Cristian G. Bologa

In vivo Effects of a GPR30 Antagonist

Estrogen is central to many physiological processes throughout the human body. We have previously shown that the G protein-coupled receptor GPR30/GPER, in addition to classical nuclear estrogen receptors (ERα/β), activates cellular signaling pathways in response to estrogen. In order to distinguish between the actions of classical estrogen receptors and GPR30, we have previously characterized a selective agonist of GPR30, G-1 (1). To complement the pharmacological properties of G-1, we sought to identify an antagonist of GPR30 that displays similar selectivity against the classical estrogen receptors. Here we describe the identification and characterization of a G-1 analog, G15 (2) that binds to GPR30 with high affinity and acts as an antagonist of estrogen signaling through GPR30. In vivo administration of G15 reveals that GPR30 contributes to both uterine and neurological responses initiated by estrogen. The identification of this antagonist will accelerate the evaluation of the roles of GPR30 in human physiology.

A comprehensive map of molecular drug targets

The success of mechanism-based drug discovery depends on the definition of the drug target. This definition becomes even more important as we try to link drug response to genetic variation, understand stratified clinical efficacy and safety, rationalize the differences between drugs in the same therapeutic class and predict drug utility in patient subgroups. However, drug targets are often poorly defined in the literature, both for launched drugs and for potential therapeutic agents in discovery and development. Here, we present an updated comprehensive map of molecular targets of approved drugs. We curate a total of 893 human and pathogen-derived biomolecules through which 1,578 US FDA-approved drugs act. These biomolecules include 667 human-genome-derived proteins targeted by drugs for human disease. Analysis of these drug targets indicates the continued dominance of privileged target families across disease areas, but also the growth of novel first-in-class mechanisms, particularly in oncology. We explore the relationships between bioactivity class and clinical success, as well as the presence of orthologues between human and animal models and between pathogen and human genomes. Through the collaboration of three independent teams, we highlight some of the ongoing challenges in accurately defining the targets of molecular therapeutics and present conventions for deconvoluting the complexities of molecular pharmacology and drug efficacy.

Identification of a GPER/GPR30 antagonist with improved estrogen receptor counterselectivity

GPER/GPR30 is a seven-transmembrane G protein-coupled estrogen receptor that regulates many aspects of mammalian biology and physiology. We have previously described both a GPER-selective agonist G-1 and antagonist G15 based on a tetrahydro-3H-cyclopenta[c]quinoline scaffold. The antagonist lacks an ethanone moiety that likely forms important hydrogen bonds involved in receptor activation. Computational docking studies suggested that the lack of the ethanone substituent in G15 could minimize key steric conflicts, present in G-1, that limit binding within the ERα ligand binding pocket. In this report, we identify low-affinity cross-reactivity of the GPER antagonist G15 to the classical estrogen receptor ERα. To generate an antagonist with enhanced selectivity, we therefore synthesized an isosteric G-1 derivative, G36, containing an isopropyl moiety in place of the ethanone moiety. We demonstrate that G36 shows decreased binding and activation of ERα, while maintaining its antagonist profile towards GPER. G36 selectively inhibits estrogen-mediated activation of PI3K by GPER but not ERα. It also inhibits estrogen- and G-1-mediated calcium mobilization as well as ERK1/2 activation, with no effect on EGF-mediated ERK1/2 activation. Similar to G15, G36 inhibits estrogen- and G-1-stimulated proliferation of uterine epithelial cells in vivo. The identification of G36 as a GPER antagonist with improved ER counterselectivity represents a significant step towards the development of new highly selective therapeutics for cancer and other diseases.

