Inhibitory Kinetics of Cyanidin-3-O-glucoside against α-Amylase and α-Glucosidase

The inhibitory mechanism of α-amylase and α-glucosidase by cyanidin-3-O-glucoside was investigated by ultrafiltration, high performance liquid chromatography (HPLC), enzyme kinetics, and molecular docking. The results indicated that cyanidin-3-O-glucoside inhibited α-amylase and α-glucosidase in a reversible and non-competitive manner. Besides, the fluorescence quenching analysis indicated that cyanidin-3-O-glucoside combined with the two enzymes by hydrogen bonds to form a complex. Molecular docking analysis showed that cyanidin-3-O-glucoside interacted with the key amino acid residues of α-amylase and α-glucosidase through hydrogen bonds and hydrophobic forces, and the binding energies were −7.8 and −9.8 kcal/mol, respectively. Our research suggests that cyanidin-3-O-glucoside has the potential to be used as an inhibitor of α-amylase and α-glucosidase in the development of functional foods

Tumor Endothelial Marker 8 Amplifies Canonical Wnt Signaling in Blood Vessels

Tumor Endothelial Marker 8/Anthrax Toxin Receptor 1 (TEM8/ANTXR1) expression is induced in the vascular compartment of multiple tumors and therefore, is a candidate molecule to target tumor therapies. This cell surface molecule mediates anthrax toxin internalization, however, its physiological function in blood vessels remains largely unknown. We identified the chicken chorioallantoic membrane (CAM) as a model system to study the endogenous function of TEM8 in blood vessels as we found that TEM8 expression was induced transiently between day 10 and 12 of embryonic development, when the vascular tree is undergoing final development and growth. We used the cell-binding component of anthrax toxin, Protective Antigen (PA), to engage endogenous TEM8 receptors and evaluate the effects of PA-TEM8 complexes on vascular development. PA applied at the time of highest TEM8 expression reduced vascular density and disrupted hierarchical branching as revealed by quantitative morphometric analysis of the vascular tree after 48h. PA-dependent reduced branching phenotype was partially mimicked by Wnt3a application and ameliorated by the Wnt antagonist, Dikkopf-1. These results implicate TEM8 expression in endothelial cells in regulating the canonical Wnt signaling pathway at this day of CAM development. Consistent with this model, PA increased beta catenin levels acutely in CAM blood vessels in vivo and in TEM8 transfected primary human endothelial cells in vitro. TEM8 expression in Hek293 cells, which neither express endogenous PA-binding receptors nor Wnt ligands, stabilized beta catenin levels and amplified beta catenin-dependent transcriptional activity induced by Wnt3a. This agonistic function is supported by findings in the CAM, where the increase in TEM8 expression from day 10 to day 12 and PA application correlated with Axin 2 induction, a universal reporter gene for canonical Wnt signaling. We postulate that the developmentally controlled expression of TEM8 modulates endothelial cell response to canonical Wnt signaling to regulate vessel patterning and density

Computational QSAR model combined molecular descriptors and fingerprints to predict HDAC1 inhibitors

The dynamic balance between acetylation and deacetylation of histones plays a crucial role in the epigenetic regulation of gene expression. It is equilibrated by two families of enzymes: histone acetyltransferases and histone deacetylases (HDACs). HDACs repress transcription by regulating the conformation of the higher-order chromatin structure. HDAC inhibitors have recently become a class of chemical agents for potential treatment of the abnormal chromatin remodeling process involved in certain cancers. In this study, we constructed a large dataset to predict the activity value of HDAC1 inhibitors. Each compound was represented with seven fingerprints, and computational models were subsequently developed to predict HDAC1 inhibitors via five machine learning methods. These methods include naïve Bayes, κ-nearest neighbor, C4.5 decision tree, random forest, and support vector machine (SVM) algorithms. The best predicting model was CDK fingerprint with SVM, which exhibited an accuracy of 0.89. This model also performed best in five-fold cross-validation. Some representative substructure alerts responsible for HDAC1 inhibitors were identified by using MoSS in KNIME, which could facilitate the identification of HDAC1 inhibitors

Sur la situation en Chine

Gauthier Ursula, Wei 魏 Jingsheng 京生. Sur la situation en Chine . In: Raison présente, n°135, 3e trimestre 2000. Économie et démocratie. pp. 99-112