Multiple ligand detection and affinity measurement by ultrafiltration and mass spectrometry analysis applied to fragment mixture screening

Binding affinity of a small molecule drug candidate to a therapeutically relevant biomolecular target is regarded the first determinant of the candidate's efficacy. Although the ultrafiltration-LC/MS (UF-LC/MS) assay enables efficient ligand discovery for a specific target from a mixed pool of compounds, most previous analysis allowed for relative affinity ranking of different ligands. Moreover, the reliability of affinity measurement for multiple ligands with UF-LC/MS has hardly been strictly evaluated. In this study, we examined the accuracy of K_d determination through UF-LC/MS by comparison with classical ITC measurement. A single-point K_d calculation method was found to be suitable for affinity measurement of multiple ligands bound to the same target when binding competition is minimized. A second workflow based on analysis of the unbound fraction of compounds was then developed, which simplified sample preparation as well as warranted reliable ligand discovery. The new workflow implemented in a fragment mixture screen afforded rapid and sensitive detection of low-affinity ligands selectively bound to the RNA polymerase NS5B of hepatitis C virus. More importantly, ligand identification and affinity measurement for mixture-based fragment screens by UF-LC/MS were in good accordance with single ligand evaluation by conventional SPR analysis. This new approach is expected to become a valuable addition to the arsenal of high-throughput screening techniques for fragment-based drug discovery.     

Identification and characterization of mGlu3 ligands using a high throughput FLIPR assay for detection of agonists, antagonists, and allosteric modulators

When targeting G-protein coupled receptors (GPCRs) in early stage drug discovery, or for novel targets, the type of ligand most likely to produce the desired therapeutic effect may be unknown. Therefore, it can be desirable to identify potential lead compounds from multiple categories: agonists, antagonists, and allosteric modulators. In this study, we developed a triple addition calcium flux assay using FLIPR Tetra to identify multiple ligand classes for the metabotropic glutamate receptor 3 (mGlu3), using a cell line stably co-expressing the human G-protein-coupled mGlu3 receptor, a promiscuous G-protein (G(α16)), and rat Glast, a glutamate transporter. Compounds were added to the cells followed by stimulation with EC(10) and then EC(80) concentration of glutamate, the physiological agonist for mGlu receptors. This format produced a robust assay, facilitating the identification of agonists, positive allosteric modulators and antagonists/negative allosteric modulators. Follow up experiments were conducted to exclude false positives. Using this approach, we screened a library of approximately 800,000 compounds using FLIPR Tetra and identified viable leads for all three ligand classes. Further characterization revealed the selectivity of individual ligands.     

Polypharmacology directed compound data mining: identification of promiscuous chemotypes with different activity profiles and comparison to approved drugs

Increasing evidence that many pharmaceutically relevant compounds elicit their effects through binding to multiple targets, so-called polypharmacology, is beginning to change conventional drug discovery and design strategies. In light of this paradigm shift, we have mined publicly available compound and bioactivity data for promiscuous chemotypes. For this purpose, a hierarchy of active compounds, atomic property based scaffolds, and unique molecular topologies were generated, and activity annotations were analyzed using this framework. Starting from ～35?000 compounds active against human targets with at least 1 μM potency, 33 chemotypes with distinct topology were identified that represented molecules active against at least 3 different target families. Network representations were utilized to study scaffold-target family relationships and activity profiles of scaffolds corresponding to promiscuous chemotypes. A subset of promiscuous chemotypes displayed a significant enrichment in drugs over bioactive compounds. A total of 190 drugs were identified that had on average only 2 known target annotations but belonged to the 7 most promiscuous chemotypes that were active against 8-15 target families. These drugs should be attractive candidates for polypharmacological profiling.     

Snooker: a structure-based pharmacophore generation tool applied to class A GPCRs

G-protein coupled receptors (GPCRs) are important drug targets for various diseases and of major interest to pharmaceutical companies. The function of individual members of this protein family can be modulated by the binding of small molecules at the extracellular side of the structurally conserved transmembrane (TM) domain. Here, we present Snooker, a structure-based approach to generate pharmacophore hypotheses for compounds binding to this extracellular side of the TM domain. Snooker does not require knowledge of ligands, is therefore suitable for apo-proteins, and can be applied to all receptors of the GPCR protein family. The method comprises the construction of a homology model of the TM domains and prioritization of residues on the probability of being ligand binding. Subsequently, protein properties are converted to ligand space, and pharmacophore features are generated at positions where protein ligand interactions are likely. Using this semiautomated knowledge-driven bioinformatics approach we have created pharmacophore hypotheses for 15 different GPCRs from several different subfamilies. For the beta-2-adrenergic receptor we show that ligand poses predicted by Snooker pharmacophore hypotheses reproduce literature supported binding modes for ～75% of compounds fulfilling pharmacophore constraints. All 15 pharmacophore hypotheses represent interactions with essential residues for ligand binding as observed in mutagenesis experiments and compound selections based on these hypotheses are shown to be target specific. For 8 out of 15 targets enrichment factors above 10-fold are observed in the top 0.5% ranked compounds in a virtual screen. Additionally, prospectively predicted ligand binding poses in the human dopamine D3 receptor based on Snooker pharmacophores were ranked among the best models in the community wide GPCR dock 2010.     

