Ligand-based virtual screening identifies a family of selective cannabinoid receptor 2 agonists

1-Benzylindoles as inhibitors of cytosolic phospholipase A2α: synthesis, biological activity, aqueous solubility, and cell permeability

Cytosolic phospholipase A2α (cPLA2α) is considered an interesting target for the development of new anti-inflammatory drugs, as it is significantly involved in the formation of pro-inflammatory lipid mediators. Recently, in a ligand-based virtual screening approach, 2,4-dichlorobenzyl-substituted 4-[2-(indol-3-ylmethylene)hydrazineyl]benzoic acid 7 was found to be an inhibitor of cPLA2α with micromolar activity. This compound has now been systematically varied to increase inhibitory potency. The studies performed led to 5-(1-benzylindol-3-ylmethyl)-2H-tetrazol-2-yl)pentanoic acid derivatives that exhibited submicromolar activity against the enzyme. The most potent compounds were also tested for their water solubility and for permeability in a Caco-2 model. Among other things, it was found that in Caco-2 cells, the pentanoic acid chain of the molecules can be metabolised to a considerable extent to propionic acid by β-oxidation.

Application of computational methods for class A GPCR Ligand discovery

G protein-coupled receptors (GPCR) are integral membrane proteins of considerable interest as targets for drug development due to their role in transmitting cellular signals in a multitude of biological processes. Of the six classes categorizing GPCR (A, B, C, D, E, and F), class A contains the largest number of therapeutically relevant GPCR. Despite their importance as drug targets, many challenges exist for the discovery of novel class A GPCR ligands serving as drug precursors. Though knowledge of the structural and functional characteristics of GPCR has grown significantly over the past 20 years, a large portion of GPCR lack reported, experimentally determined structures. Furthermore, many GPCR have no known endogenous and/or synthetic ligands, limiting further exploration of their biochemical, cellular, and physiological roles. While many successes in GPCR ligand discovery have resulted from experimental high-throughput screening, computational methods have played an increasingly important role in GPCR ligand identification in the past decade. Here we discuss computational techniques applied to GPCR ligand discovery. This review summarizes class A GPCR structure/function and provides an overview of many obstacles currently faced in GPCR ligand discovery. Furthermore, we discuss applications and recent successes of computational techniques used to predict GPCR structure as well as present a summary of ligand- and structure-based methods used to identify potential GPCR ligands. Finally, we discuss computational hit list generation and refinement and provide comprehensive workflows for GPCR ligand identification.

Rational drug design of CB2 receptor ligands: from 2012 to 2021

Cannabinoid receptors belong to the large family of G-protein-coupled receptors, which can be divided into two receptor types, cannabinoid receptor type-1 (CB1) and cannabinoid receptor type-2 (CB2). Marinol, Cesamet and Sativex are marketed CB1 drugs which are still in use and work well, but the central nervous system side effects caused by activation CB1, which limited the development of CB1 ligands. So far, no selective CB2 ligand has been approved for marketing, but lots of its ligands in the clinical stage and pre-clinical stage have positive effects on the treatment of some disease models and have great potential for development. Most selective CB2 agonists are designed and synthesized based on non-selective CB2 agonists through the classical med-chem strategies, e.g. molecular hybridization, scaffold hopping, bioisosterism, etc. During these processes, the balance between selectivity, activity, and pharmacokinetic properties needs to be achieved. Hence, we summarized some reported ligands on the basis of the optimization strategies in recent 10 years, and the limitations and future directions.

Investigating the Structure-Activity Relationship of 1,2,4-Triazine G-Protein-Coupled Receptor 84 (GPR84) Antagonists

G-protein-coupled receptor 84 (GPR84) is a proinflammatory orphan G-protein-coupled receptor implicated in several inflammatory and fibrotic diseases. Several agonist and antagonist ligands have been developed that target GPR84; however, a noncompetitive receptor blocker that was progressed to phase II clinical trials failed to demonstrate efficacy. New high-quality antagonists are required to investigate the pathophysiological role of GPR84 and to validate GPR84 as a therapeutic target. We previously reported the discovery of a novel triazine GPR84 competitive antagonist 1. Here, we describe an extensive structure–activity relationship (SAR) of antagonist 1 and also present in silico docking with supporting mutagenesis studies that reveals a potential binding pose for this type of orthosteric antagonist. Lead compound 42 is a potent GPR84 antagonist with a favorable pharmacokinetic (PK) profile suitable for further drug development.

