Wound Healing and Anti-Inflammatory Effects of a Newly Developed Ointment Containing Jujube Leaves Extract.

Ziziphus jujuba Mill. (jujube) is a well-known medicinal plant with pronounced wound healing properties. The present study aimed to establish the chemical composition of the lyophilized ethanolic extract from Romanian Ziziphus jujuba leaves and to evaluate the healing and anti-inflammatory properties of a newly developed lipophilic ointment containing 10% dried jujube leaves extract. The ultra-High-Performance Liquid Chromatography Electrospray Ionization Tandem Mass Spectrometry method was used, and 47 compounds were detected, among them the novel epicatechin and caffeic acid. The extract contains significant amounts of rutin (29.836 mg/g), quercetin (15.180 mg/g) and chlorogenic acid (350.96 µg/g). The lipophilic ointment has a slightly tolerable pH, between 5.41-5.42, and proved to be non-toxic in acute dermal irritation tests on New Zealand albino rabbits and after repeated administration on Wistar rats. The ointment also has a healing activity comparable to Cicatrizin (a pharmaceutical marketed product) on Wistar rats and a moderate anti-inflammatory action compared to the control group, but statistically insignificant compared to indomethacin in the rat-induced inflammation test by intraplantar administration of kaolin. The healing and anti-inflammatory properties of the tested ointment are due to phenolic acids and flavonoids content, less because of minor components as apocynin, scopoletin, and isofraxidin.

Use of QSAR Global Models and Molecular Docking for Developing New Inhibitors of c-src Tyrosine Kinase.

A prototype of a family of at least nine members, cellular Src tyrosine kinase is a therapeutically interesting target because its inhibition might be of interest not only in a number of malignancies, but also in a diverse array of conditions, from neurodegenerative pathologies to certain viral infections. Computational methods in drug discovery are considerably cheaper than conventional methods and offer opportunities of screening very large numbers of compounds in conditions that would be simply impossible within the wet lab experimental settings. We explored the use of global quantitative structure-activity relationship (QSAR) models and molecular ligand docking in the discovery of new c-src tyrosine kinase inhibitors. Using a dataset of 1038 compounds from ChEMBL database, we developed over 350 QSAR classification models. A total of 49 models with reasonably good performance were selected and the models were assembled by stacking with a simple majority vote and used for the virtual screening of over 100,000 compounds. A total of 744 compounds were predicted by at least 50% of the QSAR models as active, 147 compounds were within the applicability domain and predicted by at least 75% of the models to be active. The latter 147 compounds were submitted to molecular ligand docking using AutoDock Vina and LeDock, and 89 were predicted to be active based on the energy of binding.