Detecting drug promiscuity using gaussian ensemble screening

Polypharmacology describes the binding of a ligand to multiple protein targets (a promiscuous ligand) or multiple diverse ligands binding to a given target (a promiscuous target). Pharmaceutical companies are discovering increasing numbers of both promiscuous drugs and drug targets. Hence, polypharmacology is now recognized as an important aspect of drug design. Here, we describe a new and fast way to predict polypharmacological relationships between drug classes quantitatively, which we call Gaussian Ensemble Screening (GES). This approach represents a cluster of molecules with similar spherical harmonic surface shapes as a Gaussian distribution with respect to a selected center molecule. Calculating the Gaussian overlap between pairs of such clusters allows the similarity between drug classes to be calculated analytically without requiring thousands of bootstrap comparisons, as in current promiscuity prediction approaches. We find that such cluster similarity scores also follow a Gaussian distribution. Hence, a cluster similarity score may be transformed into a probability value, or "p-value", in order to quantify the relationships between drug classes. We present results obtained when using the GES approach to predict relationships between drug classes in a subset of the MDL Drug Data Report (MDDR) database. Our results indicate that GES is a useful way to study polypharmacology relationships, and it could provide a novel way to propose new targets for drug repositioning.     

SEC–MS as an Approach to Isolate and Directly Identifying Small Molecular GPCR–Ligands from Complex Mixtures Without Labeling

G protein coupled receptors (GPCRs) belong to the most successful targets in drug discovery. However, the development of assays with an appropriately labeled high affinity reporter compound is laborious. In the present study an MS-based binding assay is described using the rat histamine receptor 2 (rH2) as a model GPCR system. Instead of using a purified receptor it is demonstrated that it is possible to use an unpurified receptor to extract active compounds from a solution or small mixture of compounds. By using SEC it is possible to separate the bound ligand from the unbound ligand. The major advantage of this approach is that there is no labeling of ligands required (direct monitoring based on the appropriate m/z values).     

Alchemical free energy calculations via metadynamics: Application to the theophylline-RNA aptamer complex

We propose a computational workflow for robust and accurate prediction of both binding poses and their affinities at early stage in designing drug candidates. Small, rigid ligands with few intramolecular degrees of freedom, for example, fragment-like molecules, have multiple binding poses, even at a single binding site, and their affinities are often close to each other. We explore various structures of ligand binding to a target through metadynamics using a small number of collective variables, followed by reweighting to obtain the atomic coordinates. After identifying each binding pose by cluster analysis, we perform alchemical free energy calculations on each structure to obtain the overall value. We applied this protocol in computing free energy of binding for the theophylline-RNA aptamer complex. Of the six (meta)stable structures found, the most favorable binding structure is consistent with the structure obtained by NMR. The overall free energy of binding reproduces the experimental values very well.     

Identification of a β1/β2‐Specific Sulfonamide Proteasome Ligand by Crystallographic Screening

The proteasome represents a validated drug target for the treatment of cancer, however, new types of inhibitors are required to tackle the development of resistant tumors. Current fluorescence‐based screening methods suffer from low sensitivity and are limited to the detection of ligands with conventional binding profiles. In response to these drawbacks, a crystallographic screening procedure for the discovery of agents with a novel mode of action was utilized. The optimized workflow was applied to the screening of a focused set of compounds, resulting in the discovery of a β1/β2‐specific sulfonamide derivative that noncovalently binds between subunits β1 and β2. The binding pocket displays significant differences in size and polarity between the immuno‐ and constitutive proteasome. The identified ligand thus provides valuable insights for the future structure‐based design of subtype‐specific proteasome inhibitors.     

