Triamcinolone Diacetate

This study delved into the exploration of bioactive constituent profiling of Floscopa scandens Lour. by using HRLC‐MS. The plant is well‐known as a folklore herb. It is extensively utilized in traditional medicine to address various ailments such as fractures, sore eyes, fevers, abscesses, pyoderma, and acute nephritis. This study aimed to explore the phytochemical composition of F. scandens and assess the anti‐inflammatory activity of the ecdysterone marker compound by molecular docking studies followed by MD simulations. Extracts were prepared using hexane, chloroform, and methanol solvents. Chromatographic techniques were applied to isolate compounds from the methanol extract, which underwent phytochemical screening via HR‐LCMS. Functional groups were assessed using NMR and Fourier transform infrared (FTIR), confirming the presence of bioactive compounds. HR‐LCMS analysis identified 21 phytoconstituents in the methanolic fraction, with ecdysterone being a prominent component characterized through spectroscopic techniques. Our findings confirm known molecules while unveiling new bioactive constituents, particularly highlighting the potential of ecdysterone as a novel chemical entity. Molecular docking and molecular dynamic simulation analysis further show the anti‐inflammatory properties of ecdysterone with various enzymes in the body.

The local interpretable model-agnostic explanation (LIME) method was used to interpret two machine learning models of compounds penetrating the blood-brain barrier. The classification models, Random Forest, ExtraTrees, and Deep Residual Network, were trained and validated using the blood-brain barrier penetration dataset, which shows the penetrability of compounds in the blood-brain barrier. LIME was able to create explanations for such penetrability, highlighting the most important substructures of molecules that affect drug penetration in the barrier. The simple and intuitive outputs prove the applicability of this explainable model to interpreting the permeability of compounds across the blood-brain barrier in terms of molecular features. LIME explanations were filtered with a weight equal to or greater than 0.1 to obtain only the most relevant explanations. The results showed several structures that are important for blood-brain barrier penetration. In general, it was found that some compounds with nitrogenous substructures are more likely to permeate the blood-brain barrier. The application of these structural explanations may help the pharmaceutical industry and potential drug synthesis research groups to synthesize active molecules more rationally.