Deep learning-based network pharmacology for exploring the mechanism of licorice for the treatment of COVID-19.

Licorice, a traditional Chinese medicine, has been widely used for the treatment of COVID-19, but all active compounds and corresponding targets are still not clear. Therefore, this study proposed a deep learning-based network pharmacology approach to identify more potential active compounds and targets of licorice. 4 compounds (quercetin, naringenin, liquiritigenin, and licoisoflavanone), 2 targets (SYK and JAK2) and the relevant pathways (P53, cAMP, and NF-kB) were predicted, which were confirmed by previous studies to be associated with SARS-CoV-2-infection. In addition, 2 new active compounds (glabrone and vestitol) and 2 new targets (PTEN and MAP3K8) were further validated by molecular docking and molecular dynamics simulations (simultaneous molecular dynamics), as well as the results showed that these active compounds bound well to COVID-19 related targets, including the main protease (Mpro), the spike protein (S-protein) and the angiotensin-converting enzyme 2 (ACE2). Overall, in this study, glabrone and vestitol from licorice were found to inhibit viral replication by inhibiting the activation of Mpro, S-protein and ACE2; related compounds in licorice may reduce the inflammatory response and inhibit apoptosis by acting on PTEN and MAP3K8. Therefore, licorice has been proposed as an effective candidate for the treatment of COVID-19 through PTEN, MAP3K8, Mpro, S-protein and ACE2.

Exploring Myocardial Ischemia-Reperfusion Injury Mechanism of Cinnamon by Network Pharmacology, Molecular Docking, and Experiment Validation.

Myocardial ischemia-reperfusion injury (MIRI) is a common complication of acute myocardial infarction that seriously endangers human health. Cinnamon, a traditional Chinese medicine, has been used to counteract MIRI as it has been shown to possess anti-inflammatory and antioxidant properties. To investigate the mechanisms of action of cinnamon in the treatment of MIRI, a deep learning-based network pharmacology method was established to predict potential active compounds and targets. The results of the network pharmacology showed that oleic acid, palmitic acid, beta-sitosterol, eugenol, taxifolin, and cinnamaldehyde were the main active compounds, and phosphatidylinositol-3 kinase (PI3K)/protein kinase B (Akt), mitogen-activated protein kinase (MAPK), interleukin (IL)-7, and hypoxia-inducible factor 1 (HIF-1) are promising signaling pathways. Further molecular docking tests revealed that these active compounds and targets exhibited good binding abilities. Finally, experimental validation using a zebrafish model demonstrated that taxifolin, the active compound of cinnamon, has a potential protective effect against MIRI.