Network pharmacology approach to bioactive chemical compounds identified from Lespedeza bicolor lignum methanol extract by GC–MS for amelioration of hepatitis

Predicting the bioactive compounds of Lentinula edodes and elucidating its interaction with genes associated to obesity through network pharmacology and in-vitro cell-based assay

Mushrooms are traditionally used for various medicinal purposes in traditional oriental medicine. The Japanese and Chinese are familiar with the medicinal macro fungus Lentinula edodes (Shiitake mushroom). This study aims to evaluate the role of chemical compounds from L. edodes using network pharmacology and in-vitro studies for management of Obesity. Bioactive compounds in extracts of L. edodes were identified by GC-MS analysis. Compounds were later screened for their drug-like property by Lipinski's rule. In addition, public databases (SEA, STP, Omim and DisGenet) were searched to identify genes associated with selected molecules and obesity, as well as genes that overlap obesity target genes with genes related to L. edodes. Additionally, analysis was performed using Enrichr KG to predict the disease targets of L. edodes. Finally, network was constructed between the overlapping genes and bioactive molecules using Rstudio. Further in-vitro studies were carried out using 3T3-L1 cell line. The genes related to the selected compounds and obesity were identified and overlapped. The disease targets of L. edodes was predicted by enrichment analysis and was found to be linked to obesity. Furthermore, the hub gene was found to be fatty acid amide hydrolase, and the key bioactive compound was hexadecanoic acid methyl ester. The in-vitro cell culture studies confirmed the inhibition of adipogenesis in mushroom extract-treated 3T3-L1 cells and the augmentation of adiponectin. The study suggests that the hub gene fatty acid amide hydrolase might alleviate obesity by inhibiting arachidonoyl ethanolamide signaling, which would enhance the action of fatty acid amide hydrolase and limit appetite in L. edodes extract.

Hepatoprotective Effect Associated with Alkaloids from Corydalis tomentella Franch. based on Network Pharmacology, Molecular Docking and in Vitro Experiment

Liver is an important metabolic organ with numerous functions in human body. Hepatitis is defined as the inflammation of the liver tissue, which could lead to acute liver failure, liver fibrosis, liver cirrhosis and hepatocellular carcinoma. Corydalis tomentella Franch., a precious herb in China, is often used in the treatment of hepatitis, liver cirrhosis and liver cancer. In this study, 41 isoquinoline alkaloids and derivatives isolated by our lab from C. tomentella and 61 related targets were analyzed by network pharmacology. Their activities were further verified by cell assay evaluated for antitumor activity against HepG2 cells and molecular docking. The results confirmed that the alkaloids from C.tomentella had extensive hepatoprotective effects, and TNF-α was the key target of hendersinate B methyl ester against acute liver damage by viral hepatitis and HCC, which provided a foundation for further in vivo studies.

Uncovering a Hub Signaling Pathway of Antimicrobial-Antifungal-Anticancer Peptides’ Axis on Short Cationic Peptides via Network Pharmacology Study

Short cationic peptides (SCPs) with therapeutic efficacy of antimicrobial peptides (AMPs), antifungal peptides (AFPs), and anticancer peptides (ACPs) are known as an enhancement of the host defense system. Here, we investigated the uppermost peptide(s), hub signaling pathway(s), and their associated target(s) through network pharmacology. Firstly, we selected SCPs with positive amino acid residues on N- and C- terminals under 500 Dalton via RStudio. Secondly, the overlapping targets between the bacteria-responsive targets (TTD and OMIM) and AMPs’ targets were visualized by VENNY 2.1. Thirdly, the overlapping targets between AFPs’ targets and fungal-responsive targets were exhibited by VENNY 2.1. Fourthly, the overlapping targets between cancer-related targets (TTD and OMIM) and fungal-responsive targets were displayed by VENNY 2.1. Finally, a molecular docking study (MDS) was carried out to discover the most potent peptides on a hub signaling pathway. A total of 1833 SCPs were identified, and AMPs’, AFPs’, and ACPs’ filtration suggested that 197 peptides (30 targets), 81 peptides (6 targets), and 59 peptides (4 targets) were connected, respectively. The AMPs―AFPs―ACPs’ axis indicated that 27 peptides (2 targets) were associated. Each hub signaling pathway for the enhancement of the host defense system was “Inactivation of Rap1 signaling pathway on AMPs”, “Activation of Notch signaling pathway on AMPs―AFPs’ axis”, and “Inactivation of HIF-1 signaling pathway on AMPs―AFPs―ACPs’ axis”. The most potent peptides were assessed via MDS; finally, HPIK on STAT3 and HVTK on NOS2 and on HIF-1 signaling pathway were the most stable complexes. Furthermore, the two peptides had better affinity scores than standard inhibitors (Stattic, 1400 W). Overall, the most potent SCPs for the human defense system were HPIK on STAT3 and HVTK on NOS2, which might inactivate the HIF-1 signaling pathway.

