AdipoRs- a potential therapeutic target for fibrotic disorders

Tectorigenin protects against cardiac fibrosis in diabetic mice heart via activating the adiponectin receptor 1-mediated AMPK pathway

Diabetic cardiomyopathy (DCM) is a common severe complication of diabetes that occurs independently of hypertension, coronary artery disease, and valvular cardiomyopathy, eventually leading to heart failure. Previous studies have reported that Tectorigenin (TEC) possesses extensive anti-inflammatory and anti-oxidative stress properties. In this present study, the impact of TEC on diabetic cardiomyopathy was examined. The model of DCM in mice was established with the combination of a high-fat diet and STZ treatment. Remarkably, TEC treatment significantly attenuated cardiac fibrosis and improved cardiac dysfunction. Concurrently, TEC was also found to mitigate hyperglycemia and hyperlipidemia in the DCM mouse. At the molecular level, TEC is involved in the activation of AMPK, both in vitro and in vivo, by enhancing its phosphorylation. This is achieved through the regulation of endothelial-mesenchymal transition via the AMPK/TGFβ/Smad3 pathway. Furthermore, it was demonstrated that the level of ubiquitination of the adiponectin receptor 1 (AdipoR1) protein is associated with TEC-mediated improvement of cardiac dysfunction in DCM mice. Notably the substantial reduction of myocardial fibrosis. In conclusion, TEC improves cardiac fibrosis in DCM mice by modulating the AdipoR1/AMPK signaling pathway. These findings suggest that TEC could be an effective therapeutic agent for the treatment of diabetic cardiomyopathy.

Discovery of Covalent Lead Compounds Targeting 3CL Protease with a Lateral Interactions Spiking Neural Network

Covalent drugs exhibit advantages in that noncovalent drugs cannot match, and covalent docking is an important method for screening covalent lead compounds. However, it is difficult for covalent docking to screen covalent compounds on a large scale because covalent docking requires determination of the covalent reaction type of the compound. Here, we propose to use deep learning of a lateral interactions spiking neural network to construct a covalent lead compound screening model to quickly screen covalent lead compounds. We used the 3CL protease (3CL Pro) of SARS-CoV-2 as the screen target and constructed two classification models based on LISNN to predict the covalent binding and inhibitory activity of compounds. The two classification models were trained on the covalent complex data set targeting cysteine (Cys) and the compound inhibitory activity data set targeting 3CL Pro, respected, with good prediction accuracy (ACC > 0.9). We then screened the screening compound library with 6 covalent binding screening models and 12 inhibitory activity screening models. We tested the inhibitory activity of the 32 compounds, and the best compound inhibited SARS-CoV-2 3CL Pro with an IC50 value of 369.5 nM. Further assay implied that dithiothreitol can affect the inhibitory activity of the compound to 3CL Pro, indicating that the compound may covalently bind 3CL Pro. The selectivity test showed that the compound had good target selectivity to 3CL Pro over cathepsin L. These correlation assays can prove the rationality of the covalent lead compound screening model. Finally, covalent docking was performed to demonstrate the binding conformation of the compound with 3CL Pro. The source code can be obtained from the GitHub repository (https://github.com/guzh970630/Screen_Covalent_Compound_by_LISNN).

GcForest-based compound-protein interaction prediction model and its application in discovering small-molecule drugs targeting CD47

Identifying compound-protein interaction plays a vital role in drug discovery. Artificial intelligence (AI), especially machine learning (ML) and deep learning (DL) algorithms, are playing increasingly important roles in compound-protein interaction (CPI) prediction. However, ML relies on learning from large sample data. And the CPI for specific target often has a small amount of data available. To overcome the dilemma, we propose a virtual screening model, in which word2vec is used as an embedding tool to generate low-dimensional vectors of SMILES of compounds and amino acid sequences of proteins, and the modified multi-grained cascade forest based gcForest is used as the classifier. This proposed method is capable of constructing a model from raw data, adjusting model complexity according to the scale of datasets, especially for small scale datasets, and is robust with few hyper-parameters and without over-fitting. We found that the proposed model is superior to other CPI prediction models and performs well on the constructed challenging dataset. We finally predicted 2 new inhibitors for clusters of differentiation 47(CD47) which has few known inhibitors. The IC50s of enzyme activities of these 2 new small molecular inhibitors targeting CD47-SIRPα interaction are 3.57 and 4.79 μM respectively. These results fully demonstrate the competence of this concise but efficient tool for CPI prediction.

