivatization allowed the determination of drug bindings on the heterogeneous surface with the utilization of a single series of injections and linear regression. We reasoned that is simple enough to model the bindings of drug adsorption on commercially available adsorbents in fundamental or industrial fields, thus having the potential to become a universal method for analyzing the bindings of a drug to the heterogeneous surface containing multiple targets.

IUPHAR themed review: Opioid efficacy, bias, and selectivity

Drugs acting at the opioid receptor family are clinically used to treat chronic and acute pain, though they represent the second line of treatment behind GABA analogs, antidepressants and SSRI's. Within the opioid family mu and kappa opioid receptor are commonly targeted. However, activation of the mu opioid receptor has side effects of constipation, tolerance, dependence, euphoria, and respiratory depression; activation of the kappa opioid receptor leads to dysphoria and sedation. The side effects of mu opioid receptor activation have led to mu receptor drugs being widely abused with great overdose risk. For these reasons, newer safer opioid analgesics are in high demand. For many years a focus within the opioid field was finding drugs that activated the G protein pathway at mu opioid receptor, without activating the β-arrestin pathway, known as biased agonism. Recent advances have shown that this may not be the way forward to develop safer analgesics at mu opioid receptor, though there is still some promise at the kappa opioid receptor. Here we discuss recent novel approaches to develop safer opioid drugs including efficacy vs bias and fine-tuning receptor activation by targeting sub-pockets in the orthosteric site, we explore recent works on the structural basis of bias, and we put forward the suggestion that Gα subtype selectivity may be an exciting new area of interest.

Quantitative analysis of sterol-modulated monomer-dimer equilibrium of the β1-adrenergic receptor by DEER spectroscopy

G protein-coupled receptors (GPCR) activate numerous intracellular signaling pathways. The oligomerization properties of GPCRs, and hence their cellular functions, may be modulated by various components within the cell membrane (such as the presence of cholesterol). Modulation may occur directly via specific interaction with the GPCR or indirectly by affecting the physical properties of the membrane. Here, we use pulsed Q-band double electron-electron resonance (DEER) spectroscopy to probe distances between R1 nitroxide spin labels attached to Cys163 and Cys344 of the β₁-adrenergic receptor (β₁AR) in n-dodecyl-β-D-maltoside micelles upon titration with two soluble cholesterol analogs, cholesteryl hemisuccinate (CHS) and sodium cholate. The former, like cholesterol, inserts itself into the lipid membrane, parallel to the phospholipid chains; the latter is aligned parallel to the surface of membranes. Global quantitative analysis of DEER echo curves upon titration of spin-labeled β₁AR with CHS and sodium cholate reveal the following: CHS binds specifically to the β₁AR monomer at a site close to the Cys163-R1 spin label with an equilibrium dissociation constant [Formula: see text] ~1.4 ± 0.4 mM. While no direct binding of sodium cholate to the β₁AR receptor was observed by DEER, sodium cholate induces specific β₁AR dimerization ([Formula: see text] ~35 ± 6 mM and a Hill coefficient n ~ 2.5 ± 0.4) with intersubunit contacts between transmembrane helices 1 and 2 and helix 8. Analysis of the DEER data obtained upon the addition of CHS to the β₁AR dimer in the presence of excess cholate results in dimer dissociation with species occupancies as predicted from the individual K_D values.

Protein Design Strategies for the Structural–Functional Studies of G Protein-Coupled Receptors

G protein-coupled receptors (GPCRs) are an important family of membrane proteins responsible for many physiological functions in human body. High resolution GPCR structures are required to understand their molecular mechanisms and perform rational drug design, as GPCRs play a crucial role in a variety of diseases. That is difficult to obtain for the wild-type proteins because of their low stability. In this review, we discuss how this problem can be solved by using protein design strategies developed to obtain homogeneous stabilized GPCR samples for crystallization and cryoelectron microscopy.

Recent advances in dopamine D2 receptor ligands in the treatment of neuropsychiatric disorders

Dopamine is a biologically active amine synthesized in the central and peripheral nervous system. This biogenic monoamine acts by activating five types of dopamine receptors (D_1-5 Rs), which belong to the G protein-coupled receptor family. Antagonists and partial agonists of D₂ Rs are used to treat schizophrenia, Parkinson's disease, depression, and anxiety. The typical pharmacophore with high D₂ R affinity comprises four main areas, namely aromatic moiety, cyclic amine, central linker and aromatic/heteroaromatic lipophilic fragment. From the literature reviewed herein, we can conclude that 4-(2,3-dichlorophenyl), 4-(2-methoxyphenyl)-, 4-(benzo[b]thiophen-4-yl)-1-substituted piperazine, and 4-(6-fluorobenzo[d]isoxazol-3-yl)piperidine moieties are critical for high D₂ R affinity. Four to six atoms chains are optimal for D₂ R affinity with 4-butoxyl as the most pronounced one. The bicyclic aromatic/heteroaromatic systems are most frequently occurring as lipophilic appendages to retain high D₂ R affinity. In this review, we provide a thorough overview of the therapeutic potential of D₂ R modulators in the treatment of the aforementioned disorders. In addition, this review summarizes current knowledge about these diseases, with a focus on the dopaminergic pathway underlying these pathologies. Major attention is paid to the structure, function, and pharmacology of novel D₂ R ligands, which have been developed in the last decade (2010-2021), and belong to the 1,4-disubstituted aromatic cyclic amine group. Due to the abundance of data, allosteric D₂ R ligands and D₂ R modulators from patents are not discussed in this review.

Fragment hopping protocol for the design of small-molecule protein-protein interaction inhibitors

Fragment-based ligand discovery (FBLD) is one of the most successful approaches to designing small-molecule protein-protein interaction (PPI) inhibitors. The incorporation of computational tools to FBLD allows the exploration of chemical space in a time- and cost-efficient manner. Herein, a computational protocol for the development of small-molecule PPI inhibitors using fragment hopping, a fragment-based de novo design approach, is described and a case study is presented to illustrate the efficiency of this protocol. Fragment hopping facilitates the design of PPI inhibitors from scratch solely based on key binding features in the PPI complex structure. This approach is an open system that enables the inclusion of different state-of-the-art programs and softwares to improve its performances.