Network pharmacology approach to decipher signaling pathways associated with target proteins of NSAIDs against COVID-19

Non-steroidal anti-inflammatory drugs (NSAIDs) showed promising clinical efficacy toward COVID-19 (Coronavirus disease 2019) patients as potent painkillers and anti-inflammatory agents. However, the prospective anti-COVID-19 mechanisms of NSAIDs are not evidently exposed. Therefore, we intended to decipher the most influential NSAIDs candidate(s) and its novel mechanism(s) against COVID-19 by network pharmacology. FDA (U.S. Food & Drug Administration) approved NSAIDs (19 active drugs and one prodrug) were used for this study. Target proteins related to selected NSAIDs and COVID-19 related target proteins were identified by the Similarity Ensemble Approach, Swiss Target Prediction, and PubChem databases, respectively. Venn diagram identified overlapping target proteins between NSAIDs and COVID-19 related target proteins. The interactive networking between NSAIDs and overlapping target proteins was analyzed by STRING. RStudio plotted the bubble chart of the KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichment analysis of overlapping target proteins. Finally, the binding affinity of NSAIDs against target proteins was determined through molecular docking test (MDT). Geneset enrichment analysis exhibited 26 signaling pathways against COVID-19. Inhibition of proinflammatory stimuli of tissues and/or cells by inactivating the RAS signaling pathway was identified as the key anti-COVID-19 mechanism of NSAIDs. Besides, MAPK8, MAPK10, and BAD target proteins were explored as the associated target proteins of the RAS. Among twenty NSAIDs, 6MNA, Rofecoxib, and Indomethacin revealed promising binding affinity with the highest docking score against three identified target proteins, respectively. Overall, our proposed three NSAIDs (6MNA, Rofecoxib, and Indomethacin) might block the RAS by inactivating its associated target proteins, thus may alleviate excessive inflammation induced by SARS-CoV-2.

A network pharmacology study on main chemical compounds from Hibiscus cannabinus L. leaves

Hibiscus cannabinus L. leaves (HCLLs) are considered a favorable source of natural antiobesity substances. However, actual bioactive compound(s) in it and their mechanism(s) against obesity have not been confirmed. Hence, network pharmacology was conducted to identify its key compounds and mechanism(s) against obesity. Compounds in HCLLs were identified through GC-MS analysis and screened by Lipinski's rule. Genes related to the selected compounds and obesity were obtained from public databases, and overlapping genes between HCLL compound-related genes and obesity target genes were selected using a Venn diagram. The networking between selected compounds and overlapping genes was then constructed, visualized, and analyzed by RStudio. Finally, the binding affinity between compounds and genes was evaluated via molecular docking (MD). A total of 30 compounds in HCLLs were detected via GC-MS, and Lipinski's rule accepted all compounds. The compound-related genes (570 genes) and obesity targeted genes (3028 genes) were identified, and between them, 64 overlapping genes were selected. Gene Set Enrichment Analysis (GSEA) displayed that the mechanisms of HCLLs against obesity were associated with 13 signaling pathways on 22 compounds in HCLLs. Superficially, AKT1, vitamin E, and RAS signaling pathways were noted as a hub gene, an uppermost bioactive compound, and a hub signaling pathway, respectively. However, the binding affinity of ligands and proteins on the RAS signaling pathway was very low; instead, the PPAR signalling pathway was evaluated with potent efficacy against obesity through MD. On the PPAR signaling pathway, α-amyrin was found as the most significant compound for the amelioration of obesity. α-Amyrin manifested the strongest binding affinity on six target proteins associated with the PPAR signaling pathway. Our study suggests that an auxiliary (PPAR) signaling pathway of HCLLs might intervene efficiently against obesity over the hub (RAS) signaling pathway.