Antifungal action of three (Z)-5-amino-N'-aryl-1-methyl-1H-imidazole-4-carbohydrazonamides

[Excerpt] The incidence of fungal infections has greatly increased in patients under sustained immunosuppression with considerable risk associated. Difficulties regarding prompt diagnosis and the limited therapeutic options dictate high mortality rates. Available antifungals display substantial toxicity, a predictable consequence of the cellular structure of the organisms involved, reduced spectrum of activity, and drug interactions. Our group had previously identified three (Z)-5-amino-N'-aryl-1-methyl-1H-imidazole-4-carbohydrazonamides 1 [aryl= phenyl (1a), 4-fluorophenyl (1b), 3fluorophenyl (1c)] as potent antifungal agents.1 (...)

Metabolic profiling and classification of propolis samples from Southern Brazil: an NMR-based platform coupled with machine learning

The chemical composition of propolis is affected by environmental factors and harvest season, making it difficult to standardize its extracts for medicinal usage. By detecting a typical chemical profile associated with propolis from a specific production region or season, certain types of propolis may be used to obtain a specific pharmacological activity. In this study, propolis from three agroecological regions (plain, plateau, and highlands) from southern Brazil, collected over the four seasons of 2010, were investigated through a novel NMR-based metabolomics data analysis workflow. Chemometrics and machine learning algorithms (PLS-DA and RF), including methods to estimate variable importance in classification, were used in this study. The machine learning and feature selection methods permitted construction of models for propolis sample classification with high accuracy (>75%, reaching 90% in the best case), better discriminating samples regarding their collection seasons comparatively to the harvest regions. PLS-DA and RF allowed the identification of biomarkers for sample discrimination, expanding the set of discriminating features and adding relevant information for the identification of the class-determining metabolites. The NMR-based metabolomics analytical platform, coupled to bioinformatic tools, allowed characterization and classification of Brazilian propolis samples regarding the metabolite signature of important compounds, i.e., chemical fingerprint, harvest seasons, and production regions.

Synthesis, antiangiogenesis evaluation and molecular docking studies of 1-Aryl-3-[(thieno[3,2-b]pyridin-7-ylthio)phenyl]ureas: Discovery of a new substitution pattern for type II VEGFR-2 Tyr kinase inhibitors

The synthesis and biological evaluation of novel 1-aryl-3-[2-, 3- or 4-(thieno[3,2-b]pyridin-7-ylthio)phenyl]ureas 3, 4 and 5 as VEGFR-2 tyrosine kinase inhibitors, are reported. The 1-aryl-3-[3-(thieno[3,2-b]pyridin-7-ylthio)phenyl]ureas 4a-4h, with the arylurea in the meta position to the thioether, showed the lowest IC50 values in enzymatic assays (10-206 nM), the most potent compounds 4d-4h (IC50 10-28 nM) bearing hydrophobic groups (Me, F, CF3 and Cl) in the terminal phenyl ring. A convincing rationalization was achieved for the highest potent compounds 4 as type II VEGFR-2 inhibitors, based on the simultaneous presence of: (1) the thioether linker and (2) the arylurea moiety in the meta position. For compounds 4, significant inhibition of Human Umbilical Vein Endothelial Cells (HUVECs) proliferation (BrdU assay), migration (wound-healing assay) and tube formation were observed at low concentrations. These compounds have also shown to increase apoptosis using the TUNEL assay. Immunostaining for total and phosphorylated (active) VEGFR-2 was performed by Western blotting. The phosphorylation of the receptor was significantly inhibited at 1.0 and 2.5 microM for the most promising compounds. Altogether, these findings point to an antiangiogenic effect in HUVECs.