N-Substituted 4-sulfamoylbenzoic acid derivatives as inhibitors of cytosolic phospholipase A2α

The N,N-disubstituted 4-sulfamoylbenzoic acid derivative 3, which was found to be an inhibitor of cytosolic phospholipase A2α (cPLA2α) with micromolar activity in a ligand-based virtual screening approach, was structurally modified to increase its enzyme inhibitory potency. Replacing the substituents on the sulfonamide nitrogen with other residues such as naphthyl, naphthylmethyl, indolylalkyl and differently substituted phenyl moieties did not lead to a significant increase in activity. Only strong structural convergence to the potent known benzhydrylindole-substituted benzoic acid derivatives that had served as templates in the virtual screening resulted in compounds with considerable potency. Thus, the sulfamoyl benzoic acid derivatives 85 and 88 showed submicromolar IC50 values against cPLA2α.

Targeting CB2 and TRPV1: Computational Approaches for the Identification of Dual Modulators

Both metabotropic (CBRs) and ionotropic cannabinoid receptors (ICRs) have implications in a range of neurological disorders. The metabotropic canonical CBRs CB1 and CB2 are highly implicated in these pathological events. However, selective targeting at CB2 versus CB1 offers optimized pharmacology due to the absence of psychoactive outcomes. The ICR transient receptor potential vanilloid type 1 (TRPV1) has also been reported to play a role in CNS disorders. Thus, activation of both targets, CB2 and TRPV1, offers a promising polypharmacological strategy for the treatment of neurological events including analgesia and neuroprotection. This brief research report aims to identify chemotypes with a potential dual CB2/TRPV1 profile. For this purpose, we have rationalized key structural features for activation and performed virtual screening at both targets using curated chemical libraries.

Pd-Catalyzed Direct C-H Activation for the C5-Olefination of Methyleneindolinones

The direct C-H activation without directing groups can realize the para-selectivity, which is a powerful and concise approach for functionalization of arenes. Utilizing the strategy, a C5-olefination of methyleneindolinones has been successfully developed by palladium-catalyzed direct C-H activation, which provides an expeditious access to 5-vinylindolin-2-ones with high regioselectivity. The protocol is distinguished by a mild reaction system avoiding ligand and high temperature. The kinetic isotope experiments indicate that the C-H bond cleavage is the rate-limiting step.

Further Studies on Triazinoindoles as Potential Novel Multitarget-Directed Anti-Alzheimer's Agents

The inadequate clinical efficacy of the present anti-Alzheimer's disease (AD) drugs and their low impact on the progression of Alzheimer's disease in patients have revised the research focus from single targets to multitarget-directed ligands. A novel series of substituted triazinoindole derivatives were obtained by introducing various substituents on the indole ring for the development of multitarget-directed ligands as anti-AD agents. The experimental data indicated that some of these compounds exhibited significant anti-AD properties. Among them, 8-(piperidin-1-yl)-N-(6-(pyrrolidin-1-yl)hexyl)-5H-[1,2,4]triazino[5,6-b]indol-3-amine (60), the most potent cholinesterase inhibitor (AChE, IC₅₀ value of 0.32 μM; BuChE, IC₅₀ value of 0.21 μM), was also found to possess significant self-mediated Aβ_1-42 aggregation inhibitory activity (54% at 25 μM concentration). Additionally, compound 60 showed strong antioxidant activity. In the PAMPA assay, compound 60 exhibited blood-brain barrier penetrating ability. An acute toxicity study in rats demonstrated no sign of toxicity at doses up to 2000 mg/kg. Furthermore, compound 60 significantly restored the cognitive deficits in the scopolamine-induced mice model and Aβ_1-42-induced rat model. In the in silico ADMET prediction studies, the compound satisfied all the parameters of CNS acting drugs. These results highlighted the potential of compound 60 to be a promising multitarget-directed ligand for the development of potential anti-AD drugs.

