The objective of this work is to explore the effect and potential mechanism of Punicalagin (Pun) in managing Alzheimer’s disease (AD) based on computer-aided drug technology. The following methods were used: the intersection genes of Pun and AD were retrieved from the database and subjected to PPI analysis, GO, and KEGG enrichment analyses. Preliminary verification was performed by molecular docking, molecular dynamics (MD) simulation, and combined free energy calculation. The motor coordination and balance ability, anxiety degree, spatial learning, and memory ability of mice were measured by a rotating rod fatigue instrument, elevated cross maze, and Y maze, respectively. The amyloid β protein (Aβ) in the hippocampus was examined by immunohistochemistry, and the phosphorylation of serine at position 404 of the tau protein (Tau-pS404) was examined by western blot in the mouse brain. The PPI network of Pun showed that the intersection genes were closely related and enriched in muscle cell proliferation and the response to lipopolysaccharide. Results of molecular docking, MD simulations, and MM-GBSA demonstrated that Pun was closely bound to the target protein. Pun could improve the cognitive function of AD mice, as well as reduce Aβ1‑42 deposition and Tau phosphorylation in the brain (P < 0.05, P < 0.01). It can be concluded that Pun holds great promise in improving the cognitive function of AD mice. Mechanistically, Pun potentially acts on ALB, AKT1, SRC, EGFR, CASP3, and IGF-1 targets and mediates proteoglycan, lipid, and atherosclerosis in cancer, so as to reduce the accumulation of neurotoxic proteins in the brain.

Background: The Chinese medicine punicalagin (Pun), the most important active ingredient in pomegranate peel, has significant bacteriostatic and anti-inflammatory properties. The potential mechanisms of Pun for bacterial enteritis, however, are unknown. Objective: The goal of our research is to investigate the mechanism of Pun in the treatment of bacterial enteritis using computer-aided drug technology, as well as to investigate the intervention effect of Pun on mice with bacterial enteritis using intestinal flora sequencing. Methods: The targets of Pun and Bacterial enteritis were obtained by using the specific database, and cross-targets were screened among these targets, followed by PPI and enrichment analysis of the targets. Furthermore, the degree of binding between Pun and key targets were predicted through molecular docking. After successfully establishing the bacterial enteritis model in vivo, mice were randomly assigned to groups. They were treated for 7 days, the symptoms were observed daily, and the daily DAI and body weight change rate were calculated. Following administration, the intestinal tissue was removed, and the contents were separated. The tight junction protein expression was detected in the small intestine by the immunohistochemical method; ELISA and Western Blot (WB) were performed to detect the expressions of tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6) in the serum and intestinal wall of mice. The 16S rRNA sequence was used to determine the composition and diversity of the intestinal flora of mice. Results: In total, 130 intersection targets of Pun and disease were screened by network pharmacology. The enrichment analysis showed cross genes were closely related and enriched in the cancer regulation and the TNF signal pathway. The active components of Pun could specifically bind to the core targets TNF, IL-6, etc., determined from molecular docking results. In vivo experiment results showed that the symptoms in the PUN group mice were alleviated, and the expression levels of TNF-α and IL-6 were significantly reduced. Pun can cause substantial changes in the intestinal flora of mice in terms of structure and function. Conclusion: Pun plays a multi-target role in alleviating bacterial enteritis by regulating intestinal flora.