Accurate determination of protein:ligand standard binding free energies from molecular dynamics simulations

Designing a reliable computational methodology to calculate protein:ligand standard binding free energies is extremely challenging. The large change in configurational enthalpy and entropy that accompanies the association of ligand and protein is notoriously difficult to capture in naive brute-force simulations. Addressing this issue, the present protocol rests upon a rigorous statistical mechanical framework for the determination of protein:ligand binding affinities together with the comprehensive Binding Free-Energy Estimator 2 (BFEE2) application software. With the knowledge of the bound state, available from experiments or docking, application of the BFEE2 protocol with a reliable force field supplies in a matter of days standard binding free energies within chemical accuracy, for a broad range of protein:ligand complexes. Limiting undesirable human intervention, BFEE2 assists the end user in preparing all the necessary input files and performing the post-treatment of the simulations towards the final estimate of the binding affinity.

Allosteric Modulation of Adenosine A2A Receptors as a New Therapeutic Avenue

The therapeutic potential of targeting adenosine A_2A receptors (A_2ARs) is immense due to their broad expression in the body and central nervous system. The role of A_2ARs in cardiovascular function, inflammation, sleep/wake behaviors, cognition, and other primary nervous system functions has been extensively studied. Numerous A_2AR agonist and antagonist molecules are reported, many of which are currently in clinical trials or have already been approved for treatment. Allosteric modulators can selectively elicit a physiologic response only where and when the orthosteric ligand is released, which reduces the risk of an adverse effect resulting from A_2AR activation. Thus, these allosteric modulators have a potential therapeutic advantage over classical agonist and antagonist molecules. This review focuses on the recent developments regarding allosteric A_2AR modulation, which is a promising area for future pharmaceutical research because the list of existing allosteric A_2AR modulators and their physiologic effects is still short.

Structure-Based Virtual Screening for Ligands of G Protein-Coupled Receptors: What Can Molecular Docking Do for You?

G protein-coupled receptors (GPCRs) constitute the largest family of membrane proteins in the human genome and are important therapeutic targets. During the last decade, the number of atomic-resolution structures of GPCRs has increased rapidly, providing insights into drug binding at the molecular level. These breakthroughs have created excitement regarding the potential of using structural information in ligand design and initiated a new era of rational drug discovery for GPCRs. The molecular docking method is now widely applied to model the three-dimensional structures of GPCR-ligand complexes and screen for chemical probes in large compound libraries. In this review article, we first summarize the current structural coverage of the GPCR superfamily and the understanding of receptor-ligand interactions at atomic resolution. We then present the general workflow of structure-based virtual screening and strategies to discover GPCR ligands in chemical libraries. We assess the state of the art of this research field by summarizing prospective applications of virtual screening based on experimental structures. Strategies to identify compounds with specific efficacy and selectivity profiles are discussed, illustrating the opportunities and limitations of the molecular docking method. Our overview shows that structure-based virtual screening can discover novel leads and will be essential in pursuing the next generation of GPCR drugs. SIGNIFICANCE STATEMENT: Extraordinary advances in the structural biology of G protein-coupled receptors have revealed the molecular details of ligand recognition by this large family of therapeutic targets, providing novel avenues for rational drug design. Structure-based docking is an efficient computational approach to identify novel chemical probes from large compound libraries, which has the potential to accelerate the development of drug candidates.

Nonantimicrobial Actions of Macrolides: Overview and Perspectives for Future Development

Macrolides are among the most widely prescribed broad spectrum antibacterials, particularly for respiratory infections. It is now recognized that these drugs, in particular azithromycin, also exert time-dependent immunomodulatory actions that contribute to their therapeutic benefit in both infectious and other chronic inflammatory diseases. Their increased chronic use in airway inflammation and, more recently, of azithromycin in COVID-19, however, has led to a rise in bacterial resistance. An additional crucial aspect of chronic airway inflammation, such as chronic obstructive pulmonary disease, as well as other inflammatory disorders, is the loss of epithelial barrier protection against pathogens and pollutants. In recent years, azithromycin has been shown with time to enhance the barrier properties of airway epithelial cells, an action that makes an important contribution to its therapeutic efficacy. In this article, we review the background and evidence for various immunomodulatory and time-dependent actions of macrolides on inflammatory processes and on the epithelium and highlight novel nonantibacterial macrolides that are being studied for immunomodulatory and barrier-strengthening properties to circumvent the risk of bacterial resistance that occurs with macrolide antibacterials. We also briefly review the clinical effects of macrolides in respiratory and other inflammatory diseases associated with epithelial injury and propose that the beneficial epithelial effects of nonantibacterial azithromycin derivatives in chronic inflammation, even given prophylactically, are likely to gain increasing attention in the future. SIGNIFICANCE STATEMENT: Based on its immunomodulatory properties and ability to enhance the protective role of the lung epithelium against pathogens, azithromycin has proven superior to other macrolides in treating chronic respiratory inflammation. A nonantibiotic azithromycin derivative is likely to offer prophylactic benefits against inflammation and epithelial damage of differing causes while preserving the use of macrolides as antibiotics.

