Exploring the Potential Molecular Mechanism of the Shugan Jieyu Capsule in the Treatment of Depression through Network Pharmacology, Molecular Docking, and Molecular Dynamics Simulation.

Shugan Jieyu Capsule (SJC) is a pure Chinese medicine compound prepared with Hypericum perforatum and Acanthopanacis senticosi. SJC has been approved for the clinical treatment of depression, but the mechanism of action is still unclear. Network pharmacology, molecular docking, and molecular dynamics simulation (MDS) were applied in the present study to explore the potential mechanism of SJC in the treatment of depression. TCMSP, BATMAN-TCM, and HERB databases were used, and related literature was reviewed to screen the effective active ingredients of Hypericum perforatum and Acanthopanacis senticosi. TCMSP, BATMAN-TCM, HERB, and STITCH databases were used to predict the potential targets of effective active ingredients. GeneCards database, DisGeNET database, and GEO data set were used to obtain depression targets and clarify the intersection targets of SJC and depression. STRING database and Cytoscape software were used to build a protein-protein interaction (PPI) network of intersection targets and screen the core targets. The enrichment analysis on the intersection targets was conducted. Then the receiver operator characteristic (ROC) curve was constructed to verify the core targets. The pharmacokinetic characteristics of core active ingredients were predicted by SwissADME and pkCSM. Molecular docking was performed to verify the docking activity of the core active ingredients and core targets, and molecular dynamics simulations were performed to evaluate the accuracy of the docking complex. We obtained 15 active ingredients and 308 potential drug targets with quercetin, kaempferol, luteolin, and hyperforin as the core active ingredients. We obtained 3598 targets of depression and 193 intersection targets of SJC and depression. A total of 9 core targets (AKT1, TNF, IL6, IL1B, VEGFA, JUN, CASP3, MAPK3, PTGS2) were screened with Cytoscape 3.8.2 software. A total of 442 GO entries and 165 KEGG pathways (p <0.01) were obtained from the enrichment analysis of the intersection targets, mainly enriched in IL-17, TNF, and MAPK signaling pathways. The pharmacokinetic characteristics of the 4 core active ingredients indicated that they could play a role in SJC antidepressants with fewer side effects. Molecular docking showed that the 4 core active components could effectively bind to the 8 core targets (AKT1, TNF, IL6, IL1B, VEGFA, JUN, CASP3, MAPK3, PTGS2), which were related to depression by the ROC curve. MDS showed that the docking complex was stable. SJC may treat depression by using active ingredients such as quercetin, kaempferol, luteolin, and hyperforin to regulate targets such as PTGS2 and CASP3 and signaling pathways such as IL-17, TNF, and MAPK, and participate in immune inflammation, oxidative stress, apoptosis, neurogenesis, etc.

Liu Z ，Huang H ，Yu Y ，Jia Y ，Li L ，Shi X ，Wang F ... -  《-》

Exploring the Molecular Mechanism of Action of Yinchen Wuling Powder for the Treatment of Hyperlipidemia, Using Network Pharmacology, Molecular Docking, and Molecular Dynamics Simulation.

Yinchen Wuling powder is often used to treat clinical hyperlipidemia, although its mechanism of action remains unclear. In this study, we aimed to investigate the active ingredients found in Yinchen Wuling powder and find its mechanism of action when treating hyperlipidemia, using a combination of network pharmacology, molecular docking, and molecular dynamics simulation approaches. The TCMSP database was used to obtain the principle active ingredients found in Yinchen Wuling powder and the NCBI and DisGeNet databases were used to obtain the main target genes involved in hyperlipidemia, and the intersectional targets were obtained by EXCEL. We also used Cytoscape 3.7.2 software to construct a "Traditional Chinese Medicine-Active Ingredient-Target" network and use STRING platform to conduct "protein-protein interactional" (PPI) analyses on the intersection targets. Bioconductor software and RX 64 4.0.0 software were then used to perform GO functional enrichment analysis and KEGG pathway enrichment analysis on the targets. Molecular docking of core protein-ligand interactions was modeled using AutoDock Vina software. A simulation of molecular dynamics was conducted for the optimal core protein-ligand obtained by molecular docking using Amber18 software. A total of 63 active ingredients were found in Yinchen Wuling powder, corresponding to 175 targets, 508 hyperlipidemia targets, and 55 intersection targets in total. Cytoscape 3.7.2 showed that the key active ingredients were quercetin, isorhamnetin, taxifolin, demethoxycapillarisin, and artepillin A. The PPI network showed that the key proteins involved were AKT1, IL6, VEGFA, and PTGS2. GO enrichment analysis found that genes were enriched primarily in response to oxygen levels and nutrient levels of the vesicular lumen and were associated with membrane rafts. These were mainly enriched in AGE-RAGE (advanced glycation end products-receptor for advanced glycation end products) signaling pathway in diabetic complications, fluid shear stress, and atherosclerosis, as well as other pathways. The molecular docking results indicated key binding activity between PTGS2-quercetin, PTGS2-isorhamnetin, and PTGS2-taxifolin. Results from molecular dynamics simulations showed that PTGS2-quercetin, PTGS2-isorhamnetin, and PTGS2-taxifolin bound more stably, and their binding free energies were PTGS2-quercetin -29.5 kcal/mol, PTGS2-isorhamnetin -32 kcal/mol, and PTGS2-taxifolin -32.9 kcal/mol. This study is based on network pharmacology and reveals the potential molecular mechanisms involved in the treatment of hyperlipidemia by Yinchen Wuling powder.