Modulation of bitter taste perception by a small molecule hTAS2R antagonist

Human bitter taste is mediated by the hTAS2R family of G protein-coupled receptors. The discovery of the hTAS2Rs enables the potential to develop specific bitter receptor antagonists that could be beneficial as chemical probes to examine the role of bitter receptor function in gustatory and nongustatory tissues. In addition, they could have widespread utility in food and beverages fortified with vitamins, antioxidants, and other nutraceuticals, because many of these have unwanted bitter aftertastes. We employed a high-throughput screening approach to discover a novel bitter receptor antagonist (GIV3727) that inhibits activation of hTAS2R31 (formerly hTAS2R44) by saccharin and acesulfame K, two common artificial sweeteners. Pharmacological analyses revealed that GIV3727 likely acts as an orthosteric, insurmountable antagonist of hTAS2R31. Surprisingly, we also found that this compound could inhibit five additional hTAS2Rs, including the closely related receptor hTAS2R43. Molecular modeling and site-directed mutagenesis studies suggest that two residues in helix 7 are important for antagonist activity in hTAS2R31 and hTAS2R43. In human sensory trials, GIV3727 significantly reduced the bitterness associated with the two sulfonamide sweeteners, indicating that hTAS2R antagonists are active in vivo. Our results demonstrate that small molecule bitter receptor antagonists can effectively reduce the bitter taste qualities of foods, beverages, and pharmaceuticals.

A crowdsourcing evaluation of the NIH chemical probes.

Between 2004 and 2008, the US National Institutes of Health Molecular Libraries and Imaging initiative pilot phase funded 10 high-throughput screening centers, resulting in the deposition of 691 assays into PubChem and the nomination of 64 chemical probes. We crowdsourced the Molecular Libraries and Imaging initiative output to 11 experts, who expressed medium or high levels of confidence in 48 of these 64 probes.

Lead-like, drug-like or ''Pub-like'': how different are they?

Academic and industrial research continues to be focused on discovering new classes of compounds based on HTS. Post-HTS analyses need to prioritize compounds that are progressed to chemical probe or lead status. We report trends in probe, lead and drug discovery by examining the following categories of compounds: 385 leads and the 541 drugs that emerged from them; “active” (152) and “inactive” (1488) compounds from the Molecular Libraries Initiative Small Molecule Repository (MLSMR) tested by HTS; “active” (46) and “inactive” (72) compounds from Nature Chemical Biology (NCB) tested by HTS; compounds in the drug development phase (I, II, III and launched), as indexed in MDDR; and medicinal chemistry compounds from WOMBAT, separated into high-activity (5,784 compounds with nanomolar activity or better) and low-activity (30,690 with micromolar activity or less). We examined Molecular weight (MW), molecular complexity, flexibility, the number of hydrogen bond donors and acceptors, LogP—the octanol/water partition coefficient estimated by ClogP and ALOGPS), LogSw (intrinsic water solubility, estimated by ALOGPS) and the number of Rule of five (Ro5) criteria violations. Based on the 50% and 90% distribution moments of the above properties, there were no significant difference between leads of known drugs and “actives” from MLSMR or NCB (chemical probes). “Inactives” from NCB and MLSMR were also found to exhibit similar properties. From these combined sets, we conclude that “Actives” (569 compounds) are less complex, less flexible, and more soluble than drugs (1,651 drugs), and significantly smaller, less complex, less hydrophobic and more soluble than the 5,784 high-activity WOMBAT compounds. These trends indicate that chemical probes are similar to leads with respect to some properties, e.g., complexity, solubility, and hydrophobicity.

Associating Drugs, Targets and Clinical Outcomes into an Integrated Network Affords a New Platform for Computer-Aided Drug Repurposing

