A categorical structure–activity relationship analysis of GPR119 ligands

The categorical structure–activity relationship (cat-SAR) expert system has been successfully used in the analysis of chemical compounds that cause toxicity. Herein we describe the use of this fragment-based approach to model ligands for the G protein-coupled receptor 119 (GPR119). Using compounds that are known GPR119 agonists and compounds that we have confirmed experimentally that are not GPR119 agonists, four distinct cat-SAR models were developed. Using a leave-one-out validation routine, the best GPR119 model had an overall concordance of 99%, a sensitivity of 99%, and a specificity of 100%. Our findings from the in-depth fragment analysis of several known GPR119 agonists were consistent with previously reported GPR119 structure–activity relationship (SAR) analyses. Overall, while our results indicate that we have developed a highly predictive cat-SAR model that can be potentially used to rapidly screen for prospective GPR119 ligands, the applicability domain must be taken into consideration. Moreover, our study demonstrates for the first time that the cat-SAR expert system can be used to model G protein-coupled receptor ligands, many of which are important therapeutic agents.     

Parameterization of the GPR119 Receptor Agonist AR231453

The GPR119 receptor is a class A G protein‐coupled receptor expressed mainly in pancreatic beta cells. Since GPR119 receptor activation ameliorates Type 2 Diabetes through an increase in glucose‐dependent insulin release, the development of new GPR119 receptor agonists would be worthwhile. A better understanding of the way agonists interact with the receptor would help to design better ligands for the receptor. It also would help to better understand the agonist mechanism of action. An understanding of how agonists interact with the receptor can be acquired using molecular dynamics simulations, which cannot be performed without having force field parameters for the ligand molecule. This study presents the development of CHARMM force field parameters for AR231453, the prototypical first potent and orally available GPR119 agonist, using the Force Field Tool Kit. The parameters are validated through Normal Mode Analysis calculations and molecular dynamics simulations in combination with infrared spectroscopy. © 2017 Wiley Periodicals, Inc.     

Potent estrogen agonists based on carborane as a hydrophobic skeletal structure. A new medicinal application of boron clusters

BACKGROUND: Carboranes (dicarba-closo-dodecaboranes) are a class of carbon-containing polyhedral boron-cluster compounds having remarkable thermal stability and exceptional hydrophobicity. Applications of the unique structural and chemical properties offered by icosahedral carboranes in boron neutron capture therapy have received increasing attention over the past 30 years. However, these features of carboranes may allow another application as a hydrophobic pharmacophore in biologically active molecules that interact hydrophobically with receptors. RESULTS: We have designed candidate estrogen-receptor-binding compounds having carborane as a hydrophobic skeletal structure and synthesized them. The most potent compound bearing a carborane cage exhibited activity at least 10-fold greater than that of 17beta-estradiol in the luciferase reporter gene assay. Estrogen receptor-alpha-binding data for the compound were consistent with the results of the luciferase reporter gene assay. The compound also showed potent in vivo effects on the recovery of uterine weight and bone loss in ovariectomized mice. CONCLUSION: Further development of the potent carborane-containing estrogenic agonists described here, having a new skeletal structure and unique characteristics, should yield novel therapeutic agents, especially selective estrogen receptor modulators. Furthermore, the suitability of the spherical carborane cage for binding to the cavity of the estrogen receptor-alpha ligand-binding domain should provide a basis for a similar approach to developing novel ligands for other steroid receptors.     

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.     

A virtual screen for diverse ligands: discovery of selective G protein-coupled receptor antagonists

Virtual screening has become a major focus of bioactive small molecule lead identification, and reports of agonists and antagonists discovered via virtual methods are becoming more frequent. G protein-coupled receptors (GPCRs) are the one class of protein targets for which success with this approach has been limited. This is likely due to the paucity of detailed experimental information describing GPCR structure and the intrinsic function-associated structural flexibility of GPCRs which present major challenges in the application of receptor-based virtual screening. Here we describe an in silico methodology that diminishes the effects of structural uncertainty, allowing for more inclusive representation of a potential docking interaction with exogenous ligands. Using this approach, we screened one million compounds from a virtual database, and a diverse subgroup of 100 compounds was selected, leading to experimental identification of five structurally diverse antagonists of the thyrotropin-releasing hormone receptors (TRH-R1 and TRH-R2). The chirality of the most potent chemotype was demonstrated to be important in its binding affinity to TRH receptors; the most potent stereoisomer was noted to have a 13-fold selectivity for TRH-R1 over TRH-R2. A comprehensive mutational analysis of key amino acid residues that form the putative binding pocket of TRH receptors further verified the binding modality of these small molecule antagonists. The described virtual screening approach may prove applicable in the search for novel small molecule agonists and antagonists of other GPCRs.     