Ye J ，Li L ，Hu Z 《-》

Potential Molecular Mechanisms of Ephedra Herb in the Treatment of Nephrotic Syndrome Based on Network Pharmacology and Molecular Docking.

To explore the possible mechanisms of Ephedra herb (EH) in the treatment of nephrotic syndrome (NS) by using network pharmacology and molecular docking in this study. Active ingredients and related targets of EH were obtained from the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database, and the gene names corresponding to the proteins were found through the UniProt database. Then, target genes related to NS were screened out from GeneCards, PharmGKB, and OMIM databases. Next, the intersection targets were obtained successfully through Venn diagram, which were also seen as key target genes of EH and NS. Cytoscape 3.9.0 software was used to construct the effective "active ingredient-target" network diagram, and "drug-ingredient-target-disease (D-I-T-D)" network diagram. After that, the STRING database was used to construct a protein-protein interaction (PPI) network. Furthermore, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment involved in the targets were performed by the DAVID database and ClueGO plugin in Cytoscape. Finally, AutoDockTools software was used for molecular docking to verify the binding strength between main active ingredients and key target proteins. A total of 22 main active ingredients such as quercetin, kaempferol, luteolin, and naringenin were obtained, which could act on 105 targets related to NS. Through PPI network, 53 core targets such as AKT1, TNF, IL6, VEGFA, and IL1B were found, which might play a crucial role in the treatment of NS. Meanwhile, these targets were significantly involved in PI3K-Akt signaling pathway, TNF signaling pathway, AGE-RAGE signaling pathway, hepatitis B, and pathways in cancer through GO and KEGG enrichment analysis. The docking results indicated that active ingredients such as kaempferol, luteolin, quercetin, and naringenin all had good binding to the target protein AKT1 or TNF. Among them, luteolin and naringenin binding with AKT1 showed the best binding energy (-6.2 kcal/mol). This study indicated that the potential mechanism of EH in treating NS may be related to PI3K-Akt signaling pathway, TNF signaling pathway, and AGE-RAGE signaling pathway, which provided better approaches for exploring the mechanism in treating NS and new ideas for further in vivo and in vitro experimental verifications.

Yao T ，Wang Q ，Han S ，Lu Y ，Xu Y ，Wang Y ... -  《-》

Exploring the pharmacological components and effective mechanism of Mori Folium against periodontitis using network pharmacology and molecular docking.

