scholarly journals Identification of Potential Bioactive Ingredients and Mechanisms of the Guanxin Suhe Pill on Angina Pectoris by Integrating Network Pharmacology and Molecular Docking

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Mingmin Wang ◽  
Shuangjie Yang ◽  
Mingyan Shao ◽  
Qian Zhang ◽  
Xiaoping Wang ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Angina Pectoris ◽  
Protein Interaction ◽  
Interaction Analysis ◽  
Network Pharmacology ◽  
Biological Processes ◽  
Protein Protein Interaction ◽  
Go Enrichment ◽  
Chemokine Ligand ◽  
Bioactive Ingredients

The Guanxin Suhe pill (GSP), a traditional Chinese medicine, has been widely used to treat angina pectoris (AP) in Chinese clinical practice. However, research on the bioactive ingredients and underlying mechanisms of GSP in AP remains scarce. In this study, a system pharmacology approach integrating gastrointestinal absorption (GA) evaluation, drug-likeness (DL) evaluation, target exploration, protein-protein-interaction analysis, Gene Ontology (GO) enrichment analysis, network construction, and molecular docking was adopted to explore its potential mechanisms. A total of 481 ingredients from five herbs were collected, and 242 were qualified based on GA and DL evaluation. Target exploration identified 107 shared targets between GSP and AP. Protein-protein interaction identified VEGFA (vascular endothelial growth factor A), TNF (tumor necrosis factor), CCL2 (C-C motif chemokine ligand 2), FN1 (fibronectin 1), MMP9 (matrix metallopeptidase 9), PTGS2 (prostaglandin-endoperoxide synthase 2), IL10 (interleukin 10), CXCL8 (C-X-C motif chemokine ligand 8), IL6 (interleukin 6), and INS (insulin) as hub targets for GSP, which were involved in the inflammatory process, ECM proteolysis, glucose metabolism, and lipid metabolism. GO enrichment identified top pathways in the biological processes, molecular functions, and cell components, explaining GSP’s potential AP treatment mechanism. Positive regulation of the nitric oxide biosynthetic process and the response to hypoxia ranked highest of the biological processes; core targets that GSP can regulate in these two pathways were PTGS2 and NOS2, respectively. Molecular docking verified the interactions between the core genes in the pathway and the active ingredients. The study lays a foundation for further experimental research and clinical application.

scholarly journals Molecular Mechanism of Gleditsiae Spina for the Treatment of High-grade Serous Ovarian Cancer Based on Network Pharmacology and Experimental Verification

2021 ◽  
Author(s):  
Boran Zhang ◽  
Wenchao Dan ◽  
Xing Chen ◽  
Cunfang Dai ◽  
Guangda Li ◽  
...  
Keyword(s):  
Ovarian Cancer ◽  
Protein Interaction ◽  
Interaction Analysis ◽  
Dynamics Simulation ◽  
Network Pharmacology ◽  
High Grade ◽  
Serous Ovarian Cancer ◽  
Active Ingredients ◽  
Protein Protein Interaction

Abstract Background In this study, we aimed to analyze the pharmacological mechanism of Gleditsiae Spina in the treatment of high-grade serous ovarian cancer (HGSC) based on network pharmacology and in vitro experiments. Methods The main active ingredients of Gleditsiae Spina were identified by high performance liquid chromatography and mass spectrometry, and ADME screening was performed. The component targets of Gleditsiae Spina were screened using the pharmMapper platform, and differentially expressed genes in normal and HGSC tissues were identified through GEO database. Thereafter, Cytoscape 3.7.2 software was used to construct the network of "active ingredient-targets," and the BioGenet database was used for protein-protein interaction analysis. Furthermore, the protein-protein interaction network was established, and the potential protein function module was mined. Biological processes and pathways were analyzed through gene ontology and Kyoto Encyclopedia of Genes and Genomes analysis. Results The core active ingredients of Gleditsiae Spina for regulating HGSC included luteolin, genistein, D-(+)-tryptophan, ursolic acid, and berberine. The ideal targets were HPSE, PI3KCA, AKT1, and CTNNB1. The prediction results were verified by molecular docking, molecular dynamics simulation, and western blot analysis. Conclusions This study revealed the mechanism of Gleditsiae Spina for the treatment of HGSC based on multi-components, multi-targets, and multi-channels. It also provides a theoretical basis for the prevention of ovarian cancer and its treatment using traditional Chinese medicine in the future.

scholarly journals Mechanism of Peony and Licorice and Aconite Decoction in the Treatment of Osteoarthritis Based on Network Pharmacology and Molecular Docking

2021 ◽  
Author(s):  
Zhiqiang li ◽  
Luo Jun
Keyword(s):  
Molecular Docking ◽  
Chinese Medicine ◽  
Protein Interaction ◽  
Active Component ◽  
Kegg Pathway ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Biological Processes ◽  
Pathway Enrichment