Screening of β1- and β2-Adrenergic Receptor Modulators through Advanced Pharmacoinformatics and Machine Learning Approaches

Cardiovascular diseases (CDs) are a major concern in the human race and one of the leading causes of death worldwide. β-Adrenergic receptors (β1-AR and β2-AR) play a crucial role in the overall regulation of cardiac function. In the present study, structure-based virtual screening, machine learning (ML), and a ligand-based similarity search were conducted for the PubChem database against both β1- and β2-AR. Initially, all docked molecules were screened using the threshold binding energy value. Molecules with a better binding affinity were further used for segregation as active and inactive through ML. The pharmacokinetic assessment was carried out on molecules retained in the above step. Further, similarity searching of the ChEMBL and DrugBank databases was performed. From detailed analysis of the above data, four compounds for each of β1- and β2-AR were found to be promising in nature. A number of critical ligand-binding amino acids formed potential hydrogen bonds and hydrophobic interactions. Finally, a molecular dynamics (MD) simulation study of each molecule bound with the respective target was performed. A number of parameters obtained from the MD simulation trajectories were calculated and substantiated the stability between the protein-ligand complex. Hence, it can be postulated that the final molecules might be crucial for CDs subjected to experimental validation.

Structural insights into ligand recognition and activation of the melanocortin-4 receptor

Melanocortin-4 receptor (MC4R) plays a central role in the regulation of energy homeostasis. Its high sequence similarity to other MC receptor family members, low agonist selectivity and the lack of structural information concerning MC4R-specific activation have hampered the development of MC4R-seletive therapeutics to treat obesity. Here, we report four high-resolution structures of full-length MC4R in complex with the heterotrimeric G_s protein stimulated by the endogenous peptide ligand α-MSH, FDA-approved drugs afamelanotide (Scenesse™) and bremelanotide (Vyleesi™), and a selective small-molecule ligand THIQ, respectively. Together with pharmacological studies, our results reveal the conserved binding mode of peptidic agonists, the distinctive molecular details of small-molecule agonist recognition underlying receptor subtype selectivity, and a distinct activation mechanism for MC4R, thereby offering new insights into G protein coupling. Our work may facilitate the discovery of selective therapeutic agents targeting MC4R.

Ligands of Adrenergic Receptors: A Structural Point of View

Adrenergic receptors are G protein-coupled receptors for epinephrine and norepinephrine. They are targets of many drugs for various conditions, including treatment of hypertension, hypotension, and asthma. Adrenergic receptors are intensively studied in structural biology, displayed for binding poses of different types of ligands. Here, we summarized molecular mechanisms of ligand recognition and receptor activation exhibited by structure. We also reviewed recent advances in structure-based ligand discovery against adrenergic receptors.

Affinity Mass Spectrometry-Based Fragment Screening Identified a New Negative Allosteric Modulator of the Adenosine A2A Receptor Targeting the Sodium Ion Pocket

Allosteric ligands provide new opportunities to modulate G protein-coupled receptor (GPCR) function and present therapeutic benefits over orthosteric molecules. Negative allosteric modulators (NAMs) can inhibit the activation of a receptor and downstream signal transduction. Screening NAMs for a GPCR target is particularly challenging because of the difficulty in distinguishing NAMs from antagonists bound to the orthosteric site as they both show inhibitory effects in receptor signaling assays. Here we report an affinity mass spectrometry (MS)-based approach tailored to screening potential NAMs of a GPCR target especially from fragment libraries. Compared to regular surface plasmon resonance or NMR-based methods for fragment screening, our approach features a reduction of the protein and compound consumption by 2-4 orders of magnitude and an increase in the data acquisition speed by 2-3 orders of magnitude. Our affinity MS-based fragment screening led to the identification of a new NAM of the adenosine A_2A receptor (A_2AAR) bearing an unprecedented azetidine moiety predicted to occupy the allosteric sodium binding site. Molecular dynamics simulations, ligand structure-activity relationship (SAR) studies, and in-solution NMR analyses further revealed the unique binding mode and antagonistic property of this compound that differs considerably from HMA (5-(N,N-hexamethylene)amiloride), a well-characterized NAM of A_2AAR. Taken together, our work would facilitate fragment-based screening of allosteric modulators, as well as guide the design of novel NAMs acting at the sodium ion pocket of class A GPCRs.

Radioligand and computational insight in structure - Activity relationship of saccharin derivatives being ipsapirone and revospirone analogues

Schizophrenia and depression are diseases that significantly impede human functioning in society. Current antidepressant drugs are not fully effective. According to literature data, the effect on D₂R or 5-HT_1AR can effectively reduce the symptoms of depression or schizophrenia. Recent research hypothetized that the synergism of both of these receptors can improve the effectiveness of therapy. Ipsapirone, a representative of long-chain arylpiperazines, is a known 5-HT_1AR ligand that has antidepressant effect. This compound has no affinity for the D₂R. Bearing in mind, we decided to design ligands with improved affinity to D₂R and confirmed that in some cases elongation of the carbon linker or arylpiperazine exchange may have beneficial influence on the binding to D2R and 5-HT1AR. Four groups of ligands being ipsapirone analogues with butyl, pentyl, hexyl and stiffened xylene chains were designed. All compounds were obtained in solvent-free reactions supported by a microwave irradiation with an efficiency mainly above 60%. All ligands containing 1-(2-pyrimidinyl)piperazine exhibited high affinity to 5-HT_1AR. In this case, chemical modifications within the chain did not affect the affinity to D₂R. In the case of ligands containing 1-phenylpiperazine, 1-(3-trifluoromethylphenyl)piperazine, 1-(1-naphthyl)piperazine, and 1-(4-chlorophenyl)piperazine, elongation of carbon linker increases of affinity to D₂R. For ligands containing 1- (2-pyridyl) piperazine, and 1-(2,3-dichlorophenyl)piperazine, we observed an opposite effect. For ligands containing 1-phenylpiperazine, 1-(2-methoxyphenyl)piperazine and 1-(2-pyridyl)piperazine, chain elongation had no effect on 5-HT_1AR binding. In turn of ligands containing 1-(3-trifluoromethylphenyl)piperazine and 1- (2,3-dichlorophenyl)piperazine, we observed that elongation of carbon linker has a positive influence to 5-HT_1AR. Molecular modelling was used to support the SAR study.