To investigate the main active components, potential targets of action and analyze the potential molecular mechanisms of Mori Folium in preventing and treating periodontitis using network pharmacology and molecular docking methods. The main components and action targets of Mori Folium were obtained in TCMSP and ETCM databases, and then the action targets of Mori Folium components were inversing screening using Swiss Target Prediction and BATMAN-TCM databases. Targets associated with periodontitis were retrieved from OMIM, Genecard, DrugBank, NCBI Gene and DisGeNET databases. Intersectional targets of Mori Folium and periodontitis were obtained by Venn analysis. Construction of an "active components-targets" network to prevent and treat periodontitis in Mori Folium using Cytoscape 3.8.0. The STRING database was used to construct the protein-protein interaction (PPI) network of intersecting targets, and the core network was screened using CytoNCA and MCODE plug-ins. Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) enrichment analyses were performed using the ClusterProfile package of R software, and then the "Mori Folium active components-targets-signaling pathway" network was constructed using Cytoscape software. Molecular docking was performed using AutoDock Vina software, and Pymol and LigPlus visualized the results. Sixteen active components and 1048 targets were screened from Mori Folium, of which 164 were intersectional with periodontitis targets and were considered potential therapeutic targets. The "Mori Folium active components-action targets" network identified Quercetin, Moracin D, Moracin E, Moracin G, Moracin H and Moracin B as the main active ingredients of Mori Folium for the prevention and treatment of periodontitis. PPI network analysis revealed interleukin 6 (IL6), albumin (ALB), tumor necrosis factor (TNF), vascular endothelial growth factor A (VEGFA), RAC-alpha serine/threonine-protein kinase (AKT1), cellular tumor antigen p53 (TP53), prostaglandin G/H synthase 2 (PTGS2), pro-epidermal growth factor (EGF), matrix metalloproteinase 9 (MMP9) and interleukin 6 (IL10) as the top 10 core potential targets. GO and KEGG enrichment analyses showed that the action targets of Mori Folium against periodontitis were mainly related to the response to bacterium and their lipopolysaccharide, angiogenesis and reactive oxygen species metabolic process, as well as through signaling pathways that regulate processes related to the accumulation of advanced glycation end products (AGEs), response to oxidative stress, response to inflammatory, and osteoclast differentiation during the development of the disease. Molecular docking revealed that Quercetin, Moracin D, Moracin E, Moracin G, Moracin H and Moracin B were able to bind stably to AKT1, PTGS2 and ESR1 targets, with Moracin E showing the most stable structure after binding to AKT1. In conclusion, this study revealed the active components, potential targets of action and the potential molecular mechanisms and pharmacological activities involved in the prevention and treatment of periodontitis in Mori Folium, providing a reference for the development of drugs from Mori Folium for the prevention and treatment of periodontitis.

Wu Z ，Ji X ，Shan C ，Song J ，Zhao J ... -  《-》

Exploring the Mechanisms of Self-made Kuiyu Pingchang Recipe for the Treatment of Ulcerative Colitis and Irritable Bowel Syndrome using a Network Pharmacology-based Approach and Molecular Docking.

Ulcerative colitis (UC) and irritable bowel syndrome (IBS) are common intestinal diseases. According to the clinical experience and curative effect, the authors formulated Kuiyu Pingchang Decoction (KYPCD) comprised of Paeoniae radix alba, Aurantii Fructus, Herba euphorbiae humifusae, Lasiosphaera seu Calvatia, Angelicae sinensis radix, Panax ginseng C.A. Mey., Platycodon grandiforus and Allium azureum Ledeb. The aim of the present study was to explore the mechanisms of KYPCD in the treatment of UC and IBS following the Traditional Chinese Medicine (TCM) theory of "Treating different diseases with the same treatment". The chemical ingredients and targets of KYPCD were obtained using the Traditional Chinese Medicine Systems Pharmacology database and analysis platform (TCMSP). The targets of UC and IBS were extracted using the DisGeNET, GeneCards, DrugBANK, OMIM and TTD databases. The "TCM-component-target" network and the "TCM-shared target-disease" network were imaged using Cytoscape software. The protein-protein interaction (PPI) network was built using the STRING database. The DAVID platform was used to analyze the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Using Autodock Tools software, the main active components of KYPCD were molecularly docked with their targets and visualized using PyMOL. A total of 46 active ingredients of KYPCD corresponding to 243 potential targets, 1,565 targets of UC and 1,062 targets of IBS, and 70 targets among active ingredients and two diseases were screened. Core targets in the PPI network included IL6, TNF, AKT1, IL1B, TP53, EGFR and VEGFA. GO and KEGG enrichment analysis demonstrated 563 biological processes, 48 cellular components, 82 molecular functions and 144 signaling pathways. KEGG enrichment results revealed that the regulated pathways were mainly related to the PI3K-AKT, MAPK, HIF-1 and IL-17 pathways. The results of molecular docking analysis indicated that the core active ingredients of KYPCD had optimal binding activity to their corresponding targets. KYPCD may use IL6, TNF, AKT1, IL1B, TP53, EGFR and VEGFA as the key targets to achieve the treatment of UC and IBS through the PI3K-AKT, MAPK, HIF-1 and IL-17 pathways.

Wen Y ，Wang X ，Si K ，Xu L ，Huang S ，Zhan Y ... -  《-》