Fragment-Based Computational Method for Designing GPCR Ligands

G protein-coupled receptors (GPCRs) are the largest family of cell surface receptors, which is arguably the most important family of drug target. With the technology breakthroughs in X-ray crystallography and cryo-electron microscopy, more than 300 GPCR-ligand complex structures have been publicly reported since 2007, covering about 60 unique GPCRs. Such abundant structural information certainly will facilitate the structure-based drug design by targeting GPCRs. In this study, we have developed a fragment-based computational method for designing novel GPCR ligands. We first extracted the characteristic interaction patterns (CIPs) on the binding interfaces between GPCRs and their ligands. The CIPs were used as queries to search the chemical fragments derived from GPCR ligands, which were required to form similar interaction patterns with GPCR. Then, the selected chemical fragments were assembled into complete molecules by using the AutoT&T2 software. In this work, we chose β-adrenergic receptor (β-AR) and muscarinic acetylcholine receptor (mAChR) as the targets to validate this method. Based on the designs suggested by our method, samples of 63 compounds were purchased and tested in a cell-based functional assay. A total of 15 and 22 compounds were identified as active antagonists for β₂-AR and mAChR M1, respectively. Molecular dynamics simulations and binding free energy analysis were performed to explore the key interactions (e.g., hydrogen bonds and π-π interactions) between those active compounds and their target GPCRs. In summary, our work presents a useful approach to the de novo design of GPCR ligands based on the relevant 3D structural information.

Prediction of Orthosteric and Allosteric Regulations on Cannabinoid Receptors Using Supervised Machine Learning Classifiers

Designing highly selective compounds to protein subtypes and developing allosteric modulators targeting them are critical considerations to both drug discovery and mechanism studies for cannabinoid receptors. It is challenging but in demand to have classifiers to identify active ligands from inactive or random compounds and distinguish allosteric modulators from orthosteric ligands. In this study, supervised machine learning classifiers were built for two subtypes of cannabinoid receptors, CB1 and CB2. Three types of features, including molecular descriptors, MACCS fingerprints, and ECFP6 fingerprints, were calculated to evaluate the compound sets from diverse aspects. Deep neural networks, as well as conventional machine learning algorithms including support vector machine, naïve Bayes, logistic regression, and ensemble learning, were applied. Their performances on the classification with different types of features were compared and discussed. According to the receiver operating characteristic curves and the calculated metrics, the advantages and drawbacks of each algorithm were investigated. The feature ranking was followed to help extract useful knowledge about critical molecular properties, substructural keys, and circular fingerprints. The extracted features will then facilitate the research on cannabinoid receptors by providing guidance on preferred properties for compound modification and novel scaffold design. Besides using conventional molecular docking studies for compound virtual screening, machine-learning-based decision-making models provide alternative options. This study can be of value to the application of machine learning in the area of drug discovery and compound development.

Exploring G Protein-Coupled Receptors (GPCRs) Ligand Space via Cheminformatics Approaches: Impact on Rational Drug Design

The primary goal of rational drug discovery is the identification of selective ligands which act on single or multiple drug targets to achieve the desired clinical outcome through the exploration of total chemical space. To identify such desired compounds, computational approaches are necessary in predicting their drug-like properties. G Protein-Coupled Receptors (GPCRs) represent one of the largest and most important integral membrane protein families. These receptors serve as increasingly attractive drug targets due to their relevance in the treatment of various diseases, such as inflammatory disorders, metabolic imbalances, cardiac disorders, cancer, monogenic disorders, etc. In the last decade, multitudes of three-dimensional (3D) structures were solved for diverse GPCRs, thus referring to this period as the "golden age for GPCR structural biology." Moreover, accumulation of data about the chemical properties of GPCR ligands has garnered much interest toward the exploration of GPCR chemical space. Due to the steady increase in the structural, ligand, and functional data of GPCRs, several cheminformatics approaches have been implemented in its drug discovery pipeline. In this review, we mainly focus on the cheminformatics-based paradigms in GPCR drug discovery. We provide a comprehensive view on the ligand- and structure-based cheminformatics approaches which are best illustrated via GPCR case studies. Furthermore, an appropriate combination of ligand-based knowledge with structure-based ones, i.e., integrated approach, which is emerging as a promising strategy for cheminformatics-based GPCR drug design is also discussed.

