Abstract Tiliroside is a glycosidic flavonoid present in many plants species including Helicteres velutina K. Schum (Malvaceae sensu lato), commonly known in Brazil as “pitó”. This molecule has been shown to have many biological activities, however no study has been carried out to investigate the toxicity of this substance. The present work aimed to evaluate the possible cellular toxicity in silico, in vitro and ex-vivo of the kaempferol-3-O-β-D-(6”-E-p-coumaroyl) glucopyranoside (tiliroside), through chemical structure analysis, toxicity assessment and predictive bioactive properties, using human samples for in vitro and ex-vivo tests. The in silico analysis suggests that tiliroside exhibited great absorption index when penetrating biological membranes. In addition, it also displayed considerable potential for cellular protection against free radicals, and anticarcinogenic, antioxidant, antineoplastic, anti-inflammatory, anti-hemorrhagic and antithrombotic activities. The assessment of the hemolytic and genotoxic effects of tiliroside showed low hemolysis rates in red blood cells and absence of cellular toxicity in the oral mucosa cells. The data obtained indicate that this molecule could be a promising therapeutic approach as a possible new drug with biotechnological potential.
Abstract In recent years, the development of high-throughput technologies for obtaining sequence data leveraged the possibility of analysis of protein data in silico. However, when it comes to viral polyprotein interaction studies, there is a gap in the representation of those proteins, given their size and length. The prepare for studies using state-of-the-art techniques such as Machine Learning, a good representation of such proteins is a must. We present an alternative to this problem, implementing a fragmentation and modeling protocol to prepare those polyproteins in the form of peptide fragments. Such procedure is made by several scripts, implemented together on the workflow we call PolyPRep, a tool written in Python script and available in GitHub. This software is freely available only for noncommercial users.
Abstract By applying the in-silico method, resveratrol was docked on those proteins which are responsible for bone loss. The Molecular docking data between the resveratrol and Receptor activator of nuclear factor-kappa-Β ligand [RANKL] receptors proved that resveratrol binds tightly to the receptors, showed the highest binding affinities of −6.9, −7.6, −7.1, −6.9, −6.7, and −7.1 kcal/mol. According to in-vitro data, Resveratrol reduced the osteoclasts after treating Marrow-Derived Macrophages [BMM] with Macrophage colony-stimulating factor [MCSF] 20ng / ml and RANKL 50ng / ml, with different concentrations of resveratrol (2.5, 10 μg / ml) For 7 days, the cells were treated with MCSF (20 ng / ml) and RANKL (40 ng / ml) together with concentrated trimethyl ether and resveratrol (2.5, 10 μg / ml) within 12 hours. Which, not affect cell survival. After fixing osteoclast cells with formaldehyde fixative on glass coverslip followed by incubation with 0.1% Triton X-100 in PBS for 5 min and after that stain with rhodamine phalloidin staining for actin and Hoechst for nuclei. Fluorescence microscopy was performed to see the distribution of filaments actin [F.actin]. Finally, resveratrol reduced the actin ring formation. Resveratrol is the best bioactive compound for drug preparation against bone loss.