A combined ligand-based and target-based drug design approach for G-protein coupled receptors: application to salvinorin A,a selective kappa opioid receptor agonist

Combined ligand-based and target-based drug design approaches provide a synergistic advantage over either method individually. Therefore, we set out to develop a powerful virtual screening model to identify novel molecular scaffolds as potential leads for the human KOP (hKOP) receptor employing a combined approach. Utilizing a set of recently reported derivatives of salvinorin A, a structurally unique KOP receptor agonist, a pharmacophore model was developed that consisted of two hydrogen bond acceptor and three hydrophobic features. The model was cross-validated by randomizing the data using the CatScramble technique. Further validation was carried out using a test set that performed well in classifying active and inactive molecules correctly. Simultaneously, a bovine rhodopsin based “agonist-bound” hKOP receptor model was also generated. The model provided more accurate information about the putative binding site of salvinorin A based ligands. Several protein structure-checking programs were used to validate the model. In addition, this model was in agreement with the mutation experiments carried out on KOP receptor. The predictive ability of the model was evaluated by docking a set of known KOP receptor agonists into the active site of this model. The docked scores correlated reasonably well with experimental pK _i values. It is hypothesized that the integration of these two independently generated models would enable a swift and reliable identification of new lead compounds that could reduce time and cost of hit finding within the drug discovery and development process, particularly in the case of GPCRs.Electronic supplementary material Supplementary material is available in the online version of this article at and is accessible for authorized users.     

Designing novel nicotinic agonists by searching a database of molecular shapes

Summary We introduce an approach by which novel ligands can be designed for a receptor if a pharmacophore geometry has been established and the receptor-bound conformations of other ligands are known. We use the shape-matching method of Kuntz et al. [J. Mol. Biol., 161 (1982) 269–288] to search a database of molecular shapes for those molecules which can fit inside the combined volume of the known ligands and which have interatomic distances compatible with the pharmacophore geometry. Some of these molecules are then modified by interactive modeling techniques to better match the chemical properties of the known ligands. Our shape database (about 5000 candidate molecules) is derived from a subset of the Cambridge Crystallographic Database [Allen et al., Acta Crystallogr., Sect. B,35 (1979) 2331–2339]. We show, as an example, how several novel designs for nicotinic agonists can be derived by this approach, given a pharmacophore model derived from known agonists [Sheridan et al., J. Med. Chem., 29 (1986) 889–906]. This report complements our previous report [DesJarlais et al., J. Med. Chem., in press], which introduced a similar method for designing ligands when the structure of the receptor is known.     

A reactivity pattern for discrimination of ER agonism and antagonism based on 3-D molecular attributes

Various models have been developed to predict the relative binding affinity (RBA) of chemicals to estrogen receptors (ER). These models can be used to prioritize chemicals for further tiered biological testing to assess the potential for endocrine disruption. One shortcoming of models predicting RBA has been the inability to distinguish potential receptor antagonism from agonism, and hence in vivo response. It has been suggested that steroid receptor antagonists are less compact than agonists; thus, ER binding of antagonists may prohibit proper alignment of receptor protein helices preventing subsequent transactivation. The current study tests the theory of chemical bulk as a defining parameter of antagonism by employing a 3-D structural approach for development of reactivity patterns for ER antagonists and agonists. Using a dataset of 23 potent ER ligands (16 agonists, 7 antagonists), molecular parameters previously found to be associated with ER binding affinity, namely global ( E HOMO ) and local (donor delocalizabilities and charges) electron donating ability of electronegative sites and steric distances between those sites, were found insufficient to discriminate ER antagonists from agonists. However, parameters related to molecular bulk, including solvent accessible surface and negatively charged Van der Waal's surface, provided reactivity patterns that were 100% successful in discriminating antagonists from agonists in the limited data set tested. The model also shows potential to discriminate pure antagonists from partial agonist/antagonist structures. Using this exploratory model it is possible to predict additional chemicals for their ability to bind but inactivate the ER, providing a further tool for hypothesis testing to elucidate chemical structural characteristics associated with estrogenicity and anti-estrogenicity.     

