Pharmacological fingerprint of antipsychotic drugs at the serotonin 5-HT2A receptor.

The intricate involvement of the serotonin 5-HT2A receptor (5-HT2AR) both in schizophrenia and in the activity of antipsychotic drugs is widely acknowledged. The currently marketed antipsychotic drugs, although effective in managing the symptoms of schizophrenia to a certain extent, are not without their repertoire of serious side effects. There is a need for better therapeutics to treat schizophrenia for which understanding the mechanism of action of the current antipsychotic drugs is imperative. With bioluminescence resonance energy transfer (BRET) assays, we trace the signaling signature of six antipsychotic drugs belonging to three generations at the 5-HT2AR for the entire spectrum of signaling pathways activated by serotonin (5-HT). The antipsychotic drugs display previously unidentified pathway preference at the level of the individual Gα subunits and ß-arrestins. In particular, risperidone, clozapine, olanzapine and haloperidol showed G protein-selective inverse agonist activity. In addition, G protein-selective partial agonism was found for aripiprazole and cariprazine. Pathway-specific apparent dissociation constants determined from functional analyses revealed distinct coupling-modulating capacities of the tested antipsychotics at the different 5-HT-activated pathways. Computational analyses of the pharmacological and structural fingerprints support a mechanistically based clustering that recapitulate the clinical classification (typical/first generation, atypical/second generation, third generation) of the antipsychotic drugs. The study provides a new framework to functionally classify antipsychotics that should represent a useful tool for the identification of better and safer neuropsychiatric drugs and allows formulating hypotheses on the links between specific signaling cascades and in the clinical outcomes of the existing drugs.

Fluorescent Tools for the Imaging of Dopamine D2 -Like Receptors.

The family of dopamine D2 -like receptors represents an interesting target for a variety of neurological diseases, e. g. Parkinson's disease (PD), addiction, or schizophrenia. In this study we describe the synthesis of a new set of fluorescent ligands as tools for visualization of dopamine D2 -like receptors. Pharmacological characterization in radioligand binding studies identified UR-MN212 (20) as a high-affinity ligand for D2 -like receptors (pKi (D2long R)=8.24, pKi (D3 R)=8.58, pKi (D4 R)=7.78) with decent selectivity towards D1 -like receptors. Compound 20 is a neutral antagonist in a Go1 activation assay at the D2long R, D3 R, and D4 R, which is an important feature for studies using whole cells. The neutral antagonist 20, equipped with a 5-TAMRA dye, displayed rapid association to the D2long R in binding studies using confocal microscopy demonstrating its suitability for fluorescence microscopy. Furthermore, in molecular brightness studies, the ligand's binding affinity could be determined in a single-digit nanomolar range that was in good agreement with radioligand binding data. Therefore, the fluorescent compound can be used for quantitative characterization of native D2 -like receptors in a broad variety of experimental setups.

Shedding Light on the D1 -Like Receptors: A Fluorescence-Based Toolbox for Visualization of the D1 and D5 Receptors.

Dopamine D1 -like receptors are the most abundant type of dopamine receptors in the central nervous system and, even after decades of discovery, still highly interesting for the study of neurological diseases. We herein describe the synthesis of a new set of fluorescent ligands, structurally derived from D1 R antagonist SCH-23390 and labeled with two different fluorescent dyes, as tool compounds for the visualization of D1 -like receptors. Pharmacological characterization in radioligand binding studies identified UR-NR435 (25) as a high-affinity ligand for D1 -like receptors (pKi (D1 R)=8.34, pKi (D5 R)=7.62) with excellent selectivity towards D2 -like receptors. Compound 25 proved to be a neutral antagonist at the D1 R and D5 R in a Gs heterotrimer dissociation assay, an important feature to avoid receptor internalization and degradation when working with whole cells. The neutral antagonist 25 displayed rapid association and complete dissociation to the D1 R in kinetic binding studies using confocal microscopy verifying its applicability for fluorescence microscopy. Moreover, molecular brightness studies determined a single-digit nanomolar binding affinity of the ligand, which was in good agreement with radioligand binding data. For this reason, this fluorescent ligand is a useful tool for a sophisticated characterization of native D1 receptors in a variety of experimental setups.

