To study the mechanism of galangal in the treatment of gastric cancer by network pharmacology. The TCMSP database was used to collect the effective compounds and potential targets of galangal, and the genes associated with gastric cancer were obtained through the GeneCards database, and Venn obtained the interaction genes of the effective compound targets of galangal and gastric cancer targets, plotted the interaction genes into PPI networks, and screened out key targets. The interacting genes were imported into Metascape database for GO enrichment analysis and KEGG signal enrichment. A total of 13 active compounds and 207 potential downstream target genes were screened by TCMSP database. Have 5222 gastric cancer target genes through GeneCards database, there were a total of 150 interactive genes and 6 key genes: TP53, AKT1, JUN, HSP90AA1, IL6, and CASP3. These interacting genes involved 30 typical GO entries and 20 KEGG signals. Galangal may play a role in the treatment of gastric cancer by means of multi-component, multi-target and multi-signal pathway. Full article

Objective: To investigate the molecular mechanism and simulated validation of Zhi Bai Di Huang Pill (ZBDHP) for the treatment of systemic lupus erythematosus (SLE) using network pharmacology and molecular docking techniques. Methods: The active ingredients of ZBDHP were obtained through the TCMSP database and the Canonical SMILES of the active ingredients were queried through Pubchem. The targets of the active ingredients were predicted in the SwissTarget database based on the SMILES. The SLE-related disease targets were obtained through the GeneCards, OMIM and DisGenets databases, and the intersection targets of ZBDHP and SLE were obtained using the Venny 2.1.0 online platform. Intersection targets build a visual protein interaction network (PPI) through the STRING database, and the core targets were identified by network topology analysis. GO analysis and KEGG pathway enrichment analysis of the intersecting targets were performed using the DAVID database. Finally, the molecular docking of the first four active ingredients and the first four core target genes were verified by Pubchem, the PDB database and CB-Dock online molecular docking technology. Results: ZBDHP screened 91 potential active ingredients and 816 potential targets. Among them, 141 genes were intersected by ZBDHP and SLE. The network topology analysis showed that the main active ingredients were Hydroxygenkwanin, Alisol B, asperglaucide, Cerevisterol, etc., and the key target genes were TNF, AKT1, EGFR, STAT3, etc. GO and KEGG enrichment analysis showed that common targets interfere with biological processes or molecular functions such as signal transduction protein phosphorylation, inflammatory response, transmembrane receptor protein tyrosine kinase activity, etc., through multiple signaling pathways, such as pathways in cancer, Kaposi sarcoma-associated herpesvirus infection, the PI3K-Akt signaling pathway, lipid and atherosclerosis, hepatitis B, etc. Molecular docking results showed that the active components of ZBDHP have good binding activity to the core targets of SLE. Conclusions: This study reveals that the ZBDHP treatment of SLE is a complex mechanistic process with multi-components, multi-targets and multi-pathways, and it may play a therapeutic role in SLE by inhibiting the production, proliferation and apoptosis of inflammatory factors. In conclusion, the present study provides a theoretical basis for further research on ZBDHP. Full article

Glycyrrhiza uralensis is used to treat alcoholic liver injury in China; however, its pharmacological mechanism remains to be clarified. Here, the potential of G. uralensis for the treatment of alcoholic liver injury was explored using a network pharmacology and molecular docking approach. The effective components and targets of G. uralensis were searched in a traditional Chinese medicine systems pharmacology database and analysis platform. Disease targets were obtained using the GeneCards and OMIM databases. The target genes of G. uralensis and alcoholic liver injury were compared to obtain common target genes. Symbol conversion was carried out using the Uniport database, and the composition–target network of G. uralensis and alcoholic liver injury was prepared. A protein–protein interaction network was constructed. Gene Ontology functional enrichment and the Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed. AutoDock was used for the molecular docking of core compounds and key targets. One hundred and ninety-three common target genes of G. uralensis and alcoholic liver injury were screened. We identified targets of five active components of G. uralensis, namely, formononetin, 3′-methoxyglabridin, glypallichalcone, 1-methoxyphaseollidin, and glabridin. The main targets identified via the protein–protein interaction network analysis were JUN, MAPK3, STAT3, AKT1, and MAPK1. The biological processes associated with xenobiotic stimulus and lipopolysaccharide metabolism were involved. These biological processes were common between Glycyrrhiza treatment and liver injury. They mainly involved lipid and atherosclerosis, chemical carcinogenic gene-receptor activation, and Kaposi sarcoma-associated herpesvirus. Shinpterocarpin and 7-methoxy-2-methyl-isoflavone had good docking effects with MAPK3, and their binding energies were less than −5 kcal/mol. Based on the network pharmacology and molecular docking analyses, the chemical compositions, potential targets, and pathways involved in G. uralensis treatment of alcoholic liver injury were successfully predicted. This study lays a foundation for the selection of drugs to treat alcoholic liver injury. Full article