Design,synthesis and evaluation of potent G-protein coupled receptor 40 agonists

GPR40 has emerged as an attractive drug target for the treatment of type 2 diabetes due to its role in the enhancement of insulin secretion with glucose dependency. With the aim to improve the metabolic and safety profiles, a series of novel phenylpropionic acid derivatives were synthesized. Extensive structural optimization led to identification of compounds 22g and 23e as potent GPR40 agonists with moderate liver microsomal stability. All the discovery supported further exploration surrounding this scaffold.     

Specific GABA(A) agonists and partial agonists

The GABA(A) receptor system is implicated in a number of neurological and psychiatric diseases, making GABA(A) receptor ligands interesting as potential therapeutic agents. Only a few different classes of structures are currently known as ligands for the GABA recognition site on the hetero-pentameric GABA(A) receptor complex, reflecting the very strict structural requirements for GABA(A) receptor recognition and activation. Within the series of compounds showing agonist activity at the GABA(A) receptor site that have been developed, most of the ligands are structurally derived from the GABA(A) agonists muscimol, THIP, or isoguvacine, which we developed in the initial stages of the project. Using recombinant GABA(A) receptors, functional selectivity was demonstrated for a number of compounds, including THIP, showing highly subunit-dependent potency and maximal response. In light of the interest in partial GABA(A) receptor agonists as potential therapeutics, structure-activity studies of a number of analogs of 4-PIOL, a low-efficacy partial GABA(A) agonist derived from THIP, have been performed. In this connection, a series of GABA(A) ligands has been developed that exhibit pharmacological profiles from moderately potent low-efficacy partial GABA(A) agonist activity to potent and selective antagonist effects. Very little information is available on direct-acting GABA(A) receptor agonists in clinical studies. However, the results of clinical studies on the effect of the partial GABA(A) agonist THIP on human sleep patterns show that the functional consequences of a direct-acting agonist are different from those seen after the administration of GABA(A) receptor modulators, such as benzodiazepines and barbiturates.     

One-pot approach for the synthesis of trans-cyclopropyl compounds from aldehydes. Application to the synthesis of GPR40 receptor agonists

A novel multicatalytic one-pot process providing trans-cyclopropyl compounds from corresponding aldehydes has been developed and applied to the synthesis of GPR40 small molecule agonists.     

A reactivity pattern for discrimination of ER agonism and antagonism based on 3-D molecular attributes

Various models have been developed to predict the relative binding affinity (RBA) of chemicals to estrogen receptors (ER). These models can be used to prioritize chemicals for further tiered biological testing to assess the potential for endocrine disruption. One shortcoming of models predicting RBA has been the inability to distinguish potential receptor antagonism from agonism, and hence in vivo response. It has been suggested that steroid receptor antagonists are less compact than agonists; thus, ER binding of antagonists may prohibit proper alignment of receptor protein helices preventing subsequent transactivation. The current study tests the theory of chemical bulk as a defining parameter of antagonism by employing a 3-D structural approach for development of reactivity patterns for ER antagonists and agonists. Using a dataset of 23 potent ER ligands (16 agonists, 7 antagonists), molecular parameters previously found to be associated with ER binding affinity, namely global (E(HOMO)) and local (donor delocalizabilities and charges) electron donating ability of electronegative sites and steric distances between those sites, were found insufficient to discriminate ER antagonists from agonists. However, parameters related to molecular bulk, including solvent accessible surface and negatively charged Van der Waal's surface, provided reactivity patterns that were 100% successful in discriminating antagonists from agonists in the limited data set tested. The model also shows potential to discriminate pure antagonists from partial agonist/antagonist structures. Using this exploratory model it is possible to predict additional chemicals for their ability to bind but inactivate the ER, providing a further tool for hypothesis testing to elucidate chemical structural characteristics associated with estrogenicity and anti-estrogenicity.     

Enrichment of ligands for the serotonin receptor using the Shape Signatures approach

Shape Signatures, a new 3-dimensional molecular comparison method, has been adapted to rank ligands of the serotonin receptors. A set of 825 agonists and 400 antagonists together with approximately 10,000 randomly chosen compounds from the NCI database were used in this study. Both 1D and 2D Shape Signature databases were created, and enrichment studies were carried out. Results from these studies reveal that the 1D Shape Signature approach is highly efficient in separating agonists from a mixture of molecules which includes compounds randomly selected from the NCI database taken as inactives. It is also equally effective at separating agonists and antagonists from a pool of active ligands for the serotonin receptor. Parallel enrichment studies using 2D shape signatures showed high selectivity with more restricted coverage due to the high specificity of 2D signatures. The influence of conformational variation of the shape signature on enrichment was explored by docking a subset of ligands into the crystal structure of serotonin N-acetyltransferase. Enrichment studies on the resulting "docked" conformations produced only slightly improved results compared with the CORINA-generated conformations.     

