Khanal, Shalil

BET bromodomain inhibitors are efficacious as anti-inflammatory compounds, but clinical translation is hampered by dose-limiting toxicities from non-selective inhibition. We herein report compounds 16 and 26, based on previously reported 4-methyl-1,2,3-triazole-based inhibitor, DW34. 16 has a BRD4 BD1 Ki of 10 nM, and up to 13–38-fold selectivity for BRD4 BD1 over other BD2 domains, and an improved hERG affinity of 4.24 µM over DW34. 26, A biscyclopropyl analog of 16 showed further enhancement of BD1 selectivity over BD2 (26–203-fold), but exhibited more potent hERG inhibition. Compound 16 had improved liver and plasma clearance over DW34, with good biodistribution to the liver, and had an intracellular target-engagement affinity Ki of 92 nM, with reduction of Ccl2, Cxcl1, AST, and ALT in in vitro and in vivo mouse models of liver inflammation. 16 represents a useful lead for treating inflammatory liver diseases, with improved specificity, drug-like properties, and reduced hERG affinity.

Background and Aims: Liver fibrosis and cirrhosis are major global health burdens with limited treatments. Activated HSCs drive fibrosis through increased proliferation, migration, collagen deposition and glycolysis. The aim of this study is to elucidate the signaling events that lead to enhanced glycolysis, subsequent HSC activation, and liver fibrosis. Approach and Results: Utilizing a phospho-kinase array, we identified with no lysine kinase 1 (WNK1) as a new kinase in primary human HSCs activated by the profibrotic PDGF-B. PDGF-mediated glycolysis in HSCs was attenuated by the WNK1 selective inhibitor, WNK-IN-11, as measured by live-cell metabolic assay, Glifon-300 fluorescence, Glucose-Glo assay, and glucose transporter 1 immunofluorescence. To understand how WNK1 promotes glycolysis, we employed chemical genetics where an engineered WNK1 carrying threonine 301 to glycine mutation (WNK1 T301G ) mutant with a modified ATP pocket accommodated a specific ATP-γ-S analogue to thio-phosphorylate its substrates. Thio-phosphorylated proteins were analyzed by mass spectrometry, which identified the glycolytic protein, triosephosphate isomerase 1 (TPI1), as a novel WNK1 direct substrate. TPI1 interacted with WNK1 in condensates, membrane-less phase separation structures. Condensate disruption and knockdown of TPI1 or WNK1 reduced HSC proliferation and migration in vitro. In vivo, pharmacological or genetic WNK1 inhibition significantly attenuated liver fibrosis in carbon tetrachloride and high-fat, choline-deficient, L -amino acid diet mouse models. Finally, WNK1 inhibition reduced fibrogenesis ex vivo in human precision-cut liver slices. Conclusions: These findings identify WNK1 as a previously unrecognized kinase that promotes HSC activation and liver fibrosis via TPI1-mediated glycolysis, highlighting the WNK1-TPI1 axis as a potential therapeutic target.

BET bromodomain inhibitors demonstrate significant promise as anti-inflammatory agents targeting a variety of inflammatory disorders. However, clinical data has demonstrated that the administration of non-selective BET bromodomain inhibitors has led to significant dose-limiting toxicity in clinical settings. More selective inhibitors of the second BET bromodomains, referred to as pan-D2 inhibitors, are better tolerated, however their efficacy varies significantly depending on disease indication. Here, we use three orally bioavailable inhibitors, 1–3, that are either selective for the first N-terminal bromodomain of BRD4 (BRD4-D1 selective), or pan-D1 biased, for assessing their cellular and in vivo efficacy and safety profile in two models of inflammatory liver disease. We compare their effects to known pan-D2 and pan-BET inhibitors. Our results show that pan-D1 biased inhibitor, 3, is as efficacious as the pan-BET inhibitor I-BET151 in reducing inflammation from LPS-induced and drug-induced toxicity, whereas pan-D2 inhibitors are less effective. BRD4-D1 selective inhibitors, 1 and 2, are also efficacious; however, new inhibitors with improved cellular target engagement will be necessary to more thoroughly assess their effects. Finally, BRD4-D1 selective inhibitors are better tolerated in a preclinical model of thrombocytopenia than pan-D1 biased inhibitors, while gastrointestinal (GI) toxicity may be a BRD4-driven effect. These results highlight the importance of assessing specific BET protein and bromodomain functions due to their varying roles in diverse disease models.

Liver fibrosis is characterized by the activation of perivascular hepatic stellate cells (HSCs), the release of fibrogenic nanosized extracellular vesicles (EVs), and increased HSC glycolysis. Nevertheless, how glycolysis in HSCs coordinates fibrosis amplification through tissue zone-specific pathways remains elusive. Here, we demonstrate that HSC-specific genetic inhibition of glycolysis reduced liver fibrosis. Moreover, spatial transcriptomics revealed a fibrosis-mediated up-regulation of EV-related pathways in the liver pericentral zone, which was abrogated by glycolysis genetic inhibition. Mechanistically, glycolysis in HSCs up-regulated the expression of EV-related genes such as Ras-related protein Rab-31 ( RAB31 ) by enhancing histone 3 lysine 9 acetylation on the promoter region, which increased EV release. Functionally, these glycolysis-dependent EVs increased fibrotic gene expression in recipient HSC. Furthermore, EVs derived from glycolysis-deficient mice abrogated liver fibrosis amplification in contrast to glycolysis-competent mouse EVs. In summary, glycolysis in HSCs amplifies liver fibrosis by promoting fibrogenic EV release in the hepatic pericentral zone, which represents a potential therapeutic target.

The search for non-invasive, fast, and low-cost diagnostic tools has gained significant traction among many researchers worldwide. Dielectric properties calculated from microwave signals offer unique insights into biological tissue. Material properties, such as relative permittivity (εr) and conductivity (σ), can vary significantly between healthy and unhealthy tissue types at a given frequency. Understanding this difference in properties is key for identifying the disease state. The frequency-dependent nature of the dielectric measurements results in large datasets, which can be postprocessed using artificial intelligence (AI) methods. In this work, the dielectric properties of liver tissues in three mouse models of liver disease are characterized using dielectric spectroscopy. The measurements are grouped into four categories based on the diets or disease state of the mice, i.e., healthy mice, mice with non-alcoholic steatohepatitis (NASH) induced by choline-deficient high-fat diet, mice with NASH induced by western diet, and mice with liver fibrosis. Multi-class classification machine learning (ML) models are then explored to differentiate the liver tissue groups based on dielectric measurements. The results show that the support vector machine (SVM) model was able to differentiate the tissue groups with an accuracy up to 90%. This technology pipeline, thus, shows great potential for developing the next generation non-invasive diagnostic tools.