A virtual library of small molecules mimicking dipeptides.

Virtual combinatorial libraries are prevalent in drug discovery due to improvements in the prediction of synthetic reactions that can be performed. This has gone hand in hand with the development of virtual screening capabilities to effectively screen the large chemical spaces spanned by exhaustive enumeration of reaction products. In this study, we generated a small-molecule dipeptide mimic library to target proteins binding small peptides. The library was created based on the general idea of peptide synthesis, that is, amino acid mimics were reacted in silico to form the dipeptide mimics, yielding 2,036,819 unique compounds. After docking calculations, two compounds from the library were synthesized and tested against WD repeat-containing protein 5 (WDR5) and histamine receptors H1-H4 to evaluate whether these molecules are viable in assays. The compounds showed the highest potency at the histamine H3 receptor, with Ki values in the two-digit micromolar range.

The Isoleucine at Position 118 in Transmembrane 2 Is Responsible for the Selectivity of Xamoterol, Nebivolol, and ICI89406 for the Human ß1-Adrenoceptor.

Known off-target interactions frequently cause predictable drug side-effects (e.g., ß1-antagonists used for heart disease, risk ß2-mediated bronchospasm). Computer-aided drug design would improve if the structural basis of existing drug selectivity was understood. A mutagenesis approach determined the ligand-amino acid interactions required for ß1-selective affinity of xamoterol and nebivolol, followed by computer-based modeling to provide possible structural explanations. 3H-CGP12177 whole cell binding was conducted in Chinese hamster ovary cells stably expressing human ß1, ß2, and chimeric ß1/ß2-adrenoceptors (ARs). Single point mutations were investigated in transiently transfected cells. Modeling studies involved docking ligands into three-dimensional receptor structures and performing molecular dynamics simulations, comparing interaction frequencies between apo and holo structures of ß1 and ß2-ARs. From these observations, an ICI89406 derivative was investigated that gave further insights into selectivity. Stable cell line studies determined that transmembrane 2 was crucial for the ß1-selective affinity of xamoterol and nebivolol. Single point mutations determined that the ß1-AR isoleucine (I118) rather than the ß2 histidine (H93) explained selectivity. Studies of other ß1-ligands found I118 was important for ICI89406 selective affinity but not that for betaxolol, bisoprolol, or esmolol. Modeling studies suggested that the interaction energies and solvation of ß1-I118 and ß2-H93 are factors determining selectivity of xamoterol and ICI89406. ICI89406 without its phenyl group loses its high ß1-AR affinity, resulting in the same affinity as for the ß2-AR. The human ß1-AR residue I118 is crucial for the ß1-selective affinity of xamoterol, nebivolol, and ICI89406 but not all ß1-selective compounds. SIGNIFICANCE STATEMENT: Some ligands have selective binding affinity for the human ß1 versus the ß2-adrenoceptor; however, the molecular/structural reason for this is not known. The transmembrane 2 residue isoleucine I118 is responsible for the selective ß1-binding of xamoterol, nebivolol, and ICI89406 but does not explain the selective ß1-binding of betaxolol, bisoprolol, or esmolol. Understanding the structural basis of selectivity is important to improve computer-aided ligand design, and targeting I118 in ß1-adrenoceptors is likely to increase ß1-selectivity of drugs.

EP4 Receptor Conformation Sensor Suited for Ligand Screening and Imaging of Extracellular Prostaglandins.

