Similarity- and Substructure-Based Development of β2-Adrenergic Receptor Ligands Based on Unusual Scaffolds

In silico identification of a biarylamine acting as agonist at human β3 adrenoceptors and exerting BRL37344-like effects on mouse metabolism

Human β3-adrenoceptor (β3AR) agonists were considered potential agents for the treatment of metabolic disorders. However, compounds tested as β3AR ligands have shown marked differences in pharmacological profile in rodent and human species, although these compounds remain attractive as they were successfully repurposed for the therapy of urinary incontinence. In this work, some biarylamine compounds were designed and tested in silico as potential β3AR agonists on 3-D models of mouse or human β3ARs. Based on the theoretical results, we identified, synthesized and tested a biarylamine compound (polibegron). In CHO-K1 cells expressing the human β3AR, polibegron and the β3AR agonist BRL 37344 were partial agonists for stimulating cAMP accumulation (50 and 57% of the response to isoproterenol, respectively). The potency of polibegron was 1.71- and 4.5-fold higher than that of isoproterenol and BRL37344, respectively. These results indicate that polibegron acts as a potent, but partial, agonist at human β3ARs. In C57BL/6N mice with obesity induced by a high-fat diet, similar effects of the equimolar intraperitoneal administration of polibegron and BRL37344 were observed on weight, visceral fat and plasma levels of glucose, cholesterol and triglycerides. Similarities and differences between species related to ligand-receptor interactions can be useful for drug designing.

Rational design, synthesis, and pharmacological evaluation of a cohort of novel beta-adrenergic receptors ligands enables an assessment of structure-activity relationships

Biomedical applications of molecules that are able to modulate β-adrenergic signaling have become increasingly attractive over the last decade, revealing that β-adrenergic receptors (β-ARs) are key targets for a plethora of therapeutic interventions, including cancer. Despite successes in β-AR drug discovery, identification of β-AR ligands that are useful as selective chemical tools in pharmacological studies of the three β-AR subtypes, or lead compounds for drug development is still a highly challenging task. This is mainly due to the intrinsic plasticity of β-ARs as G protein-coupled receptors in conjunction with the requirement for functional receptor subtype selectivity, tissue specificity and minimal off-target effects. With the aim to provide insight into structure-activity relationships for the three β-AR subtypes, we have synthesized and obtained the pharmacological profile of a series of structurally diverse compounds (named MC) that were designed based on the aryloxy-propanolamine scaffold of SR59230A. Comparative analysis of their predicted binding mode within the active and inactive states of the receptors in combination with their pharmacological profile revealed key structural elements that control their activity as agonists or antagonists, in addition to clues about substituents that mediate selectivity for one receptor subtype over the others. We anticipate that these results will facilitate selective β-AR drug development efforts.

Structure-Based Virtual Screening for Ligands of G Protein-Coupled Receptors: What Can Molecular Docking Do for You?

G protein-coupled receptors (GPCRs) constitute the largest family of membrane proteins in the human genome and are important therapeutic targets. During the last decade, the number of atomic-resolution structures of GPCRs has increased rapidly, providing insights into drug binding at the molecular level. These breakthroughs have created excitement regarding the potential of using structural information in ligand design and initiated a new era of rational drug discovery for GPCRs. The molecular docking method is now widely applied to model the three-dimensional structures of GPCR-ligand complexes and screen for chemical probes in large compound libraries. In this review article, we first summarize the current structural coverage of the GPCR superfamily and the understanding of receptor-ligand interactions at atomic resolution. We then present the general workflow of structure-based virtual screening and strategies to discover GPCR ligands in chemical libraries. We assess the state of the art of this research field by summarizing prospective applications of virtual screening based on experimental structures. Strategies to identify compounds with specific efficacy and selectivity profiles are discussed, illustrating the opportunities and limitations of the molecular docking method. Our overview shows that structure-based virtual screening can discover novel leads and will be essential in pursuing the next generation of GPCR drugs. SIGNIFICANCE STATEMENT: Extraordinary advances in the structural biology of G protein-coupled receptors have revealed the molecular details of ligand recognition by this large family of therapeutic targets, providing novel avenues for rational drug design. Structure-based docking is an efficient computational approach to identify novel chemical probes from large compound libraries, which has the potential to accelerate the development of drug candidates.

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 β 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 β 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.

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 β₂-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 β₂-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.

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.