Engineering of Challenging G Protein-Coupled Receptors for Structure Determination and Biophysical Studies

Membrane proteins such as G protein-coupled receptors (GPCRs) exert fundamental biological functions and are involved in a multitude of physiological responses, making these receptors ideal drug targets. Drug discovery programs targeting GPCRs have been greatly facilitated by the emergence of high-resolution structures and the resulting opportunities to identify new chemical entities through structure-based drug design. To enable the determination of high-resolution structures of GPCRs, most receptors have to be engineered to overcome intrinsic hurdles such as their poor stability and low expression levels. In recent years, multiple engineering approaches have been developed to specifically address the technical difficulties of working with GPCRs, which are now beginning to make more challenging receptors accessible to detailed studies. Importantly, successfully engineered GPCRs are not only valuable in X-ray crystallography, but further enable biophysical studies with nuclear magnetic resonance spectroscopy, surface plasmon resonance, native mass spectrometry, and fluorescence anisotropy measurements, all of which are important for the detailed mechanistic understanding, which is the prerequisite for successful drug design. Here, we summarize engineering strategies based on directed evolution to reduce workload and enable biophysical experiments of particularly challenging GPCRs.

Palladium-Catalyzed Amination/Dearomatization Reaction of Indoles and Benzofurans

This report describes a palladium-catalyzed dearomatization and amination tandem reaction of 2,3-disubstituted indoles and benzofurans via the Catellani strategy. This reaction provides a new method for the construction of amino-substituted indoline-fused cyclic and benzofuran spiro compounds in good yields. The reaction has broad functional group compatibility and substrate scope.

Allosteric modulation of G protein-coupled receptors by amiloride and its derivatives. Perspectives for drug discovery?

The function of G protein‐coupled receptors (GPCRs) can be modulated by compounds that bind to other sites than the endogenous orthosteric binding site, so‐called allosteric sites. Structure elucidation of a number of GPCRs has revealed the presence of a sodium ion bound in a conserved allosteric site. The small molecule amiloride and analogs thereof have been proposed to bind in this same sodium ion site. Hence, this review seeks to summarize and reflect on the current knowledge of allosteric effects by amiloride and its analogs on GPCRs. Amiloride is known to modulate adenosine, adrenergic, dopamine, chemokine, muscarinic, serotonin, gonadotropin‐releasing hormone, GABA_B, and taste receptors. Amiloride analogs with lipophilic substituents tend to be more potent modulators than amiloride itself. Adenosine, α‐adrenergic and dopamine receptors are most strongly modulated by amiloride analogs. In addition, for a few GPCRs, more than one binding site for amiloride has been postulated. Interestingly, the nature of the allosteric effect of amiloride and derivatives varies considerably between GPCRs, with both negative and positive allosteric modulation occurring. Since the sodium ion binding site is strongly conserved among class A GPCRs it is to be expected that amiloride also binds to class A GPCRs not evaluated yet. Investigating this typical amiloride‐GPCR interaction further may yield general insight in the allosteric mechanisms of GPCR ligand binding and function, and possibly provide new opportunities for drug discovery.

NMR investigation of protein-ligand interactions for G-protein coupled receptors

In this review, we report NMR studies of ligand-GPCR interactions, including both ligand-observed and protein-observed NMR experiments. Published studies exemplify how NMR can be used as a powerful tool to design novel GPCR ligands and investigate the ligand-induced conformational changes of GPCRs. The strength of NMR also lies in its capability to explore the diverse signaling pathways and probe the allosteric modulation of these highly dynamic receptors. By offering unique opportunities for the identification, structural and functional characterization of GPCR ligands, NMR will likely play a major role for the generation of novel molecules both as new tools for the understanding of the GPCR function and as therapeutic compounds for a large diversity of pathologies.

A benchmark study of loop modeling methods applied to G protein-coupled receptors

G protein-coupled receptors (GPCR) are important drug discovery targets. Despite progress, many GPCR structures have not yet been solved. For these targets, comparative modeling is used in virtual ligand screening to prioritize experimental efforts. However, the structure of extracellular loop 2 (ECL2) is often poorly predicted. This is significant due to involvement of ECL2 in ligand binding for many Class A GPCR. Here we examine the performance of loop modeling protocols available in the Rosetta (cyclic coordinate descent [CCD], KIC with fragments [KICF] and next generation KIC [NGK]) and Molecular Operating Environment (MOE) software suites (de novo search). ECL2 from GPCR crystal structures served as the structure prediction targets and were divided into four sets depending on loop length. Results suggest that KICF and NGK sampled and scored more loop models with sub-angstrom and near-atomic accuracy than CCD or de novo search for loops of 24 or fewer residues. None of the methods were able to sample loop conformations with near-atomic accuracy for the longest targets ranging from 25 to 32 residues based on 1000 models generated. For these long loop targets, increased conformational sampling is necessary. The strongly conserved disulfide bond between Cys3.25 and Cys45.50 in ECL2 proved an effective filter. Setting an upper limit of 5.1 Å on the S-S distance improved the lowest RMSD model included in the top 10 scored structures in Groups 1-4 on average between 0.33 and 1.27 Å. Disulfide bond formation and geometry optimization of ECL2 provided an additional incremental benefit in structure quality.

Three-dimensional descriptors for aminergic GPCRs: dependence on docking conformation and crystal structure

Three-dimensional descriptors are often used to search for new biologically active compounds, in both ligand- and structure-based approaches, capturing the spatial orientation of molecules. They frequently constitute an input for machine learning-based predictions of compound activity or quantitative structure-activity relationship modeling; however, the distribution of their values and the accuracy of depicting compound orientations might have an impact on the power of the obtained predictive models. In this study, we analyzed the distribution of three-dimensional descriptors calculated for docking poses of active and inactive compounds for all aminergic G protein-coupled receptors with available crystal structures, focusing on the variation in conformations for different receptors and crystals. We demonstrated that the consistency in compound orientation in the binding site is rather not correlated with the affinity itself, but is more influenced by other factors, such as the number of rotatable bonds and crystal structure used for docking studies. The visualizations of the descriptors distributions were prepared and made available online at http://chem.gmum.net/vischem_stability , which enables the investigation of chemical structures referring to particular data points depicted in the figures. Moreover, the performed analysis can assist in choosing crystal structure for docking studies, helping in selection of conditions providing the best discrimination between active and inactive compounds in machine learning-based experiments.