Prostaglandins are important lipid mediators with a wide range of functions in the human body. They act mainly via plasma membrane localized prostaglandin receptors, which belong to the G-protein coupled receptor class. Due to their localized formation and short lifetime, it is important to be able to measure the distribution and abundance of prostaglandins in time and/or space. In this study, we present a Foerster resonance energy transfer (FRET)-based conformation sensor of the human prostaglandin E receptor subtype 4 (EP4 receptor), which was capable of detecting prostaglandin E2 (PGE2)-induced receptor activation in the low nanomolar range with a good signal-to-noise ratio. The sensor retained the typical selectivity for PGE2 among arachidonic acid products. Human embryonic kidney cells stably expressing the sensor did not produce detectable amounts of prostaglandins making them suitable for a coculture approach allowing us, over time, to detect prostaglandin formation in Madin-Darby canine kidney cells and primary mouse macrophages. Furthermore, the EP4 receptor sensor proved to be suited to detect experimentally generated PGE2 gradients by means of FRET-microscopy, indicating the potential to measure gradients of PGE2 within tissues. In addition to FRET-based imaging of prostanoid release, the sensor allowed not only for determination of PGE2 concentrations, but also proved to be capable of measuring ligand binding kinetics. The good signal-to-noise ratio at a commercial plate reader and the ability to directly determine ligand efficacy shows the obvious potential of this sensor interest for screening and characterization of novel ligands of the pharmacologically important human EP4 receptor. SIGNIFICANCE STATEMENT: The authors present a biosensor based on the prostaglandin E receptor subtype 4, which is well suited to measure extracellular prostaglandin E2 (PGE2) concentration with high temporal and spatial resolution. It can be used for the imaging of PGE2 levels and gradients by means of Foerster resonance energy transfer microscopy, and for determining PGE2 release of primary cells as well as for screening purposes in a plate reader setting.

Isoforms of GPR35 have distinct extracellular N-termini that allosterically modify receptor-transducer coupling and mediate intracellular pathway bias.

Within the intestine, the human G protein-coupled receptor (GPCR) GPR35 is involved in oncogenic signaling, bacterial infections, and inflammatory bowel disease. GPR35 is known to be expressed as two distinct isoforms that differ only in the length of their extracellular N-termini by 31 amino acids, but detailed insights into their functional differences are lacking. Through gene expression analysis in immune and gastrointestinal cells, we show that these isoforms emerge from distinct promoter usage and alternative splicing. Additionally, we employed optical assays in living cells to thoroughly profile both GPR35 isoforms for constitutive and ligand-induced activation and signaling of 10 different heterotrimeric G proteins, ligand-induced arrestin recruitment, and receptor internalization. Our results reveal that the extended N-terminus of the long isoform limits G protein activation yet elevates receptor-ß-arrestin interaction. To better understand the structural basis for this bias, we examined structural models of GPR35 and conducted experiments with mutants of both isoforms. We found that a proposed disulfide bridge between the N-terminus and extracellular loop 3, present in both isoforms, is crucial for constitutive G13 activation, while an additional cysteine contributed by the extended N-terminus of the long GPR35 isoform limits the extent of agonist-induced receptor-ß-arrestin2 interaction. The pharmacological profiles and mechanistic insights of our study provide clues for the future design of isoform-specific GPR35 ligands that selectively modulate GPR35-transducer interactions and allow for mechanism-based therapies against, for example, inflammatory bowel disease or bacterial infections of the gastrointestinal system.

GPCRmd uncovers the dynamics of the 3D-GPCRome.

G-protein-coupled receptors (GPCRs) are involved in numerous physiological processes and are the most frequent targets of approved drugs. The explosion in the number of new three-dimensional (3D) molecular structures of GPCRs (3D-GPCRome) over the last decade has greatly advanced the mechanistic understanding and drug design opportunities for this protein family. Molecular dynamics (MD) simulations have become a widely established technique for exploring the conformational landscape of proteins at an atomic level. However, the analysis and visualization of MD simulations require efficient storage resources and specialized software. Here we present GPCRmd (http://gpcrmd.org/), an online platform that incorporates web-based visualization capabilities as well as a comprehensive and user-friendly analysis toolbox that allows scientists from different disciplines to visualize, analyze and share GPCR MD data. GPCRmd originates from a community-driven effort to create an open, interactive and standardized database of GPCR MD simulations.

Publisher Correction: GPCRmd uncovers the dynamics of the 3D-GPCRome.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

On the construction of LIECE models for the serotonin receptor 5-HT[Formula: see text]R.