Electron-catalyzed radical perfluoroalkylation of organic sulfides: the serendipitous use of the TMEDA/I2 complex as a radical initiator

The (TMEDA)I·I₃ complex as a new radical initiator for the perfluoroalkylation of RSH.

Augmentation of Creatine in the Heart

Creatine is a principle component of the creatine kinase (CK) phosphagen system common to all vertebrates. It is found in excitable cells, such as cardiomyocytes, where it plays an important role in the buffering and transport of chemical energy to ensure that supply meets the dynamic demands of the heart. Multiple components of the CK system, including intracellular creatine levels, are reduced in heart failure, while ischaemia and hypoxia represent acute crises of energy provision. Elevation of myocardial creatine levels has therefore been suggested as potentially beneficial, however, achieving this goal is not trivial. This mini-review outlines the evidence in support of creatine elevation and critically examines the pharmacological approaches that are currently available. In particular, dietary creatine-supplementation does not sufficiently elevate creatine levels in the heart due to subsequent down-regulation of the plasma membrane creatine transporter (CrT). Attempts to increase passive diffusion and bypass the CrT, e.g. via creatine esters, have yet to be tested in the heart. However, studies in mice with genetic overexpression of the CrT demonstrate proof-of-principle that elevated creatine protects the heart from ischaemia-reperfusion injury. This suggests activation of the CrT as a major unmet pharmacological target. However, translation of this finding to the clinic will require a greater understanding of CrT regulation in health and disease and the development of small molecule activators.

Cannabinoid receptor 2 (CB2) agonists and antagonists: a patent update

INTRODUCTION

Modulation of the CB2 receptor is an interesting approach for pain and inflammation, arthritis, addictions, neuroprotection, and cancer, among other possible therapeutic applications, and is devoid of central side effects.

AREAS COVERED

This review highlights the novel scaffolds for CB2 ligands and the diverse therapeutic applications for CB2 modulators disclosed in patents published since 2012.

EXPERT OPINION

Structural diversity of CB2 modulator scaffolds characterized the patent literature. Several CB2 agonists reached clinical Phase II for pain management and inflammation. Other therapeutic applications need to be explored such as neuroprotection and/or neurodegeneration.

Primary Macrophage Chemotaxis Induced by Cannabinoid Receptor 2 Agonists Occurs Independently of the CB2 Receptor

Activation of CB₂ has been demonstrated to induce directed immune cell migration. However, the ability of CB2 to act as a chemoattractant receptor in macrophages remains largely unexplored. Using a real-time chemotaxis assay and a panel of chemically diverse and widely used CB₂ agonists, we set out to examine whether CB₂ modulates primary murine macrophage chemotaxis. We report that of 12 agonists tested, only JWH133, HU308, L-759,656 and L-759,633 acted as macrophage chemoattractants. Surprisingly, neither pharmacological inhibition nor genetic ablation of CB₂ had any effect on CB₂ agonist-induced macrophage chemotaxis. As chemotaxis was pertussis toxin sensitive in both WT and CB₂^-/- macrophages, we concluded that a non-CB₁/CB₂, G_i/o-coupled GPCR must be responsible for CB₂ agonist-induced macrophage migration. The obvious candidate receptors GPR18 and GPR55 could not mediate JWH133 or HU308-induced cytoskeletal rearrangement or JWH133-induced β-arrestin recruitment in cells transfected with either receptor, demonstrating that neither are the unidentified GPCR. Taken together our results conclusively demonstrate that CB₂ is not a chemoattractant receptor for murine macrophages. Furthermore we show for the first time that JWH133, HU308, L-759,656 and L-759,633 have off-target effects of functional consequence in primary cells and we believe that our findings have wide ranging implications for the entire cannabinoid field.