Aminergic GPCR-Ligand Interactions: A Chemical and Structural Map of Receptor Mutation Data

The aminergic family of G protein-coupled receptors (GPCRs) plays an important role in various diseases and represents a major drug discovery target class. Structure determination of all major aminergic subfamilies has enabled structure-based ligand design for these receptors. Site-directed mutagenesis data provides an invaluable complementary source of information for elucidating the structural determinants of binding of different ligand chemotypes. The current study provides a comparative analysis of 6692 mutation data points on 34 aminergic GPCR subtypes, covering the chemical space of 540 unique ligands from mutagenesis experiments and information from experimentally determined structures of 52 distinct aminergic receptor-ligand complexes. The integrated analysis enables detailed investigation of structural receptor-ligand interactions and assessment of the transferability of combined binding mode and mutation data across ligand chemotypes and receptor subtypes. An overview is provided of the possibilities and limitations of using mutation data to guide the design of novel aminergic receptor ligands.

Computational design of thermostabilizing point mutations for G protein-coupled receptors

Engineering of GPCR constructs with improved thermostability is a key for successful structural and biochemical studies of this transmembrane protein family, targeted by 40% of all therapeutic drugs. Here we introduce a comprehensive computational approach to effective prediction of stabilizing mutations in GPCRs, named CompoMug, which employs sequence-based analysis, structural information, and a derived machine learning predictor. Tested experimentally on the serotonin 5-HT_2C receptor target, CompoMug predictions resulted in 10 new stabilizing mutations, with an apparent thermostability gain ~8.8°C for the best single mutation and ~13°C for a triple mutant. Binding of antagonists confers further stabilization for the triple mutant receptor, with total gains of ~21°C as compared to wild type apo 5-HT_2C. The predicted mutations enabled crystallization and structure determination for the 5-HT_2C receptor complexes in inactive and active-like states. While CompoMug already shows high 25% hit rate and utility in GPCR structural studies, further improvements are expected with accumulation of structural and mutation data.

The trillions of cells in the human body rely on receptors that sit in their cell membranes to communicate with each other. Hundreds of different receptors belong to the G protein-coupled receptor superfamily (called GPCRs for short) and play vital roles in the all organs and bodily systems. Indeed, GPCRs are the targets for almost 40% of therapeutic drugs. As such, deciphering the shape and activity of GPCRs is key to understanding the normal workings of the human biology and could help scientists discover new treatments for various diseases, from depression to high blood pressure to cancer. These receptors, however, are notoriously flimsy and unstable, making them difficult to work with in the laboratory.

Different approaches have been developed to make GPCRs more stable, usually by swapping one or a few of the amino acid building blocks in the protein for other amino acids. Currently, this requires a costly and slow trial-and-error approach in which each amino acid out of 300-400 in the protein is mutated and tested experimentally.

To speed up and reduce the cost of the process, Popov et al. asked if a computer could predict which mutations in the protein would stabilize it, meaning that fewer proteins would actually need to be tested. Four computer algorithms based on four different principles were developed and verified. The first one compares the target GPCR to other closely related receptors, trying to detect variations that cause the instability. The second tries to build in specific stabilizing interactions, or “bridges”, between different parts of the receptor. The third algorithm searches the known structures of other GPCRs for useful mutations. Finally, the fourth one uses accumulated data on the stability of hundreds of mutations in different GPCRs to train a machine learning predictor to recognize stabilizing mutations.

All four algorithms produced useful predictions in a real-life project. Indeed, when combined in one computational tool, named CompoMug, the algorithms made it possible to detect optimal mutations in a human GPCR called 5-HT_2C. This made the protein much easier to work with in the laboratory, and ultimately helped to solve its three-dimensional structure (which was reported in a separate study, published earlier in 2018)

The 5-HT_2C receptor is involved in regulating, among other things, mood and appetite. Details of its structure might therefore help researchers to design new antidepressants and obesity treatments. Moreover, CompoMug is already helping structural biologists to solve the structures of other GPCRs, which will further facilitate many aspects of GPCR drug discovery.

Exploring Molecular-Biomembrane Interactions with Surface Plasmon Resonance and Dual Polarization Interferometry Technology: Expanding the Spotlight onto Biomembrane Structure

The molecular analysis of biomolecular-membrane interactions is central to understanding most cellular systems but has emerged as a complex technical challenge given the complexities of membrane structure and composition across all living cells. We present a review of the application of surface plasmon resonance and dual polarization interferometry-based biosensors to the study of biomembrane-based systems using both planar mono- or bilayers or liposomes. We first describe the optical principals and instrumentation of surface plasmon resonance, including both linear and extraordinary transmission modes and dual polarization interferometry. We then describe the wide range of model membrane systems that have been developed for deposition on the chips surfaces that include planar, polymer cushioned, tethered bilayers, and liposomes. This is followed by a description of the different chemical immobilization or physisorption techniques. The application of this broad range of engineered membrane surfaces to biomolecular-membrane interactions is then overviewed and how the information obtained using these techniques enhance our molecular understanding of membrane-mediated peptide and protein function. We first discuss experiments where SPR alone has been used to characterize membrane binding and describe how these studies yielded novel insight into the molecular events associated with membrane interactions and how they provided a significant impetus to more recent studies that focus on coincident membrane structure changes during binding of peptides and proteins. We then discuss the emerging limitations of not monitoring the effects on membrane structure and how SPR data can be combined with DPI to provide significant new information on how a membrane responds to the binding of peptides and proteins.