GPR40 受体苯丙酸类激动剂三维定量构效关系研究

苯丙酸类化合物是G蛋白偶联受体40(GPR40)潜在的生物活性药物。本文基于比较分子力场分析法(Co MFA)和比较分子相似性指数分析法(CoMSIA),分别建立了40个已知活性的GPR40受体苯丙酸类激动剂的三维定量构效关系(3D-QSAR)模型,研究该类激动剂与生物活性之间的关系。CoMFA和CoMSIA模型的交叉验证系数(q~2)分别为0. 527和0. 500,拟合验证系数(r~2)分别为0. 901和0. 860,两个3D-QSAR模型预测值与实验值基本一致,表明模型具有良好的可信度和预测能力。根据两个3D-QSAR模型提供的立体场、静电场、疏水场、氢键供体场和氢键受体场所提供的信息提出优化该类抑制剂结构的药物设计思路,为指导设计更高活性的GPR40激动剂以及GRR40新分子激动活性的预测提供理论依据。     

Activity‐Directed Synthesis with Intermolecular Reactions: Development of a Fragment into a Range of Androgen Receptor Agonists

Activity‐directed synthesis (ADS), a novel discovery approach in which bioactive molecules emerge in parallel with associated syntheses, was exploited to develop a weakly binding fragment into novel androgen receptor agonists. Harnessing promiscuous intermolecular reactions of carbenoid compounds enabled highly efficient exploration of chemical space. Four substrates were prepared, yet exploited in 326 reactions to explore diverse chemical space; guided by bioactivity alone, the products of just nine of the reactions were purified to reveal diverse novel agonists with up to 125‐fold improved activity. Remarkably, one agonist stemmed from a novel enantioselective transformation; this is the first time that an asymmetric reaction has been discovered solely on the basis of the biological activity of the product. It was shown that ADS is a significant addition to the lead generation toolkit, enabling the efficient and rapid discovery of novel, yet synthetically accessible, bioactive chemotypes.     

The discovery of novel auxin transport inhibitors by molecular modeling and three-dimensional pattern analysis

Summary Molecular modeling techniques and three-dimensional (3D) pattern analysis have been used to investigate the chemical and steric properties of compounds that inhibit transport of the plant hormone auxin. These compounds bind to a specific site on the plant plasma membrane characterized by its affinity for the herbicide N-1-naphthylphthalamic acid (NPA). A 3D model was derived from critical features of a set of ligands for the NPA receptor, a suggested binding conformation is proposed, and implications for the topographical features of the NPA receptor are discussed. This model, along with 3D structural analysis techniques, was then used to search the Abbott corporate database of chemical structures. Of the 467 compounds that satisfied the criteria of the model, 77 representative molecules were evaluated for their ability to compete for the binding of [³H]NPA to corn microsomal membranes. Nineteen showed activity that ranged from 16 to 85% of the maximum NPA binding. Four of the most active of these, representing chemical classes not included in the original compound set, were also found to inhibit polar auxin transport through corn coleoptile sections. Thus, this study demonstrates that 3D analysis techniques can identify active, novel ligands for biochemical target sites with concomitant physiological activity.     

Identification of a Novel Delta Opioid Receptor Agonist Chemotype with Potential Negative Allosteric Modulator Capabilities

The δ-opioid receptor (δOR) holds great potential as a therapeutic target. Yet, clinical drug development, which has focused on δOR agonists that mimic the potent and selective tool compound SNC80 have largely failed. It has increasingly become apparent that the SNC80 scaffold carries with it potent and efficacious β-arrestin recruitment. Here, we screened a relatively small (5120 molecules) physical drug library to identify δOR agonists that underrecruit β-arrestin, as it has been suggested that compounds that efficaciously recruit β-arrestin are proconvulsant. The screen identified a hit compound and further characterization using cellular binding and signaling assays revealed that this molecule (R995045, compound 1) exhibited ten-fold selectivity over µ- and κ-opioid receptors. Compound 1 represents a novel chemotype at the δOR. A subsequent characterization of fourteen analogs of compound 1, however did not identify a more potent δOR agonist. Computational modeling and in vitro characterization of compound 1 in the presence of the endogenous agonist leu-enkephalin suggest compound 1 may also bind allosterically and negatively modulate the potency of Leu-enkephalin to inhibit cAMP, acting as a ‘NAM-agonist’ in this assay. The potential physiological utility of such a class of compounds will need to be assessed in future in vivo assays.     

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.