Adiponectin alleviates the symptoms of ischemic renal disease by inhibiting renal cell apoptosis

AIMS

Ischemic renal disease (IRD) can cause kidney damage and eventually lead to end-stage renal disease. Adiponectin (APN), a recently discovered collagen-like protein secreted by adipose tissues, plays an important role in regulating energy metabolism and inflammation. This study aimed to explore the specific mechanism by which APN affects IRD.

MAIN METHODS

We cultured human renal tubular epithelial cells (HK-2) and created a mouse model of IRD to detect apoptosis-related indicators in vitro and in vivo.

KEY FINDINGS

Compared with those in the control group, the apoptosis rate and expression levels of Bax and Fas increased in the CoCl₂-induced hypoxia model group. However, the expression of Bcl-2 decreased, and after the combined treatment with APN, the phenomenon mentioned above was reversed. Moreover, studies have found that stanniocalcin-1 (STC-1) and uncoupling protein3 (UCP3) are also involved in the protective effect of APN. Additionally, we found that the glomeruli of the mice were significantly enlarged after the APN gene was knocked out; furthermore, the number of collagen fibers in the renal tubules, as well as the expression of the corresponding fibrogenic factors, increased significantly. More importantly, after the knockout of the APN gene, the expression of the hypoxia-inducible factors HIF-1α and HIF-1β and the apoptotic rate of renal tissue cells also increased.

SIGNIFICANCE

These results indicate that APN can alleviate the symptoms of IRD by inhibiting renal cell apoptosis. Thus, in the future, APN may be a new target for the treatment of IRD.

CHEMICAL COMPOUNDS

Cobalt chloride (PubChem CID: 24643).

Advances in understanding the role of adiponectin in renal fibrosis

Renal fibrosis is characterized by the proliferation of renal intrinsic cells, activation of renal interstitial fibroblasts and deposition of extracellular matrix (ECM), processes that lead to the progressive loss of renal function. Renal fibrosis is characterized by the proliferation of renal intrinsic cells, activation of renal interstitial fibroblasts, and septal fibrosis is recognized as a marker for the progression of chronic kidney disease, a condition that is associated with high morbidity and mortality and is a significant public health burden. Despite extensive studies, there are no effective treatments for renal fibrosis. Adiponectin (APN) is a protein mainly produced by adipocytes that has anti-inflammatory and anti-atherosclerotic effects, improves insulin resistance and provides other salutary effects. Recent studies found that APN can inhibit ECM deposition by inhibiting inflammation and oxidative stress, and by regulating the TGF-β, AMPK, MCP-1 and other signalling pathways. Many recent studies have examined the roles of these pathways in the pathogenesis of renal fibrosis. In this article, we review the pathogenic mechanism of APN in renal fibrosis and provide a theoretical basis for delaying and blocking renal fibrosis by alteration of APN activity.

AMPK: a balancer of the renin-angiotensin system

The renin-angiotensin system (RAS) is undisputedly well-studied as one of the oldest and most critical regulators for arterial blood pressure, fluid volume, as well as renal function. In recent studies, RAS has also been implicated in the development of obesity, diabetes, hyperlipidemia, and other diseases, and also involved in the regulation of several signaling pathways such as proliferation, apoptosis and autophagy, and insulin resistance. AMP-activated protein kinase (AMPK), an essential cellular energy sensor, has also been discovered to be involved in these diseases and cellular pathways. This would imply a connection between the RAS and AMPK. Therefore, this review serves to draw attention to the cross-talk between RAS and AMPK, then summering the most recent literature which highlights AMPK as a point of balance between physiological and pathological functions of the RAS.