Chemogenomic Screening in a Patient-Derived 3D Fatty Liver Disease Model Reveals the CHRM1-TRPM8 Axis as a Novel Module for Targeted Intervention.

Metabolic dysfunction-associated steatohepatitis (MASH) is a leading cause of chronic liver disease with few therapeutic options. To narrow the translational gap in the development of pharmacological MASH treatments, a 3D liver model from primary human hepatocytes and non-parenchymal cells derived from patients with histologically confirmed MASH was established. The model closely mirrors disease-relevant endpoints, such as steatosis, inflammation and fibrosis, and multi-omics analyses show excellent alignment with biopsy data from 306 MASH patients and 77 controls.

The novel adrenergic agonist ATR-127 targets skeletal muscle and brown adipose tissue to tackle diabesity and steatohepatitis.

Objective: Simultaneous activation of β2- and β3-adrenoceptors (ARs) improves whole-body metabolism via beneficial effects in skeletal muscle and brown adipose tissue (BAT). Nevertheless, high-efficacy agonists simultaneously targeting these receptors whilst limiting activation of β1-ARs - and thus inducing cardiovascular complications - are currently non-existent. Therefore, we here developed and evaluated the therapeutic potential of a novel β2-and β3-AR, named ATR-127, for the treatment of obesity and its associated metabolic perturbations in preclinical models.

GLP-1R signaling neighborhoods associate with the susceptibility to adverse drug reactions of incretin mimetics.

G protein-coupled receptors are important drug targets that engage and activate signaling transducers in multiple cellular compartments. Delineating therapeutic signaling from signaling associated with adverse events is an important step towards rational drug design. The glucagon-like peptide-1 receptor (GLP-1R) is a validated target for the treatment of diabetes and obesity, but drugs that target this receptor are a frequent cause of adverse events.

Mass Spectrometry of RNA-Binding Proteins during Liquid-Liquid Phase Separation Reveals Distinct Assembly Mechanisms and Droplet Architectures.

Liquid-liquid phase separation (LLPS) of heterogeneous ribonucleoproteins (hnRNPs) drives the formation of membraneless organelles, but structural information about their assembled states is still lacking. Here, we address this challenge through a combination of protein engineering, native ion mobility mass spectrometry, and molecular dynamics simulations. We used an LLPS-compatible spider silk domain and pH changes to control the self-assembly of the hnRNPs FUS, TDP-43, and hCPEB3, which are implicated in neurodegeneration, cancer, and memory storage.