Structural Insights into Ligand—Receptor Interactions Involved in Biased Agonism of G-Protein Coupled Receptors

G protein-coupled receptors (GPCRs) are versatile signaling proteins that mediate complex cellular responses to hormones and neurotransmitters. Ligand directed signaling is observed when agonists, upon binding to the same receptor, trigger significantly different configuration of intracellular events. The current work reviews the structurally defined ligand – receptor interactions that can be related to specific molecular mechanisms of ligand directed signaling across different receptors belonging to class A of GPCRs. Recent advances in GPCR structural biology allow for mapping receptors’ binding sites with residues particularly important in recognition of ligands’ structural features that are responsible for biased signaling. Various studies show particular role of specific residues lining the extended ligand binding domains, biased agonists may alternatively affect their interhelical interactions and flexibility what can be translated into intracellular loop rearrangements. Studies on opioid and angiotensin receptors indicate importance of residues located deeper within the binding cavity and direct interactions with receptor residues linking the ortosteric ligand binding site with the intracellular transducer binding domain. Collection of results across different receptors may suggest elements of common molecular mechanisms which are responsible for passing alternative signals from biased agonists.     

Activation of G-protein-coupled receptors in cell-derived plasma membranes supported on porous beads

G-protein-coupled receptors (GPCRs) are ubiquitous mediators of signal transduction across cell membranes and constitute a very important class of therapeutic targets. In order to study the complex biochemical signaling network coupling to the intracellular side of GPCRs, it is necessary to engineer and control the downstream signaling components, which is difficult to realize in living cells. We have developed a bioanalytical platform enabling the study of GPCRs in their native membrane transferred inside-out from live cells to lectin-coated beads, with both membrane sides of the receptor being accessible for molecular interactions. Using heterologously expressed adenosine A(2A) receptor carrying a yellow fluorescent protein, we showed that the tethered membranes comprised fully functional receptors in terms of ligand and G protein binding. The interactions between the different signaling partners during the formation and subsequent dissociation of the ternary signaling complex on single beads could be observed in real time using multicolor fluorescence microscopy. This approach of tethering inside-out native membranes accessible from both sides is straightforward and readily applied to other transmembrane proteins. It represents a generic platform suitable for ensemble as well as single-molecule measurements to investigate signaling processes at plasma membranes.     

A14-[125I]monoiodoinsulin purified by different high-performance liquid chromatographic procedures and by polyacrylamide gel electrophoresis: preparation, immunochemical properties and receptor binding affinity

Reversed-phase high-performance liquid chromatography (RP-HPLC) allows the rapid separation of A14-[125I]monoiodoinsulin directly from the iodination mixtures. It remains to be clarified, however, whether the RP-HPLC chromatographic conditions affect the properties of the purified tracer. In this study we prepared A14-[125I]insulin purified by polyacrylamide gel electrophoresis (PAGE) and by three different RP-HPLC mobile phases containing, respectively, ammonium acetate, sodium perchlorate and trifluoroacetic acid. The binding characteristics of all these tracers were examined using an insulin antiserum and insulin cell receptors. The specific radioactivity corresponded to the theoretical maximum for the RP-HPLC-purified tracers and was significantly lower for the PAGE-purified tracers. Significant differences were found in the binding of different tracers to the insulin antiserum: maximum binding ranged from 94 to 99% and was significantly lower for tracers purified by RP-HPLC eluents B and C; antiserum dilution giving 50% tracer binding was lower for tracers purified by RP-HPLC eluent B. The four insulin derivatives showed no difference in non-specific precipitation and in the affinity constant values calculated from the Scatchard analysis. No significant difference was found in the binding of the four insulin derivatives to the human-cultured IM-9 lymphocytes and to the human circulating monocytes. In conclusion, the present work demonstrates that the immunological properties of the A14-[125I]monoiodoinsulin purified by RP-HPLC may be partially affected by the composition of the mobile phase. In order to obtain a fully potent A14-[125I]insulin derivative and to have the possibility of comparing data from different laboratories, the chromatographic conditions must be taken into account.     

Mechanistic Studies on the Stereoselectivity of the Serotonin 5‐HT1A Receptor

G‐protein‐coupled receptors (GPCRs) are involved in a wide range of physiological processes, and they have attracted considerable attention as important targets for developing new medicines. A central and largely unresolved question in drug discovery, which is especially relevant to GPCRs, concerns ligand selectivity: Why do certain molecules act as activators (agonists) whereas others, with nearly identical structures, act as blockers (antagonists) of GPCRs? To address this question, we employed all‐atom, long‐timescale molecular dynamics simulations to investigate how two diastereomers (epimers) of dihydrofuroaporphine bind to the serotonin 5‐HT_1A receptor and exert opposite effects. By using molecular interaction fingerprints, we discovered that the agonist could mobilize nearby amino acid residues to act as molecular switches for the formation of a continuous water channel. In contrast, the antagonist epimer remained firmly stabilized in the binding pocket.     