Enabling STD-NMR fragment screening using stabilized native GPCR: A case study of adenosine receptor

Structural studies of integral membrane proteins have been limited by the intrinsic conformational flexibility and the need to stabilize the proteins in solution. Stabilization by mutagenesis was very successful for structural biology of G protein-coupled receptors (GPCRs). However, it requires heavy protein engineering and may introduce structural deviations. Here we describe the use of specific calixarenes-based detergents for native GPCR stabilization. Wild type, full length human adenosine A_2A receptor was used to exemplify the approach. We could stabilize native, glycosylated, non-aggregated and homogenous A_2AR that maintained its ligand binding capacity. The benefit of the preparation for fragment screening, using the Saturation-Transfer Difference nuclear magnetic resonance (STD-NMR) experiment is reported. The binding of the agonist adenosine and the antagonist caffeine were observed and competition experiments with CGS-21680 and ZM241385 were performed, demonstrating the feasibility of the STD-based fragment screening on the native A_2A receptor. Interestingly, adenosine was shown to bind a second binding site in the presence of the agonist CGS-21680 which corroborates published results obtained with molecular dynamics simulation. Fragment-like compounds identified using STD-NMR showed antagonistic effects on A_2AR in the cAMP cellular assay. Taken together, our study shows that stabilization of native GPCRs represents an attractive approach for STD-based fragment screening and drug design.

Emerging Paradigm of Intracellular Targeting of G Protein-Coupled Receptors

G protein-coupled receptors (GPCRs) recognize a diverse array of extracellular stimuli, and they mediate a broad repertoire of signaling events involved in human physiology. Although the major effort on targeting GPCRs has typically been focused on their extracellular surface, a series of recent developments now unfold the possibility of targeting them from the intracellular side as well. Allosteric modulators binding to the cytoplasmic surface of GPCRs have now been described, and their structural mechanisms are elucidated by high-resolution crystal structures. Furthermore, pepducins, aptamers, and intrabodies targeting the intracellular face of GPCRs have also been successfully utilized to modulate receptor signaling. Moreover, small molecule compounds, aptamers, and synthetic intrabodies targeting β-arrestins have also been discovered to modulate GPCR endocytosis and signaling. Here, we discuss the emerging paradigm of intracellular targeting of GPCRs, and outline the current challenges, potential opportunities, and future outlook in this particular area of GPCR biology.

Chemical Diversity in the G Protein-Coupled Receptor Superfamily

G protein-coupled receptors (GPCRs) are the largest family of cell signaling transmembrane proteins that can be modulated by a plethora of chemical compounds. Systematic cheminformatics analysis of structurally and pharmacologically characterized GPCR ligands shows that cocrystallized GPCR ligands cover a significant part of chemical ligand space, despite their limited number. Many GPCR ligands and substructures interact with multiple receptors, providing a basis for polypharmacological ligand design. Experimentally determined GPCR structures represent a variety of binding sites and receptor-ligand interactions that can be translated to chemically similar ligands for which structural data are lacking. This integration of structural, pharmacological, and chemical information on GPCR-ligand interactions enables the extension of the structural GPCR-ligand interactome and the structure-based design of novel modulators of GPCR function.

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.

High-throughput identification of G protein-coupled receptor modulators through affinity mass spectrometry screening

High-throughput identification of GPCR modulators through affinity MS screening.

G protein-coupled receptors (GPCRs) represent the largest class of cell surface proteins and thus constitute an important family of therapeutic targets. Therefore, significant effort has been put towards the identification of novel ligands that can modulate the activity of a GPCR target with high efficacy and selectivity. However, due to limitations inherent to the most common techniques for GPCR ligand discovery, there is a pressing need for more efficient and effective ligand screening methods especially for the identification of potential allosteric modulators. Here we present a high-throughput, label-free and unbiased screening approach for the identification of small molecule ligands towards GPCR targets based on affinity mass spectrometry. This new approach features the usage of target-expressing cell membranes rather than purified proteins for ligand screening and allows the detection of both orthosteric and allosteric ligands targeting specific GPCRs. Screening a small compound library with this approach led to the rapid discovery of an antagonist for the 5-HT receptor and four positive allosteric modulators for GLP-1 receptor that were not previously reported.

Towards high throughput GPCR crystallography: In Meso soaking of Adenosine A2A Receptor crystals

Here we report an efficient method to generate multiple co-structures of the A_2A G protein-coupled receptor (GPCR) with small-molecules from a single preparation of a thermostabilised receptor crystallised in Lipidic Cubic Phase (LCP). Receptor crystallisation is achieved following purification using a low affinity “carrier” ligand (theophylline) and crystals are then soaked in solutions containing the desired (higher affinity) compounds. Complete datasets to high resolution can then be collected from single crystals and seven structures are reported here of which three are novel. The method significantly improves structural throughput for ligand screening using stabilised GPCRs, thereby actively driving Structure-Based Drug Discovery (SBDD).

Intracellular Transfer of Na+ in an Active-State G-Protein-Coupled Receptor

Playing a central role in cell signaling, G-protein-coupled receptors (GPCRs) are the largest superfamily of membrane proteins and form the majority of drug targets in humans. How extracellular agonist binding triggers the activation of GPCRs and associated intracellular effector proteins remains, however, poorly understood. Structural studies have revealed that inactive class A GPCRs harbor a conserved binding site for Na+ ions in the center of their transmembrane domain, accessible from the extracellular space. Here, we show that the opening of a conserved hydrated channel in the activated state receptors allows the Na+ ion to egress from its binding site into the cytosol. Coupled with protonation changes, this ion movement occurs without significant energy barriers, and can be driven by physiological transmembrane ion and voltage gradients. We propose that Na+ ion exchange with the cytosol is a key step in GPCR activation. Further, we hypothesize that this transition locks receptors in long-lived active-state conformations.