Finding new uses for old drugs is a strategy embraced by the pharmaceutical industry, with increasing participation from the academic sector. Drug repurposing efforts focus on identifying novel modes of action, but not in a systematic manner. With intensive data mining and curation, we aim to apply bio‐ and cheminformatics tools using the DRUGS database, containing 3837 unique small molecules annotated on 1750 proteins. These are likely to serve as drug targets and antitargets (i.e., associated with side effects, SE). The academic community, the pharmaceutical sector and clinicians alike could benefit from an integrated, semantic‐web compliant computer‐aided drug repurposing (CADR) effort, one that would enable deep data mining of associations between approved drugs (D), targets (T), clinical outcomes (CO) and SE. We report preliminary results from text mining and multivariate statistics, based on 7684 approved drug labels, ADL (Dailymed) via text mining. From the ADL corresponding to 988 unique drugs, the “adverse reactions” section was mapped onto 174 SE, then clustered via principal component analysis into a 5×5 self‐organizing map that was integrated into a Cytoscape network of SE‐D‐T‐CO. This type of data can be used to streamline drug repurposing and may result in novel insights that can lead to the identification of novel drug actions.

An automated PLS search for biologically relevant QSAR descriptors

An automated PLS engine, WB-PLS, was applied to 1632 QSAR series with at least 25 compounds per series extracted from WOMBAT (WOrld of Molecular BioAcTivity). WB-PLS extracts a single Y variable per series, as well as pre-computed X variables from a table. The table contained 2D descriptors, the drug-like MDL 320 keys as implemented in the Mesa A&C Fingerprint module, and in-house generated topological-pharmacophore SMARTS counts and fingerprints. Each descriptor type was treated as a block, with or without scaling. Cross-validation, variable importance on projections (VIP) above 0.8 and q2⩾0.3 were applied for model significance. Among cross-validation methods, leave-one-in-seven-out (CV7) is a better measure of model significance, compared to leave-one-out (measuring redundancy) and leave-half-out (too restrictive). SMARTS counts overlap with 2D descriptors (having a more quantitative nature), whereas MDL keys overlap with in-house fingerprints (both are more qualitative). The SMARTS counts is the most effective descriptor system, when compared to the other three. At the individual level, size-related descriptors and topological indices (in the 2D property space), and branched SMARTS, aromatic and ring atom types and halogens are found to be most relevant according to the VIP criterion.

High-Throughput Screening with HyperCyt® Flow Cytometry to Detect Small Molecule Formylpeptide Receptor Ligands

High-throughput flow cytometry (HTFC), enabled by faster automated sample processing, represents a promising high- content approach for compound library screening. HyperCyt® is a recently developed automated HTFC analysis system by which cell samples are rapidly aspirated from microplate wells and delivered to the flow cytometer. The formylpeptide receptor (FPR) family of G protein–coupled receptors contributes to the localization and activation of tissue-damaging leukocytes at sites of chronic inflammation. Here, the authors describe development and application of an HTFC screening approach to detect potential anti-inflammatory compounds that block ligand binding to FPR. Using a homogeneous no-wash assay, samples were routinely processed at 1.5 s/well (~2500 cells analyzed/sample), allowing a 96-well plate to be processed in less than 2.5 min. Assay sensitivity and accuracy were validated by detection of a previously documented active compound with relatively low FPR affinity (sulfinpyrazone, inhibition constant [Ki]=14 μM) from among a collection of 880 compounds in the Prestwick Chemical Library. The HyperCyt® system was therefore demonstrated to be a robust, sensitive, and highly quantitative method with which to screen lead compound libraries in a 96-well format.

Community-wide assessment of GPCR structure modelling and ligand docking

Recent breakthroughs in the determination of the crystal structures of G protein-coupled receptors (GPCRs) have provided new opportunities for structure-based drug design strategies targeting this protein family. With the aim of evaluating the current status of GPCR structure prediction and ligand docking, a community-wide, blind prediction assessment — GPCR Dock 2008 — was conducted in coordination with the publication of the crystal structure of the human adenosine A2A receptor bound to the ligand ZM241385. Twenty-nine groups submitted 206 structural models before the release of the experimental structure, which were evaluated for the accuracy of the ligand binding mode and the overall receptor model compared with the crystal structure. This analysis highlights important aspects for success and future development, such as accurate modelling of structurally divergent regions and use of additional biochemical insight such as disulphide bridges in the extracellular loops.