Exploring the Potential Mechanism of Action of Ursolic Acid against Gastric Cancer and COVID-19 using Network Pharmacology and Bioinformatics Analysis.

BACKGROUND: Patients with gastric cancer (GC) are more likely to be infected with 2019 coronavirus disease (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and the prognosis is worse. It is urgent to find effective treatment methods. OBJECTIVE: This study aimed to explore the potential targets and mechanism of ursolic acid (UA) on GC and COVID-19 by network pharmacology and bioinformatics analysis. METHODS: The online public database and weighted co-expression gene network analysis (WGCNA) were used to screen the clinical related targets of GC. COVID-19-related targets were retrieved from online public databases. Then, a clinicopathological analysis was performed on GC and COVID-19 intersection genes. Following that, the related targets of UA and the intersection targets of UA and GC/COVID-19 were screened. Gene Ontology (GO) and Kyoto Encyclopedia of Gene and Genome Analysis (KEGG) pathway enrichment analyses were performed on the intersection targets. Core targets were screened using a constructed protein-protein interaction network. Finally, molecular docking and molecular dynamics simulation (MDS) of UA and core targets were performed to verify the accuracy of the prediction results. RESULTS: A total of 347 GC/COVID-19-related genes were obtained. The clinical features of GC/COVID-19 patients were revealed using clinicopathological analysis. Three potential biomarkers (TRIM25, CD59, MAPK14) associated with the clinical prognosis of GC/COVID-19 were identified. A total of 32 intersection targets of UA and GC/COVID-19 were obtained. The intersection targets were primarily enriched in FoxO, PI3K/Akt, and ErbB signaling pathways. HSP90AA1, CTNNB1, MTOR, SIRT1, MAPK1, MAPK14, PARP1, MAP2K1, HSPA8, EZH2, PTPN11, and CDK2 were identified as core targets. Molecular docking revealed that UA strongly binds to its core targets. The MDS results revealed that UA stabilizes the protein-ligand complexes of PARP1, MAPK14, and ACE2. CONCLUSION: This study found that in patients with gastric cancer and COVID-19, UA may bind to ACE2, regulate core targets such as PARP1 and MAPK14, and the PI3K/Akt signaling pathway, and participate in antiinflammatory, anti-oxidation, anti-virus, and immune regulation to exert therapeutic effects.

Potential Material Basis of Yupingfeng Powder for the Prevention and Treatment of 2019 Novel Coronavirus Pneumonia: A Study Involving Molecular Docking and Molecular Dynamic Simulation Technology.

Objective: In this study, we investigated the potential material basis of Yupingfeng powder in the prevention and treatment of 2019 novel coronavirus pneumonia (NCP) by applying molecular docking and molecular dynamic simulation technology. Design: The active ingredients and predictive targets of Yupingfeng powder were sourced using the TCMSP, ETCM, and TCMIP traditional Chinese medicine databases. NCP-related targets were then acquired from the DisGeNET and GeneCards databases, and common disease-drug targets were imported into the STRING database, and Cytoscape software was used to generate a protein-protein interaction network following the use of a network topology algorithm to identify key target genes. Gene Ontology (GO) and KEGG pathway enrichment analysis was then performed using the target genes and GOEAST and DAVID online tools. The mechanism of Yupingfeng powder in the prevention and treatment of NCP was analyzed with reference to the relevant literature. AutoDock software was used for molecular docking, the preliminary analysis of binding status, and to identify the best conformation. Desmond software was used to perform molecular dynamic simulations for protein and compound complexes, perform free energy calculations and hydrogen bond analysis, and to further verify the binding mode. Results: Overall, 38 main active components and 218 predictive targets of Yupingfeng powder were identified and 298 disease targets related to NCP were retrieved from disease databases. Yupingfeng powder was found to act predominantly on the TNF, Toll-like receptor, HIF-1, NOD-like receptor, cytokine-receptor interaction, MAPK, T cell receptor, and VEGF signaling pathways. Molecular docking of the three selected key active components with the 3CL-like protease (3CL-Pro) of SARS-CoV-2 showed that they each had a strong binding force and good affinity. Conclusions: Yupingfeng powder primarily acts on multiple active ingredients and potential targets through multiple action channels and signal pathways. Molecular docking and molecular dynamic simulation technology were used to effectively predict and analyze the potential mechanism by which this Chinese medicine can combat NCP. These results provide a reference for developing new modern Chinese medicine preparations against NCP in the future.

Potential mechanism of Astragalus membranaceus in the prevention of COVID-19 based on network pharmacology and molecular docking

Objective: To explore the potential molecular mechanism of Astragalus membranaceus in the treatment of coronavirus disease 2019(COVID-19)based on the network pharmacology and molecular docking. Methods The traditional Chinese medicine systems pharmacology database and analysis platform(TCMSP)and the related literature were searched to obtain the active ingredients and predictive targets of Astragalus membranaceus. The herbal targets were selected based on STRING database for PPI network construction and the results were displayed by Cytoscape software. The key targets were screened through the algorithm of network topology and the network modules were analyzed. Gene Ontology(GO)analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analysis were carried out on key target genes using Gene Ontology Enrichment Analysis Software Toolkit(GOEAST)and The Database for Annotation, Visualization and Integrated Discovery(DAVID)online tools. Combined with relevant literature, the mechanism of Astragalus membranaceus in the treatment of COVID-19 was analyzed. Results A total of 19 candidate active components and 889 predictive targets of Astragalus membranaceus were selected by oral bioavailability(OB)and drug-likeness(DL)values. The preventive mechanism of Astragalus membranaceus might be closely related to the signal pathways involved in the body's living nerve ligand receptor interaction, calcium signal, T cell receptor, cAMP signal pathway and chemokines. Conclusion Astragalus membranaceus mainly plays roles in many kinds of targets through multi-approach and multi-signaling pathways.