Tyrosine-protein kinase Src plays a key role in cell proliferation and growth under favorable conditions, but its overexpression and genetic mutations can lead to the progression of various inflammatory diseases. Due to the specificity and selectivity problems of previously discovered inhibitors like dasatinib and bosutinib, we employed an integrated machine learning and structure-based drug repurposing strategy to find novel, targeted, and non-toxic Src kinase inhibitors. Different machine learning models including random forest (RF), k-nearest neighbors (K-NN), decision tree, and support vector machine (SVM), were trained using already available bioactivity data of Src kinase targeting compounds.
View Article and Find Full Text PDFCitronellol (CT) is a naturally occurring lipophilic monoterpenoid which has shown anticancer effects in numerous cancerous cell lines. This study was, therefore, designed to examine CT's potential as an anticancer agent against glioblastoma (GBM). Network pharmacology analysis was employed to identify potential anticancer targets of CT.
View Article and Find Full Text PDFFree radical polymerization technique was used to formulate Poloxamer-188 based hydrogels for controlled delivery. A total of seven formulations were formulated with varying concentrations of polymer, monomer ad cross linker. In order to assess the structural properties of the formulated hydrogels, Fourier Transform Infrared Spectroscopy (FTIR), Thermogravimetric analysis (TGA), Differential Scanning Calorimetry (DSC), Scanning electron microscopy (SEM), and X-ray diffraction (XRD) were carried out.
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