Silibinin inhibits acetylcholinesterase activity and amyloid ß peptide aggregation: a dual-target drug for the treatment of Alzheimer's disease.

Alzheimer's disease (AD) is characterized by amyloid ß (Aß) peptide aggregation and cholinergic neurodegeneration. Therefore, in this paper, we examined silibinin, a flavonoid extracted from Silybum marianum, to determine its potential as a dual inhibitor of acetylcholinesterase (AChE) and Aß peptide aggregation for AD treatment. To achieve this, we used molecular docking and molecular dynamics simulations to examine the affinity of silibinin with Aß and AChE in silico. Next, we used circular dichroism and transmission electron microscopy to study the anti-Aß aggregation capability of silibinin in vitro. Moreover, a Morris Water Maze test, enzyme-linked immunosorbent assay, immunohistochemistry, 5-bromo-2-deoxyuridine double labeling, and a gene gun experiment were performed on silibinin-treated APP/PS1 transgenic mice. In molecular dynamics simulations, silibinin interacted with Aß and AChE to form different stable complexes. After the administration of silibinin, AChE activity and Aß aggregations were down-regulated, and the quantity of AChE also decreased. In addition, silibinin-treated APP/PS1 transgenic mice had greater scores in the Morris Water Maze. Moreover, silibinin could increase the number of newly generated microglia, astrocytes, neurons, and neuronal precursor cells. Taken together, these data suggest that silibinin could act as a dual inhibitor of AChE and Aß peptide aggregation, therefore suggesting a therapeutic strategy for AD treatment.

Variational symplectic integrator for long-time simulations of the guiding-center motion of charged particles in general magnetic fields.

A variational symplectic integrator for the guiding-center motion of charged particles in general magnetic fields is developed for long-time simulation studies of magnetized plasmas. Instead of discretizing the differential equations of the guiding-center motion, the action of the guiding-center motion is discretized and minimized to obtain the iteration rules for advancing the dynamics. The variational symplectic integrator conserves exactly a discrete Lagrangian symplectic structure, and has better numerical properties over long integration time, compared with standard integrators, such as the standard and variable time-step fourth order Runge-Kutta methods.