A Structural Framework for GPCR Chemogenomics: What's In a Residue Number?

The recent surge of crystal structures of G protein-coupled receptors (GPCRs), as well as comprehensive collections of sequence, structural, ligand bioactivity, and mutation data, has enabled the development of integrated chemogenomics workflows for this important target family. This chapter will focus on cross-family and cross-class studies of GPCRs that have pinpointed the need for, and the implementation of, a generic numbering scheme for referring to specific structural elements of GPCRs. Sequence- and structure-based numbering schemes for different receptor classes will be introduced and the remaining caveats will be discussed. The use of these numbering schemes has facilitated many chemogenomics studies such as consensus binding site definition, binding site comparison, ligand repurposing (e.g. for orphan receptors), sequence-based pharmacophore generation for homology modeling or virtual screening, and class-wide chemogenomics studies of GPCRs.

Exploring GPCR-Ligand Interactions with the Fragment Molecular Orbital (FMO) Method

The understanding of binding interactions between any protein and a small molecule plays a key role in the rationalization of affinity and selectivity. It is essential for an efficient structure-based drug design (SBDD) process. FMO enables ab initio approaches to be applied to systems that conventional quantum-mechanical (QM) methods would find challenging. The key advantage of the Fragment Molecular Orbital Method (FMO) is that it can reveal atomistic details about the individual contributions and chemical nature of each residue and water molecule toward ligand binding which would otherwise be difficult to detect without using QM methods. In this chapter, we demonstrate the typical use of FMO to analyze 19 crystal structures of β1 and β2 adrenergic receptors with their corresponding agonists and antagonists.

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.

Structure-inspired design of β-arrestin-biased ligands for aminergic GPCRs

Development of biased ligands targeting G protein-coupled receptors (GPCRs) is a promising approach for current drug discovery. Although structure-based drug design of biased agonists remains challenging even with an abundance of GPCR crystal structures, we present an approach for translating GPCR structural data into β-arrestin-biased ligands for aminergic GPCRs. We identified specific amino acid-ligand contacts at transmembrane helix 5 (TM5) and extracellular loop 2 (EL2) responsible for Gi/o and β-arrestin signaling, respectively, and targeted those residues to develop biased ligands. For these ligands, we found that bias is conserved at other aminergic GPCRs that retain similar residues at TM5 and EL2. Our approach provides a template for generating arrestin-biased ligands by modifying predicted ligand interactions that block TM5 interactions and promote EL2 interactions. This strategy could facilitate the structure-guided design of arrestin-biased ligands at other GPCRs, including polypharmacological biased ligands.

Weak-binding molecules are not drugs?-toward a systematic strategy for finding effective weak-binding drugs

Designing maximally selective ligands that act on individual drug targets with high binding affinity has been the central dogma of drug discovery and development for the past two decades. However, many low-affinity drugs that aim for several targets at the same time are found more effective than the high-affinity binders when faced with complex disease conditions, such as cancers, Alzheimer's disease and cardiovascular diseases. The aim of this study was to appreciate the importance and reveal the features of weak-binding drugs and propose an integrated strategy for discovering them. Weak-binding drugs can be characterized by their high dissociation rates and transient interactions with their targets. In addition, network topologies and dynamics parameters involved in the targets of weak-binding drugs also influence the effects of the drugs. Here, we first performed a dynamics analysis for 33 elementary subgraphs to determine the desirable topology and dynamics parameters among targets. Then, by applying the elementary subgraphs to the mitogen-activated protein kinase (MAPK) pathway, several optimal target combinations were obtained. Combining drug-target interaction prediction with molecular dynamics simulation, we got two potential weak-binding drug candidates, luteolin and tanshinone IIA, acting on these targets. Further, the binding affinity of these two compounds to their targets and the anti-inflammatory effects of them were validated through in vitro experiments. In conclusion, weak-binding drugs have real opportunities for maximum efficiency and may show reduced adverse reactions, which can offer a bright and promising future for new drug discovery.

G protein-coupled receptors: the evolution of structural insight

G protein-coupled receptors (GPCR) comprise a diverse superfamily of over 800 proteins that have gained relevance as biological targets for pharmaceutical drug design. Although these receptors have been investigated for decades, three-dimensional structures of GPCR have only recently become available. In this review, we focus on the technological advancements that have facilitated efforts to gain insights into GPCR structure. Progress in these efforts began with the initial crystal structure determination of rhodopsin (PDB: 1F88) in 2000 and has continued to the most recently published structure of the A_1AR (PDB: 5UEN) in 2017. Numerous experimental developments over the past two decades have opened the door for widespread GPCR structural characterization. These efforts have resulted in the determination of three-dimensional structures for over 40 individual GPCR family members. Herein we present a comprehensive list and comparative analysis of over 180 individual GPCR structures. This includes a summary of different GPCR functional states crystallized with agonists, dual agonists, partial agonists, inverse agonists, antagonists, and allosteric modulators.

Anthocyanin rich extract of Brassica oleracea L. alleviates experimentally induced myocardial infarction

Cardioprotective potential of anthocyanin rich red cabbage extract (ARCE) was assessed in H₂O₂ treated rat neonatal cardiomyoblasts (H9c2 cells) and isoproterenol (ISO) induced rodent model of myocardial infarction. H₂O₂ treated H9c2 cells recorded cytotoxicity (48–50%) and apoptosis (57.3%), the same were reduced in presence of ARCE (7–10% & 12.3% respectively). Rats pretreated with ARCE for 30 days followed by ISO treatment recorded favourable heart: body weight ratio as compared to ISO treated group. Also, the mRNA levels of enzymatic antioxidants (sod and catalase) and apoptotic genes (bax and bcl-2) in ARCE+ISO treated group were similar to the control group suggesting that ARCE pretreatment prevents ISO induced depletion of enzymatic antioxidants and apoptosis. Histoarchitecture of ventricular tissue of ISO treated group was marked by infracted areas (10%) and derangement of myocardium whereas, ARCE+ISO treated group (4.5%) recorded results comparable to control (0%). ARCE+ISO treated group accounted for upregulation of caveolin-3 and SERCA2a expression as compared to the ISO treated group implying towards ARCE mediated reduction in membrane damage and calcium imbalance. Molecular docking scores and LigPlot analysis of cyanidin-3-glucoside (-8.7 Kcal/mol) and delphinidin-3-glucoside (-8.5 Kcal/mol) showed stable hydrophobic and electrostatic interactions with β₁ adrenergic receptor. Overall this study elucidates the mechanism of ARCE mediated prevention of experimentally induced myocardial damage.