Computer-aided approaches to ligand design need to balance accuracy with speed. This is particularly true for one of the key parameters to be optimized during ligand development, the free energy of binding ([Formula: see text]G[Formula: see text]). Here, we developed simple models based on the Linear Interaction Energy approximation to free energy calculation for a G protein-coupled receptor, the serotonin receptor 2A, and critically evaluated their accuracy. Several lessons can be taken from our calculations, providing information on the influence of the docking software used, the conformational state of the receptor, the cocrystallized ligand, and its comparability to the training/test ligands.

Structure-based development of a subtype-selective orexin 1 receptor antagonist.

Orexins are neuropeptides that activate the rhodopsin-like G protein-coupled receptors OX1R and OX2R. The orexin system plays an important role in the regulation of the sleep-wake cycle and the regulation of feeding and emotions. The nonselective orexin receptor antagonist suvorexant has been the first drug on the market targeting the orexin system and is prescribed for the treatment of insomnia. Subtype-selective OX1R antagonists are valuable tools to further investigate the functions and physiological role of the OX1R in vivo and promising lead compounds for the treatment of drug addiction, anxiety, pain or obesity. Starting from the OX1R and OX2R crystal structures bound to suvorexant, we exploited a single amino acid difference in the orthosteric binding site by using molecular docking and structure-based drug design to optimize ligand interactions with the OX1R while introducing repulsive interactions with the OX2R. A newly established enantiospecific synthesis provided ligands showing up to 75-fold selectivity for the OX1R over the OX2R subtype. The structure of a new OX1R antagonist with subnanomolar affinity (JH112) was determined by crystallography in complex with the OX1R and corresponded closely to the docking-predicted geometry. JH112 exhibits high selectivity over a panel of different GPCRs, is able to cross the blood-brain barrier and acts as slowly diffusing and insurmountable antagonist for Gq protein activation and in particular ß-arrestin-2 recruitment at OX1R. This study demonstrates the potential of structure-based drug design to develop more subtype-selective GPCR ligands with potentially reduced side effects and provides an attractive probe molecule and lead compound.

NMR-Based Metabolite Profiling and the Application of STOCSY toward the Quality and Authentication Assessment of European EVOOs.

Extra virgin olive oil (EVOO) possesses a high-value rank in the food industry, thus making it a common target for adulteration. Hence, several methods have been essentially made available over the years. However, the issue of authentication remains unresolved with national and food safety organizations globally struggling to regulate and control its market. Over the course of this study, the aim was to determine the origin of EVOOs suggesting a high-throughput, state-of-the-art method that could be easily adopted. A rapid, NMR-based untargeted metabolite profiling method was applied and complemented by multivariate analysis (MVA) and statistical total correlation spectroscopy (STOCSY). STOCSY is a valuable statistical tool contributing to the biomarker identification process and was employed for the first time in EVOO analysis. Market samples from three Mediterranean countries of Spain, Italy, and Greece, blended samples from these countries, as well as monocultivar samples from Greece were analyzed. The NMR spectra were collected, with the help of chemometrics acting as "fingerprints" leading to the discovery of certain chemical classes and single biomarkers that were related to the classification of the samples into groups based on their origin.

Interrogating dense ligand chemical space with a forward-synthetic library.

Forward-synthetic databases are an efficient way to enumerate chemical space. We explored here whether these databases are good sources of novel protein ligands and how many molecules are obtainable and in which time frame. Based on docking calculations, series of molecules were selected to gain insights into the ligand structure-activity relationship. To evaluate the novelty of compounds in a challenging way, we chose the ß2-adrenergic receptor, for which a large number of ligands is already known. Finding dissimilar ligands is thus the exception rather than the rule. Here we report on the results, the successful synthesis of 127/240 molecules in just 2 weeks, the discovery of previously unreported dissimilar ligands of the ß2-adrenergic receptor, and the optimization of one series to a K D of 519 nM in only one round. Moreover, the finding that only 3 of 240 molecules had ever been synthesized before indicates that large parts of chemical space are unexplored.

Crystal structure of the human OX2 orexin receptor bound to the insomnia drug suvorexant.

