Anti-Neuroinflammatory Effect of Ombuin from Rhamnus erythroxylon Pall. Leaves in LPS-Induced BV-2 Microglia by Targeting Src and Suppressing the PI3K-AKT/NF-κB Signaling Pathway.

The leaves of Rhamnus erythroxylon Pall. are widely used as tea substitutes in northwest China for their fragrant aroma, anti-irritability, and digestion-enhancing properties. Ombuin, a main flavonoid compound found in the leaves, exhibited notable anti-inflammatory and antioxidant effects. However, its potential role in treating neuroinflammatory-related diseases remains unexplored. Thus, this study aims to evaluate the anti-neuroinflammatory effects of ombuin and to explore the underlying molecular mechanisms. According to our findings, ombuin dramatically reduced the release of interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), IL-1ß, nitric oxide (NO), and reactive oxygen species (ROS) in lipopolysaccharide (LPS)-stimulated BV-2 microglia. Further analysis, including transcriptomics, network pharmacology, molecular docking, and cellular heat transfer assays, revealed that Src was a direct target of ombuin. Western blot analysis showed that ombuin effectively suppressed Src phosphorylation and inhibited the downstream expressions of p-PI3K p85, p-AKT1, p-IKKα/ß, p-IκBα, and nuclear factor κB (NF-κB). Meanwhile, the repression of Src significantly reversed the anti-neuroinflammatory activity of ombuin. Our results identified Src as a direct target of ombuin and implied that ombuin exerted an anti-neuroinflammatory effect by inhibiting Src phosphorylation and suppressing the activation of the PI3K-AKT and NF-κB pathways, which might provide an alternative therapeutic strategy for neurodegenerative diseases.

ParaCopasi: A package for parallel biochemical simulation and analysis.

Biochemical simuflation and analysis play a significant role in systems biology research. Numerous software tools have been developed to serve this area. Using these tools for completing tasks, for example, stochastic simulation, parameter fitting and optimization, usually requires sufficient computational power to make the duration of completion acceptable. COPASI is one of the most powerful tools for quantitative simulation and analysis targeted at biological systems. It supports systems biology markup language and covers multiple categories of tasks. This work develops an open source package ParaCopasi for parallel COPASI tasks and investigates its performance regarding accelerations. ParaCopasi can be installed on platforms equipped with multicore CPU to exploit the cores, scaling from desktop computers to large scale high-performance computing clusters. More cores bring more performance. The results show that the parallel efficiency has a positive correlation with the total workload. The parallel efficiency reaches a level of at least 95% for both homogeneous and heterogenous tasks when computational workload is adequate. An example is illustrated by applicating this package in parameter estimation to calibrate a biochemical kinetics model.