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

Abstract

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 the action mechanism of Jinxin oral liquid on asthma by network pharmacology, molecular docking, and microRNA recognition

“…[77][78][79] Deep learning can also be applied for target identification and supplementation, disease-related component recognition, and screening potential natural products in some TCM studies integrating network pharmacology with machine learning. [80][81][82][83] Furthermore, our team intends to attempt using deep learning in additional research to investigate the efficacy and mechanism of JXOL in asthma, including the assessment of side effects, the prediction of new targets, the enhancement of JXOL composition, etc.…”

Bioinformatics approach and experimental validation reveal the hepatoprotective effect of pachyman against acetaminophen-associated liver injury

“…Frontier bioinformatics analyses including network pharmacology and molecular docking have highlighted the systematic strategies to detail multiple targets and molecular mechanisms of bioactive agents in the treatment of clinical disorders [ 17 ]. Based on network pharmacology-obtained findings, the therapeutic biotargets of natural candidate products against diseases have been revealed, including those of calycosin against cerebral ischemia/reperfusion injury [ 18 ], calycosin against osteosarcoma [ 19 ], and licorice against COVID-19 [ 20 ]. More attentively, our previous report by using network pharmacology approach has been revealed the pharmacological targets and mechanisms of curcumol for treating interstitial cystitis [ 21 ].…”