Glutinol, a triterpenoid compound, has no documented systematic investigation into its mechanism. Hence, we used network pharmacology to investigate glutinol’s mechanism. The chemical formula of glutinol was searched in the PubChem database for our investigation. The BindingDB Database was utilized to discover probable glutinol target genes after ADMET analysis with the pkCSM software. DAVID tools were also used to perform Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of target genes. We also uploaded the targets to the STRING database to obtain the protein interaction network at the same time. Then, we performed some molecular docking using glutinol and targets. Finally, we used Cytoscape to visualize and evaluate a protein–protein interaction network and a drug-target-pathway network. Glutinol has good biological activity and drug utilization, according to our findings. A total of 32 target genes were discovered. Bioinformatics and network analysis were used, allowing the discovery that these target genes are linked to carcinogenesis, diabetes, inflammatory response, and other biological processes. These findings showed that glutinol can operate on a wide range of proteins and pathways to establish a pharmacological network that can be useful in drug development and use. Full article

Background: Qianghuo Shengshi decoction (QHSSD), a traditional Chinese medicine formula, is used to treat ankylosing spondylitis (AS) in China. The pharmacological mechanism of QHSSD for AS remains to be clarified. In this study, we investigated the molecular mechanisms of QHSSD in the treatment of AS using network pharmacology and molecular docking. Methods: To obtain the chemical components and potential targets of QHSSD, we used the Traditional Chinese Medicine Systematic Pharmacology Database and Analysis Platform (TCMSP) and SwissTargetPrediction. AS potential targets were found in the GeneCards, OMIM, and DisGenets databases. A Venn diagram was used to screen QHSSD and AS common potential targets. The STRING website and Cytoscape software were used to create and analyze protein–protein interactions and component–target networks. The DAVID database was used for the gene ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Molecular docking was used to visualize drug–target interactions. Results: The component–target network consisted of 119 chemical components and 193 potential targets. QHSSD was implicated in various biological processes, such as inflammation and angiogenesis, and mediated multiple signaling pathways, such as the MAPK signaling pathway. Molecular docking revealed good binding ability between medicarpin, notoptol, vitetrifolin E, and cnidilin and EGFR, TNF-α, ALB, and VEGFA. Conclusions: The chemical compositions, potential targets, and pathways involved in the QHSSD treatment of AS were successfully predicted in this study. This study provides a solid foundation for the selection of drugs to treat AS. Full article

Panax Ginseng C.A. Meyer (PGCAM) is a well-known phytomedicine, but most of its compounds, such as ginsenoside derivatives, have poor absorption and bioavailability profile due to high molecular weight (≥500 Daltons), which is the major hurdle for their clinical application. Hence, this research explored the efficiency of low molecular weight compounds (LMWCs) (<500 Daltons) screened from PGCAM and their anti-COVID-19 mechanisms through network pharmacology. Molecular compounds from PGCAM were identified using public databases and filtered out by the drug-likeness evaluation. Genes interacted with these filtered compounds, and COVID-19-related genes were extracted from public databases. In addition, overlapping genes between compounds and interactive genes were identified using the Venn diagram. In parallel, the networking between compounds and overlapping genes was analyzed by RStudio. The pathway enrichment analysis of overlapping genes was determined by STRING. Finally, the key bioactive compounds were documented through virtual screening. The bubble chart suggested that the mechanisms of PGCAM against COVID-19 were related to 28 signaling pathways. The key molecular anti-COVID-19 mechanisms might be the anti-inflammation, anti-permeability, and pro-apoptosis by inactivating the PI3K-Akt signaling pathway. The six key genes and the five compounds related to the PI3K-Akt signaling pathway were RELA-paeonol, NFKB1-frutinone A, IL6-nepetin, MCL1-ramalic acid, VEGFA-trifolirhizin, and IL2-trifolirhizin. The docking between these key genes and compounds demonstrated promising binding affinity with a good binding score. Overall, our proposed LMWCs from PGCAM provide a fundamental basis with noteworthy pharmacological evidence to support the therapeutic efficacy of PGCAM in relieving the main symptoms of COVID-19. Full article

Worldwide, Tuberculosis (TB) is caused by Mycobacterium tuberculosis bacteria. Ocimum sanctum, commonly known as holy basil (Tulsi), is an herbaceous perennial that belongs to the family Lamiaceae and is considered one of the most important sources of medicine and drugs for the treatment of various diseases. The presented study aims to discover the potential phenomenon of Ocimum sanctum in the medicament of tuberculosis using a network pharmacology approach. Active ingredients of Ocimum sanctum were fetched through two different databases and from literature review and then targets of these compounds were harvested by SwissTargetPrediction. Potential targets of TB were downloaded from GeneCards and DisGNet databases. After screening of mutual targets, enrichment analysis through DAVID was performed. Protein–protein interaction was performed using the String database and visualized by Cytoscape. Then the target-compound-pathway network was constructed with Cytoscape. In the end, molecular docking was performed to get the potential active ingredients against tuberculosis. Eight active ingredients with 776 potential therapeutic targets were obtained from O. sanctum, 632 intersected targets from two databases were found in TB, 72 common potential targets were found from TB and O. sanctum. The topological analysis exposes those ten targets that formed the core PPI network. Furthermore, molecular docking analysis reveals that active compounds have the greater binding ability with the potential target to suppress TB. Full article

