Evolution of physicochemical properties of melanin concentrating hormone receptor 1 (MCHr1) antagonists

Multifaceted actions of melanin-concentrating hormone on mammalian energy homeostasis

Melanin-concentrating hormone (MCH) is a small cyclic peptide expressed in all mammals, mainly in the hypothalamus. MCH acts as a robust integrator of several physiological functions and has crucial roles in the regulation of sleep-wake rhythms, feeding behaviour and metabolism. MCH signalling has a very broad endocrine context and is involved in physiological functions and emotional states associated with metabolism, such as reproduction, anxiety, depression, sleep and circadian rhythms. MCH mediates its functions through two receptors (MCHR1 and MCHR2), of which only MCHR1 is common to all mammals. Owing to the wide variety of MCH downstream signalling pathways, MCHR1 agonists and antagonists have great potential as tools for the directed management of energy balance disorders and associated metabolic complications, and translational strategies using these compounds hold promise for the development of novel treatments for obesity. This Review provides an overview of the numerous roles of MCH in energy and glucose homeostasis, as well as in regulation of the mesolimbic dopaminergic circuits that encode the hedonic component of food intake.

Identification of novel GPCR partners of the central melanocortin signaling

OBJECTIVE

Homo- or heterodimerization of G protein-coupled receptors (GPCRs) generally affects the normal functioning of these receptors and mediates the responses to a variety of physiological stimuli in vivo. It is well known that melanocortin-3 receptor (MC3R) and melanocortin-4 receptor (MC4R) are key regulators of appetite and energy homeostasis in the central nervous system. However, the GPCR partners of MC3R and MC4R are not well understood. Our objective is to analyze single cell RNA-seq datasets of the hypothalamus to explore and identify novel GPCR partners of MC3R and MC4R and examine the pharmacological effect on the downstream signal transduction and membrane translocation of melanocortin receptors.

METHODS

We conducted an integrative analysis of multiple single cell RNA-seq datasets to reveal the expression pattern and correlation of GPCR families in the mouse hypothalamus. The emerging GPCRs with important metabolic functions were selected for cloning and co-immunoprecipitation validation. The positive GPCR partners were then tested for the pharmacological activation, competitive binding assay and surface translocation ELISA experiments.

RESULTS

Based on the expression pattern of GPCRs and their function enrichment results, we narrowed down the range of potential GPCR interaction with MC3R and MC4R for further confirmation. Co-immunoprecipitation assay verified 23 and 32 novel GPCR partners that interacted with MC3R and MC4R in vitro. The presence of these GPCR partners exhibited different effects in the physiological regulation and signal transduction of MC3R and MC4R.

CONCLUSIONS

This work represented the first large-scale screen for the functional GPCR complex of central melanocortin receptors and defined a composite metabolic regulatory GPCR network of the hypothalamic nucleuses.

Identification of a new small molecule chemotype of Melanin Concentrating Hormone Receptor-1 antagonists using pharmacophore-based virtual screening

MCH receptor is a G protein-coupled receptor with two subtypes R1 and R2. Many studies have demonstrated the role of MCH-R1 in feeding and energy homeostasis. It has been proven that oral administration of small molecule MCH-R1 antagonists significantly reduces food intake and causes a dose-dependent weight loss. In this study, two ligand-based pharmacophores were developed and validated based on recently published MCH-R1 antagonists with diverse structures. Successful pharmacophores had one hydrogen bond acceptor, one positive ionizable, one ring aromatic and two or three hydrophobic groups. These 3D-QSAR models were used for virtual screening of the ZINC chemical database resulting in the identification of nine compounds with more than 50% displacement of radiolabeled MCH at a 20 μM concentration. Moreover, four of these compounds showed antagonistic activities in Aequorin functional assay, including MH-3 which is the first MCH-R1 antagonist based on a diazaspiro[4.5]decane scaffold. The most active compounds were also docked into our previously published MCH-R1 homology model to gain insights into their binding determinants. These compounds could represent a viable starting scaffold for the design of potent MCH-R1 antagonists with improved pharmacokinetic properties as an effective treatment for obesity.

CNS-targeting pharmacological interventions for the metabolic syndrome

The metabolic syndrome (MetS) encompasses medical conditions such as obesity, hyperglycemia, high blood pressure, and dyslipidemia that are major drivers for the ever-increasing prevalence of type 2 diabetes, cardiovascular diseases, and certain types of cancer. At the core of clinical strategies against the MetS is weight loss, induced by bariatric surgery, lifestyle changes based on calorie reduction and exercise, or pharmacology. This Review summarizes the past, current, and future efforts of targeting the MetS by pharmacological agents. Major emphasis is given to drugs that target the CNS as a key denominator for obesity and its comorbid sequelae.

Translational Modeling to Guide Study Design and Dose Choice in Obesity Exemplified by AZD1979, a Melanin-concentrating Hormone Receptor 1 Antagonist

In this study, we present the translational modeling used in the discovery of AZD1979, a melanin‐concentrating hormone receptor 1 (MCHr1) antagonist aimed for treatment of obesity. The model quantitatively connects the relevant biomarkers and thereby closes the scaling path from rodent to man, as well as from dose to effect level. The complexity of individual modeling steps depends on the quality and quantity of data as well as the prior information; from semimechanistic body‐composition models to standard linear regression. Key predictions are obtained by standard forward simulation (e.g., predicting effect from exposure), as well as non‐parametric input estimation (e.g., predicting energy intake from longitudinal body‐weight data), across species. The work illustrates how modeling integrates data from several species, fills critical gaps between biomarkers, and supports experimental design and human dose‐prediction. We believe this approach can be of general interest for translation in the obesity field, and might inspire translational reasoning more broadly.