Rapid protein-ligand costructures using chemical shift perturbations

Structure-based drug discovery requires the iterative determination of protein-ligand costructures in order to improve the binding affinity and selectivity of potential drug candidates. In general, X-ray and NMR structure determination methods are time consuming and are typically the limiting factor in the drug discovery process. The application of molecular docking simulations to filter and evaluate drug candidates has become a common method to improve the throughput and efficiency of structure-based drug design. Unfortunately, molecular docking methods suffer from common problems that include ambiguous ligand conformers or failure to predict the correct docked structure. A rapid approach to determine accurate protein-ligand costructures is described based on NMR chemical shift perturbation (CSP) data routinely obtained using 2D 1H-15N HSQC spectra in high-throughput ligand affinity screens. The CSP data is used to both guide and filter AutoDock calculations using our AutoDockFilter program. This method is demonstrated for 19 distinct protein-ligand complexes where the docked conformers exhibited an average rmsd of 1.17 +/- 0.74 A relative to the original X-ray structures for the protein-ligand complexes.     

Design of Drug Efficacy Guided by Free Energy Simulations of the β2-Adrenoceptor

G-protein-coupled receptors (GPCRs) play important roles in physiological processes and are modulated by drugs that either activate or block signaling. Rational design of the pharmacological efficacy profiles of GPCR ligands could enable the development of more efficient drugs, but is challenging even if high-resolution receptor structures are available. We performed molecular dynamics simulations of the β₂ adrenergic receptor in active and inactive conformations to assess if binding free energy calculations can predict differences in ligand efficacy for closely related compounds. Previously identified ligands were successfully classified into groups with comparable efficacy profiles based on the calculated shift in ligand affinity upon activation. A series of ligands were then predicted and synthesized, leading to the discovery of partial agonists with nanomolar potencies and novel scaffolds. Our results demonstrate that free energy simulations enable design of ligand efficacy and the same approach can be applied to other GPCR drug targets.     

EF-Tu binding peptides identified,dissected, and affinity optimized by phage display

The highly abundant GTP binding protein elongation factor Tu (EF-Tu) fulfills multiple roles in bacterial protein biosynthesis. Phage-displayed peptides with high affinity for EF-Tu were selected from a library of approximately 4.7 x 10(11) different peptides. The lack of sequence homology among the identified EF-Tu ligands demonstrates promiscuous peptide binding by EF-Tu. Homolog shotgun scanning of an EF-Tu ligand was used to dissect peptide molecular recognition by EF-Tu. All homolog shotgun scanning selectants bound to EF-Tu with higher affinity than the starting ligand. Thus, homolog shotgun scanning can simultaneously optimize binding affinity and rapidly provide detailed structure activity relationships for multiple side chains of a polypeptide ligand. The reported peptide ligands do not compete for binding to EF-Tu with various antibiotic EF-Tu inhibitors, and could identify an EF-Tu peptide binding site distinct from the antibiotic inhibitory sites.     

Using silico methods predicting ligands for orphan GPCRs

The G-protein coupled receptor (GPCR) superfamily is one of the most important drug target classes for the pharmaceutical industry. The completion of the human genome project has revealed that there are more than 300 potential GPCR targets of interest. The identification of their natural ligands can gain significant insights into regulatory mechanisms of cellular signaling networks and provide unprecedented opportunities for drug discovery. Much effort has been directed towards the GPCR ligand discovery study by both academic institutions and pharmaceutical industries. However, the endogenous ligands still remain unknown for about 150 GPCRs in the human genome. It is necessary to develop new strategies to predict candidate ligands for these so-called orphan receptors. Computational techniques are playing an increasingly important role in finding and validating novel ligands for orphan GPCRs (oGPCRs). In this paper, we focus on recent development in applying bioinformatics approaches for the discovery of GPCR ligands. In addition, some of the data resources for ligand identification are also provided.     