Identification of Protein Palmitoylation Inhibitors from a Scaffold Ranking Library

The addition of palmitoyl moieties to proteins regulates their membrane targeting, subcellular localization, and stability. Dysregulation of the enzymes which catalyzed the palmitoyl addition and/or the substrates of these enzymes have been linked to cancer, cardiovascular, and neurological disorders, implying these enzymes and substrates are valid targets for pharmaceutical intervention. However, current chemical modulators of zDHHC PAT enzymes lack specificity and affinity, underscoring the need for screening campaigns to identify new specific, high affinity modulators. This report describes a mixture based screening approach to identify inhibitors of Erf2 activity. Erf2 is the Saccharomyces cerevisiae PAT responsible for catalyzing the palmitoylation of Ras2, an ortholog of the human Ras oncogene proteins. A chemical library developed by the Torrey Pines Institute for Molecular Studies consists of more than 30 million compounds designed around 68 molecular scaffolds that are systematically arranged into positional scanning and scaffold ranking formats. We have used this approach to identify and characterize several scaffold backbones and R-groups that reduce or eliminate the activity of Erf2 in vitro. Here, we present the analysis of one of the scaffold backbones, bis-cyclic piperazine. We identified compounds that inhibited Erf2 auto-palmitoylation activity using a fluorescence-based, coupled assay in a high throughput screening (HTS) format and validated the hits utilizing an orthogonal gel-based assay. Finally, we examined the effects of the compounds on cell growth in a yeast cell-based assay. Based on our results, we have identified specific, high affinity palmitoyl transferase inhibitors that will serve as a foundation for future compound design.

Fragment optimization for GPCRs by molecular dynamics free energy calculations: Probing druggable subpockets of the A 2A adenosine receptor binding site

Fragment-based lead discovery is becoming an increasingly popular strategy for drug discovery. Fragment screening identifies weakly binding compounds that require optimization to become high-affinity leads. As design of leads from fragments is challenging, reliable computational methods to guide optimization would be invaluable. We evaluated using molecular dynamics simulations and the free energy perturbation method (MD/FEP) in fragment optimization for the A_2A adenosine receptor, a pharmaceutically relevant G protein-coupled receptor. Optimization of fragments exploring two binding site subpockets was probed by calculating relative binding affinities for 23 adenine derivatives, resulting in strong agreement with experimental data (R² = 0.78). The predictive power of MD/FEP was significantly better than that of an empirical scoring function. We also demonstrated the potential of the MD/FEP to assess multiple binding modes and to tailor the thermodynamic profile of ligands during optimization. Finally, MD/FEP was applied prospectively to optimize three nonpurine fragments, and predictions for 12 compounds were evaluated experimentally. The direction of the change in binding affinity was correctly predicted in a majority of the cases, and agreement with experiment could be improved with rigorous parameter derivation. The results suggest that MD/FEP will become a powerful tool in structure-driven optimization of fragments to lead candidates.

Recent Advances in Structure-Based Drug Design Targeting Class A G Protein-Coupled Receptors Utilizing Crystal Structures and Computational Simulations

G protein-coupled receptors (GPCRs) represent the largest and most physiologically important integral membrane protein family, and these receptors respond to a wide variety of physiological and environmental stimuli. GPCRs are among the most critical therapeutic targets for numerous human diseases, and approximately one-third of the currently marketed drugs target this receptor family. The recent breakthroughs in GPCR structural biology have significantly contributed to our understanding of GPCR function, ligand binding, and pharmacological action as well as to the design of new drugs. This perspective highlights the latest advances in GPCR structures with a focus on the receptor-ligand interactions of each receptor family in class A nonrhodopsin GPCRs as well as the structural features for their activation, biased signaling, and allosteric mechanisms. The current state-of-the-art methodologies of structure-based drug design (SBDD) approaches in the GPCR research field are also discussed.

The Role of Cholesterol in Driving IAPP-Membrane Interactions

Our knowledge of the molecular events underlying type 2 diabetes mellitus-a protein conformational disease characterized by the aggregation of islet amyloid polypeptide (IAPP) in pancreatic β cells-is limited. However, amyloid-mediated membrane damage is known to play a key role in IAPP cytotoxicity, and therefore the effects of lipid composition on modulating IAPP-membrane interactions have been the focus of intense research. In particular, membrane cholesterol content varies with aging and consequently with adverse environmental factors such as diet and lifestyle, but its role in the development of the disease is controversial. In this study, we employ a combination of experimental techniques and in silico molecular simulations to shed light on the role of cholesterol in IAPP aggregation and the related membrane disruption. We show that if anionic POPC/POPS vesicles are used as model membranes, cholesterol has a negligible effect on the kinetics of IAPP fibril growth on the surface of the bilayer. In addition, cholesterol inhibits membrane damage by amyloid-induced poration on membranes, but enhances leakage through fiber growth on the membrane surface. Conversely, if 1:2 DOPC/DPPC raft-like model membranes are used, cholesterol accelerates fiber growth. Next, it enhances pore formation and suppresses fiber growth on the membrane surface, leading to leakage. Our results highlight a twofold effect of cholesterol on the amyloidogenicity of IAPP and help explain its debated role in type 2 diabetes mellitus.