Network pharmacology (NP) is a useful, emerging means of understanding the complex pharmacological mechanisms of traditional herbal medicines. Sochehwan (SCH) is a candidate herbal prescription for drug repurposing as it has been suggested to have beneficial effects on metabolic syndrome. In this study, NP was adopted to complement the shortcomings of literature-based drug repurposing strategies in traditional herbal medicine. We conducted in vitro studies to confirm the effects of SCH on potential pharmacological targets identified by NP analysis. Herbal compounds and molecular targets of SCH were explored and screened from a traditional Chinese medicine systems pharmacology database and analysis platform (TCMSP) and an oriental medicine advanced searching integrated system (OASIS). Forty-seven key targets selected from a protein-protein interaction (PPI) network were analyzed with gene ontology (GO) term enrichment and KEGG pathway enrichment analysis to identify relevant categories. The tumor necrosis factor (TNF) and mitogen-activated protein kinase (MAPK) signaling pathways were presented as significant signaling pathways with lowest p-values by NP analysis, which were downregulated by SCH treatment. The signal transducer and activator of transcription 3 (STAT3) was identified as a core key target by NP analysis, and its phosphorylation ratio was confirmed to be significantly suppressed by SCH. In conclusion, the NP-based approach used for target prediction and experimental data obtained from Raw 264.7 cells strongly suggested that SCH can attenuate inflammatory status by modulating the phosphorylation status of STAT3. Full article

(1) Background: Re-emerging influenza threats continue to challenge medical and public health systems. Quercetin is a ubiquitous flavonoid found in food and is recognized to possess antioxidant, anti-inflammatory, antiviral, and anticancer activities. (2) Methods: To elucidate the targets and mechanisms underlying the action of quercetin as a therapeutic agent for influenza, network pharmacology and molecular docking were employed. Biological targets of quercetin and target genes associated with influenza were retrieved from public databases. Compound–disease target (C-D) networks were constructed, and targets were further analyzed using KEGG pathway analysis. Potent target genes were retrieved from the compound–disease–pathway (C-D-P) and protein–protein interaction (PPI) networks. The binding affinities between quercetin and the targets were identified using molecular docking. (3) Results: The pathway study revealed that quercetin-associated influenza targets were mainly involved in viral diseases, inflammation-associated pathways, and cancer. Four targets, MAPK1, NFKB1, RELA, and TP53, were identified to be involved in the inhibitory effects of quercetin on influenza. Using the molecular docking method, we evaluated the binding affinity of each ligand (quercetin)–target and discovered that quercetin and MAPK1 showed the strongest calculated binding energy among the four ligand–target complexes. (4) Conclusion: These findings identified potential targets of quercetin and suggest quercetin as a potential drug for influenza treatment. Full article

Diabetes mellitus (DM), as a chronic disease caused by insulin deficiency or using obstacles, is gradually becoming a principal worldwide health problem. Pueraria lobata is one of the traditional Chinese medicinal and edible plants, playing roles in improving the cardiovascular system, lowering blood sugar, anti-inflammation, anti-oxidation, and so on. Studies on the hypoglycemic effects of Pueraria lobata were also frequently reported. To determine the active ingredients and related targets of Pueraria lobata for DM, 256 metabolites were identified by LC/MS non targeted metabonomics, and 19 active ingredients interacting with 51 DM-related targets were screened. The results showed that puerarin, quercetin, genistein, daidzein, and other active ingredients in Pueraria lobata could participate in the AGE-RAGE signaling pathway, insulin resistance, HIF-1 signaling pathway, FoxO signaling pathway, and MAPK signaling pathway by acting on VEGFA, INS, INSR, IL-6, TNF and AKT1, and may regulate type 2 diabetes, inflammation, atherosis and diabetes complications, such as diabetic retinopathy, diabetic nephropathy, and diabetic cardiomyopathy. Full article

Ilex cornuta Leaves (ICLs) are a representative and traditional prescription for controlling obesity. Nevertheless, the corresponding therapeutic compounds and related pharmacological mechanisms of such medication remain undocumented. The compounds from ICLs were identified by gas chromatography-mass spectrum (GC-MS), and SwissADME confirmed their physicochemical properties. Next, the target proteins related to compounds or obesity-associated proteins were retrieved from public databases. RPackage constructed the protein–protein interaction (PPI) network, a bubble chart, and signaling pathways–target proteins–compounds (STC) network. Lastly, a molecular docking test (MDT) was performed to evaluate the affinity between target proteins and ligands from ICLs. GC-MS detected a total of 51 compounds from ICLs. The public databases identified 219 target proteins associated with selective compounds, 3028 obesity-related target proteins, and 118 overlapping target proteins. Moreover, the STC network revealed 42 target proteins, 22 signaling pathways, and 39 compounds, which were viewed to be remedially significant. The NOD-like receptor (NLR) signaling pathway was considered a key signaling pathway from the bubble chart. In parallel, the MDT identified three target proteins (IL6, MAPK1, and CASP1) on the NLR signaling pathway and four compounds against obesity. Overall, four compounds from ICLs might show anti-obesity synergistic efficacy by inactivating the NLR signaling pathway. Full article