Environment-Sensitive Fluorescence of 7-Nitrobenz-2-oxa-1,3-diazol-4-yl (NBD)-Labeled Ligands for Serotonin Receptors

Serotonin is a neurotransmitter that plays a crucial role in the regulation of several behavioral and cognitive functions by binding to a number of different serotonin receptors present on the cell surface. We report here the synthesis and characterization of several novel fluorescent analogs of serotonin in which the fluorescent NBD (7-nitrobenz-2-oxa-1,3-diazol-4-yl) group is covalently attached to serotonin. The fluorescent ligands compete with the serotonin_1A receptor specific radiolabeled agonist for binding to the receptor. Interestingly, these fluorescent ligands display a high environmental sensitivity of their fluorescence. Importantly, the human serotonin_1A receptor stably expressed in CHO-K1 cells could be specifically labeled with one of the fluorescent ligands with minimal nonspecific labeling. Interestingly, we show by spectral imaging that the NBD-labeled ligand exhibits a red edge excitation shift (REES) of 29 nm when bound to the receptor, implying that it is localized in a restricted microenvironment. Taken together, our results show that NBD-labeled serotonin analogs offer an attractive fluorescent approach for elucidating the molecular environment of the serotonin binding site in serotonin receptors. In view of the multiple roles played by the serotonergic systems in the central and peripheral nervous systems, these fluorescent ligands would be useful in future studies involving serotonin receptors.     

G protein betagamma subunits as targets for small molecule therapeutic development

G proteins mediate the action of G protein coupled receptors (GPCRs), a major target of current pharmaceuticals and a major target of interest in future drug development. Most pharmaceutical interest has been in the development of selective GPCR agonists and antagonists that activate or inhibit specific GPCRs. Some recent thinking has focused on the idea that some pathologies are the result of the actions of an array of GPCRs suggesting that targeting single receptors may have limited efficacy. Thus, targeting pathways common to multiple GPCRs that control critical pathways involved in disease has potential therapeutic relevance. G protein betagamma subunits released from some GPCRs upon receptor activation regulate a variety of downstream pathways to control various aspects of mammalian physiology. There is evidence from cell- based and animal models that excess Gbetagamma signaling can be detrimental and blocking Gbetagamma signaling has salutary effects in a number of pathological models. Gbetagamma regulates downstream pathways through modulation of enzymes that produce cellular second messengers or through regulation of ion channels by direct protein-protein interactions. Thus, blocking Gbetagamma functions requires development of small molecule agents that disrupt Gbetagamma protein interactions with downstream partners. Here we discuss evidence that small molecule targeting Gbetagamma could be of therapeutic value. The concept of disruption of protein-protein interactions by targeting a "hot spot" on Gbetagamma is delineated and the biochemical and virtual screening strategies for identification of small molecules that selectively target Gbetagamma functions are outlined. Evaluation of the effectiveness of virtual screening indicates that computational screening enhanced identification of true Gbetagamma binding molecules. However, further refinement of the approach could significantly improve the yield of Gbetagamma binding molecules from this screen that could result in multiple candidate leads for future drug development.     

Small Molecule Tools to Study Cellular Target Engagement for the Intracellular Allosteric Binding Site of GPCRs

A conserved intracellular allosteric binding site (IABS) has recently been identified at several G protein-coupled receptors (GPCRs). Ligands targeting the IABS, so-called intracellular allosteric antagonists, are highly promising compounds for pharmaceutical intervention and currently evaluated in several clinical trials. Beside co-crystal structures that laid the foundation for the structure-based development of intracellular allosteric GPCR antagonists, small molecule tools that enable an unambiguous identification and characterization of intracellular allosteric GPCR ligands are of utmost importance for drug discovery campaigns in this field. Herein, we discuss recent approaches that leverage cellular target engagement studies for the IABS and thus play a critical role in the evaluation of IABS-targeted ligands as potential therapeutic agents.     

Competitive fluorescence polarization assays for the detection of phosphoinositide kinase and phosphatase activity

We describe the development and implementation of competitive fluorescence polarization (FP) based assays for determining activity of phosphoinositide 3-kinase (PI 3-K) and the type-II SH2-domain-containing inositol 5-phosphatase (SHIP2). These assays are based on the interaction of specific phosphoinositide binding proteins with fluorophore-labeled phosphoinositide and inositol phosphate tracers. Enzyme reaction products are detected by their ability to compete with the fluorescent tracers for protein binding, leading to an increase in the amount of free tracer and a decrease in polarization (mP) values. A variety of fluorophore-labeled tracers were evaluated, and assay sensitivity and specificity for products of PI 3-K and SHIP2 activity was determined. Assay performance was evaluated using recombinant PI 3-Kalpha and SHIP2 with diC(8)-PI(4,5)P(2) and diC(8)-PI(3,4,5)P(3) as respective substrates. IC(50) values for previously characterized PI 3-K inhibitors were within expected ranges. These assays are homogeneous, sensitive, and rapid, and suitable for HTS applications, and will facilitate screening for novel inhibitors of phosphoinositide kinases and phosphatases in drug development.