A Network Pharmacology Approach to Explore the Mechanisms of Artemisiae scopariae Herba for the Treatment of Chronic Hepatitis B

Through network pharmacology and molecular docking to explore the underlying mechanism of Artemisia annua L. treating in abdominal aortic aneurysm

Background: Abdominal aortic aneurysm (AAA) is a degenerative disease that causes health problems in humans. However, there are no effective drugs for the treatment of AAA. Artemisia annua L. (A. annua) is a traditional herbal that has been widely used in cardiovascular disease. Based on network pharmacology and molecular docking technology, this study predicted the practical components and potential mechanisms of A. annua inhibiting the occurrence and development of AAA.

Methods: The main active ingredients and targets of A. annua were screened through the TCMSP database; the GeneCards, OMIM, PharmGkb, and TTD databases were used to search for the targeted genes of AAA and map them to the targets of the active ingredients to obtain the active ingredient therapy of A. annua. The targets of AAA were to construct a protein interaction network through the STRING platform. R software was used to carry out the enrichment analysis of GO and KEGG for relevant targets, and Cytoscape was used to construct the active ingredient-target network prediction model of A. annua. Finally, AutoDock Vina was used to verify the results of the active ingredients and critical targets.

Results: The main active ingredients obtained from A. annua for the treatment of AAA include quercetin, luteolin, kaempferol, isorhamnetin, and artemetin, as well as 117 effective targets, including RELA, MAPK14, CCND1, MAPK1, AKT1, MYC, MAPK8, TP53, ESR1, FOS, and JUN. The 11 targeted genes might play a key role in disease treatment. Enriched in 2115 GO biological processes, 159 molecular functions, 56 cellular components, and 156 KEGG pathways, inferred that its mechanism of action might be related to PI3K-Akt signaling pathway, fluid shear stress, atherosclerosis, and AGE-RAGE signaling pathway. Molecular docking results showed that the top five active components of A. annua had a good affinity for core disease targets and played a central role in treating AAA. The low binding energy molecular docking results provided valuable information for the development of drugs to treat AAA.

Conclusion: Therefore, A. annua may have multiple components, multiple targets, and multiple signaling pathways to play a role in treating AAA. A. annua may have the potential to treat AAA.

Prediction of the Active Components and Mechanism of Forsythia suspensa Leaf against Respiratory Syncytial Virus Based on Network Pharmacology

Objective

Forsythia suspensa leaf (FSL) has been used as a health tea in China for centuries. Previous experiments have proved that FSL extract has a good effect on the antirespiratory syncytial virus (RSV) in vitro, but its exact mechanism is not clear. Therefore, this study aims to determine the active components and targets of FSL and further explore its anti-RSV mechanism.

Methods

UPLC-Q-Exactive-MS was used to analyze the main chemical components of FSL. The compound disease target network, PPI, GO, and KEGG were used to obtain key targets and potential ways. Then, the molecular docking was verified by Schrödinger Maestro software. Next, the cell model of RSV infection was established, and the inhibitory effect of each drug on RSV was detected. Finally, western blotting was used to detect the effect of the active components of FSL on the expression of PI3K/AKT signaling pathway-related protein.

Results

UPLC-Q-Exactive-MS analysis showed that there were 67 main chemical constituents in FSL, while network pharmacological analysis showed that there were 169 anti-RSV targets of the active components in FSL, involving 177 signal pathways, among which PI3K/AKT signal pathway played an important role in the anti-RSV process of FSL. The results of molecular docking showed that cryptochlorogenic acid, phillyrin, phillygenin, rutin, and rosmarinic acid had higher binding activities to TP53, STAT3, MAPK1, AKT1, and MAPK3, respectively. In vitro experiments showed that phillyrin and rosmarinic acid could effectively improve the survival rate of RSV-infected cells, increase the expression level of PI3K, and decrease the expression level of AKT.

Conclusion

The active ingredients of FSL, phillyrin, and rosmarinic acid can play an anti-RSV role by inhibiting PI3K/AKT signaling pathway. This study provides reliable theoretical and experimental support for the anti-RSV treatment of FSL.

Mitigation of Gastric Damage Using Cinnamomum cassia Extract: Network Pharmacological Analysis of Active Compounds and Protection Effects in Rats

Gastritis is a common disease worldwide that is caused by various causes such as eating habits, smoking, severe stress, and heavy drinking, as well as Helicobacter pylori infections and non-steroidal anti-inflammatory drugs. Cinnamomum cassia is a tropical aromatic evergreen tree commonly used as a natural medicine in Asia and as a functional food ingredient. Studies have reported this species' anti-obesity, anti-diabetic, and cardiovascular disease suppression effects. We evaluated the potential effects of C. cassia using non-steroidal anti-inflammatory drugs (NSAIDs), ethanol (EtOH), and ethanol/hydrochloric acid (HCl)-induced gastric mucosal injury models. C. cassia extracts reduced the area of gastric mucosa injury caused by indomethacin, NSAID, EtOH, and EtOH/HCl. We also applied a network pharmacology-based approach to identify the active compounds, potential targets, and pharmacological mechanisms of C. cassia against gastritis. Through a network pharmacology analysis, 10 key components were predicted as anti-gastritis effect-related compounds of C. cassia among 51 expected active compounds. The NF-κB signaling pathway, a widely known inflammatory response mechanism, comprised a major signaling pathway within the network pharmacology analysis. These results suggest that the anti-gastritis activities of C. cassia may be induced via the anti-inflammatory effects of key components, which suppress the inflammation-related genes and signaling pathways identified in this study.

Network Pharmacology-Based Approach to Investigate the Molecular Targets of Rhubarb for Treating Cancer

Background

As a traditional Chinese medicine, rhubarb (also named Dahuang) is used to treat various diseases.

Objective

To explore the possible antitumor mechanism of rhubarb by using network pharmacology and molecular docking in this study.

Methods

Bioactive ingredients and related targets of rhubarb were obtained from the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database. And the gene names corresponding to the proteins were found in the UniProt database. Then, the tumor-related targets were screened out from GeneCards and OMIM databases. Key antitumor targets of rhubarb were acquired by overlapping the above targets via the Venn diagram. The antitumor targets network of rhubarb active components was constructed by using Cytoscape 3.6.0 software. The protein interactions network was constructed using the STRING database. The GO and KEGG pathways involved in the targets were analyzed by using the DAVID database. Autodock Vina software was used to verify the molecular docking of rhubarb components and key targets.

Results

Through screening and analysis, 10 active ingredients and 58 antitumor prediction targets were obtained and constructed a compound-target network. The targets such as CASP3, JUN, MYC, TNF, and PTGS2 may play a crucial role. These targets are involved in cancer pathway, calcium signaling pathway, cell apoptosis, small-cell lung cancer pathway, p53 signaling pathway, and TNF signaling pathway. The docking results indicated that the rhein binding with the CASP3 showed the highest binding energy.

Conclusion

Based on the network pharmacology, the characteristics of multicomponent, multitarget, and multipathway of rhubarb were discussed, which provided a scientific basis for explaining the mechanism in treating cancer and new ideas for further research.