The orexin (also known as hypocretin) G protein-coupled receptors (GPCRs) respond to orexin neuropeptides in the central nervous system to regulate sleep and other behavioural functions in humans. Defects in orexin signalling are responsible for the human diseases of narcolepsy and cataplexy; inhibition of orexin receptors is an effective therapy for insomnia. The human OX2 receptor (OX2R) belongs to the ß branch of the rhodopsin family of GPCRs, and can bind to diverse compounds including the native agonist peptides orexin-A and orexin-B and the potent therapeutic inhibitor suvorexant. Here, using lipid-mediated crystallization and protein engineering with a novel fusion chimaera, we solved the structure of the human OX2R bound to suvorexant at 2.5 Å resolution. The structure reveals how suvorexant adopts a π-stacked horseshoe-like conformation and binds to the receptor deep in the orthosteric pocket, stabilizing a network of extracellular salt bridges and blocking transmembrane helix motions necessary for activation. Computational docking suggests how other classes of synthetic antagonists may interact with the receptor at a similar position in an analogous π-stacked fashion. Elucidation of the molecular architecture of the human OX2R expands our understanding of peptidergic GPCR ligand recognition and will aid further efforts to modulate orexin signalling for therapeutic ends.

Analyzing Kinase Similarity in Small Molecule and Protein Structural Space to Explore the Limits of Multi-Target Screening.

While selective inhibition is one of the key assets for a small molecule drug, many diseases can only be tackled by simultaneous inhibition of several proteins. An example where achieving selectivity is especially challenging are ligands targeting human kinases. This difficulty arises from the high structural conservation of the kinase ATP binding sites, the area targeted by most inhibitors. We investigated the possibility to identify novel small molecule ligands with pre-defined binding profiles for a series of kinase targets and anti-targets by in silico docking. The candidate ligands originating from these calculations were assayed to determine their experimental binding profiles. Compared to previous studies, the acquired hit rates were low in this specific setup, which aimed at not only selecting multi-target kinase ligands, but also designing out binding to anti-targets. Specifically, only a single profiled substance could be verified as a sub-micromolar, dual-specific EGFR/ErbB2 ligand that indeed avoided its selected anti-target BRAF. We subsequently re-analyzed our target choice and in silico strategy based on these findings, with a particular emphasis on the hit rates that can be expected from a given target combination. To that end, we supplemented the structure-based docking calculations with bioinformatic considerations of binding pocket sequence and structure similarity as well as ligand-centric comparisons of kinases. Taken together, our results provide a multi-faceted picture of how pocket space can determine the success of docking in multi-target drug discovery efforts.

A Taxicab geometry quantification system to evaluate the performance of in silico methods: a case study on adenosine receptors ligands.

Among still comparatively few G protein-coupled receptors, the adenosine A2A receptor has been co-crystallized with several ligands, agonists as well as antagonists. It can thus serve as a template with a well-described orthosteric ligand binding region for adenosine receptors. As not all subtypes have been crystallized yet, and in order to investigate the usability of homology models in this context, multiple adenosine A1 receptor (A1AR) homology models had been previously obtained and a library of lead-like compounds had been docked. As a result, a number of potent and one selective ligand toward the intended target have been identified. However, in in vitro experimental verification studies, many ligands also bound to the A2AAR and the A3AR subtypes. In this work we asked the question whether a classification of the ligands according to their selectivity was possible based on docking scores. Therefore, we built an A3AR homology model and docked all previously found ligands to all three receptor subtypes. As a metric, we employed an in vitro/in silico selectivity ranking system based on taxicab geometry and obtained a classification model with reasonable separation. In the next step, the method was validated with an external library of, selective ligands with similarly good performance. This classification system might also be useful in further screens.

Comparative Docking to Distinct G Protein-Coupled Receptor Conformations Exclusively Yields Ligands with Agonist Efficacy.

