Phosphatidylinositol-4,5-bisphosphate [PtdIns(4,5)P 2 ] is a key second messenger that regulates actin and membrane dynamics, as well as other cellular processes. Many of the effects of PtdIns(4,5)P 2 are mediated by binding to effector proteins that contain a pleckstrin homology (PH) domain. Here, we identify two novel effectors of PtdIns(4,5)P 2 in the budding yeast Saccharomyces cerevisiae: the PH domain containing protein Slm1 and its homolog Slm2. Slm1 and Slm2 serve redundant roles essential for cell growth and actin cytoskeleton polarization. Slm1 and Slm2 bind PtdIns(4,5)P 2 through their PH domains. In addition, Slm1 and Slm2 physically interact with Avo2 and Bit61, two components of the TORC2 signaling complex, which mediates Tor2 signaling to the actin cytoskeleton. Together, these interactions coordinately regulate Slm1 targeting to the plasma membrane. Our results thus identify two novel effectors of PtdIns(4,5)P 2 regulating cell growth and actin organization and suggest that Slm1 and Slm2 integrate inputs from the PtdIns(4,5)P 2 and TORC2 to modulate polarized actin assembly and growth.

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.

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.

Licorice, a traditional Chinese medicine, has been widely used for the treatment of COVID-19, but all active compounds and the 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 and to collect information regarding different representative compounds. A graph convolutional neural network was used to construct a molecular map and a convolutional neural network was used to develop a Morgan fingerprint. Twenty core compounds and 6 core targets were predicted, among which 4 compounds (quercetin, naringenin, liquiritigenin, and licoisoflavanone), 2 targets (SYK and JAK2) and the relevant pathways (P53, cAMP, and NF-kB) were associated with SARS-CoV-2-infection, which were confirmed by previous studies. In addition, 2 new active compounds (glabrone and vestitol) and 2 new targets (PTEN and MAP3K8) were further validated by molecular docking, and the results showed that these active compounds bound to SARS-CoV-2 related targets, including the main protease (Mpro, also called 3CLpro), the spike protein (S protein), and the angiotensin-converting enzyme 2 (ACE2). Overall, we conclude that the findings of this study has the value of further exploration in the following experiment and clinical application.

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