G protein-coupled receptors exist in a whole spectrum of conformations that are stabilized by the binding of ligands with different efficacy or intracellular effector proteins. Here, we investigate whether three-dimensional structures of receptor conformations in different states of activation can be used to enrich ligands with agonist behavior in prospective docking calculations. We focused on the ß 2-adrenergic receptor, as it is currently the receptor with the highest number of active-state crystal structures. Comparative docking calculations to distinct conformations of the receptor were used for the in silico prediction of ligands with agonist efficacy. The pharmacology of molecules selected based on these predictions was characterized experimentally, resulting in a hit rate of 37% ligands, all of which were agonists. The ligands furthermore contain a pyrazole moiety that has previously not been described for ß 2-adrenergic receptor ligands, and one of them shows an intrinsic efficacy comparable to salbutamol. SIGNIFICANCE STATEMENT: Structure-based ligand design for G protein-coupled receptors crucially depends on receptor conformation and, hence, their activation state. We explored the influence of using multiple active-conformation X-ray structures on the hit rate of docking calculations to find novel agonists, and how to predict the most fruitful strategy to apply. The results suggest that aggregating the ranks of molecules across docking calculations to more than one active-state structure exclusively yields agonists.

Virtual Compound Libraries in Computer-Assisted Drug Discovery.

The use of virtual compound libraries in computer-assisted drug discovery has gained in popularity and has already lead to numerous successes. Here, we examine key static and dynamic virtual library concepts that have been developed over the past decade. To facilitate the search for new drugs in the vastness of chemical space, there are still several hurdles to overcome, including the current difficulties in screening and parsing efficiency and the need for more reliable vendors and accurate synthesis prediction tools. These challenges should be tackled by both the developers of virtual libraries and by their users, in order for the exploration of chemical space to live up to its potential.

PrenDB, a Substrate Prediction Database to Enable Biocatalytic Use of Prenyltransferases.

Prenyltransferases of the dimethylallyltryptophan synthase (DMATS) superfamily catalyze the attachment of prenyl or prenyl-like moieties to diverse acceptor compounds. These acceptor molecules are generally aromatic in nature and mostly indole or indole-like. Their catalytic transformation represents a major skeletal diversification step in the biosynthesis of secondary metabolites, including the indole alkaloids. DMATS enzymes thus contribute significantly to the biological and pharmacological diversity of small molecule metabolites. Understanding the substrate specificity of these enzymes could create opportunities for their biocatalytic use in preparing complex synthetic scaffolds. However, there has been no framework to achieve this in a rational way. Here, we report a chemoinformatic pipeline to enable prenyltransferase substrate prediction. We systematically catalogued 32 unique prenyltransferases and 167 unique substrates to create possible reaction matrices and compiled these data into a browsable database named PrenDB. We then used a newly developed algorithm based on molecular fragmentation to automatically extract reactive chemical epitopes. The analysis of the collected data sheds light on the thus far explored substrate space of DMATS enzymes. To assess the predictive performance of our virtual reaction extraction tool, 38 potential substrates were tested as prenyl acceptors in assays with three prenyltransferases, and we were able to detect turnover in >55% of the cases. The database, PrenDB (www.kolblab.org/prendb.php), enables the prediction of potential substrates for chemoenzymatic synthesis through substructure similarity and virtual chemical transformation techniques. It aims at making prenyltransferases and their highly regio- and stereoselective reactions accessible to the research community for integration in synthetic work flows.

The quorum-sensing regulator ComA from Bacillus subtilis activates transcription using topologically distinct DNA motifs.

ComA-like transcription factors regulate the quorum response in numerous Gram-positive bacteria. ComA proteins belong to the tetrahelical helix-turn-helix superfamily of transcriptional activators, which bind as homodimers to inverted sequence repeats in the DNA. Here, we report that ComA from Bacillus subtilis recognizes a topologically distinct motif, in which the binding elements form a direct repeat. We provide in vitro and in vivo evidence that the canonical and non-canonical site play an important role in facilitating type I and type II promoter activation, respectively, by interacting with different subunits of RNA polymerase. We furthermore show that there is a variety of contexts in which the non-canonical site can occur and identify new direct target genes that are located within the integrative and conjugative element ICEBs1. We therefore suggest that ComA acts as a multifunctional transcriptional activator and provides a striking example for complexity in protein-DNA interactions that evolved in the context of quorum sensing.