Abstract Objective: To predict the key molecular mechanism of Shaoyao Liquorice Aconite Decoction in the treatment of osteoarthritis by using network pharmacology and molecular docking technology, and to provide a new target for the treatment of osteoarthritis. Methods: by means of traditional Chinese medicine database TCMSP screening peony licorice monkshood soup main active component of radix paeoniae alba, radix glycyrrhizae, and the corresponding targets, lateral root of aconite and retrieve OMIM, GeneCards, TDD, PharmGKB and Drugbank database related target for treatment of osteoarthritis, and then forecast drug targets and disease targets for intersection get peony licorice monkshood soup targets for the treatment of osteoarthritis.Then, STRING database and Cytoscape software were used to construct the "drug active component - action target" network and protein interaction network of Shaoyaogaofuzi Decoction in the treatment of osteoarthritis, and David database was used for GO function enrichment analysis and KEGG pathway enrichment analysis of shaoyaogaofuzi Decoction in the treatment of osteoarthritis.Finally, PyMOL, Chem3D, AutoDock, OpenBabel and other software were used to verify the molecular docking of the key active ingredients and key targets of Shaoyao Liquorice Aconite Decoction. Results: 162 active components were screened out.A total of 954 disease targets were collected, and a total of 72 disease targets were obtained after weight removal.Protein interaction analysis suggested that TNF, AKT1, IL6, IL1B and TP53 were the core targets of protein interaction network.Through GO enrichment analysis, 393 biological processes were obtained, and it was found that biological processes were mainly enriched in cell differentiation, migration, apoptosis, and cell stress response to organisms.A total of 116 Pathways were obtained through KEGG pathway enrichment analysis, mainly involving Pathways in cancer, TNF Signaling Pathway, Tuberculosis, Chagas disease, Hepatitis B, etc. Finally, the molecular docking of key active molecules and key targets was realized for verification.Conclusions: this study of compound Chinese medicine pharmacology, through the network of peony licorice monkshood soup ingredients with osteoarthritis, targets, pathway analysis, you can see that drugs in the treatment of osteoarthritis is not a simple single targeted therapy, but by many components, multi-channel, mutual communications between the multiple targets, on the treatment of osteoarthritis in the future to provide more advice.

scholarly journals The Mechanism of Compound Anshen Essential Oil in the Treatment of Insomnia Was Examined by Network Pharmacology

2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Guilin Ren ◽  
Yu Zhong ◽  
Gang Ke ◽  
Xiaoli Liu ◽  
Huiting Li ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Essential Oil ◽  
Protein Interaction ◽  
Active Component ◽  
Chloride Transport ◽  
Interaction Network ◽  
Binding Activity ◽  
Network Pharmacology ◽  
Protein Protein Interaction ◽  
Target Network

The active component-target network and protein-protein interaction network of Compound Anshen essential oil were constructed. The target functions and related pathways were analyzed to explore the mechanism of Compound Anshen essential oil in the treatment of insomnia. GC-MS was used to detect the chemical composition of Compound Anshen essential oil, and the TCMSP, STITCH, TTD, and DrugBank databases were searched to predict and screen the targets of Compound Anshen essential oil in the treatment of insomnia. Cytoscape software was used to construct the network diagrams of the active component-action target and protein-protein interaction networks, ClueGO software was used to analyze the GO enrichment and KEGG pathway of the target, and the systemsDock website database was used for molecular docking. The analysis of the network results showed that the activity of Compound Anshen essential oil mainly involves biological processes such as the phospholipase C-activating G protein-coupled receptor signaling pathway, response to ammonium ions, calcium ion transport into the cytosol, and chloride transport. The results of molecular docking showed that linalool, caryophyllene, dibutyl phthalate, (-)-4-terpineol, and (-)-α-terpineol have good binding activity with ADRB2, DRD2, ESR1, KCNH2, NR1H4, NR1I2, NR1I3, and TRPV1 targets. This study demonstrates the multicomponent, multitarget, and multichannel characteristics of Compound Anshen essential oil and provides a new therapeutic idea and method for further research on the mechanism of Compound Anshen essential oil in the treatment of insomnia.

scholarly journals Study on the Antianxiety Mechanism of Suanzaoren Decoction Based on Network Pharmacology and Molecular Docking

2021 ◽  
Vol 2021 ◽  
pp. 1-28
Author(s):  
Xiaocong Xu ◽  
Bingbing Gao ◽  
Xiongying Li ◽  
Shanshan Lei
Keyword(s):  
Molecular Docking ◽  
Binding Energy ◽  
Interaction Analysis ◽  
Modern Medicine ◽  
Network Pharmacology ◽  
Active Components ◽  
Material Basis ◽  
Go Enrichment ◽  
Antianxiety Drug ◽  
Analysis Platform

Objective. Suanzaoren Decoction (SZRT) is a classic decoction to calm the nerves in traditional Chinese medicine (TCM). It has been extensively treated as an antianxiety drug in modern times, but the material basis and pharmacological mechanisms are still unclear. To explore the material basis and corresponding potential targets, as well as to elucidate the mechanism of SZRT, network pharmacology and molecular docking methods were utilized. Methods. The main chemical compounds and potential targets of SZRT were collected from the pharmacological database analysis platform (TCMSP). Anxiety targets were obtained from the GeneCards database. Then, a target compound network was established using overlapping genes and the corresponding potential compounds. Protein interaction analysis, GO enrichment, and KEGG pathway enrichment were performed using the STRING database, DAVID database, and KOBAS database. Finally, molecular docking was conducted between MAOB and its corresponding active compound in SZRT to further verify the results. Results. A total of 137 active components in SZRT were screened from the TCMSP database, and 210 corresponding targets were predicted. A total of 5434 anxiety-related targets were obtained from the disease target database, and finally 22 potential targets of SZRT on antianxiety were obtained. The constructed C-T network showed that the average degree of active components was 5.4, and four of them interacted with six or more targets. PPI analysis shows that key genes such as MAOA, MAOB, IL1B, TNF, NR3CI, and HTR3A were identified as potential therapeutic targets. A pathway analysis showed that SZRT may participate in neurotransmitter regulation and immunoregulation in a synergistic way to treat anxiety. The binding energy between the active compounds and MAOB was low, indicating good binding. The results of molecular docking showed that all the 10 active ingredients were able to successfully dock with MAOB, and the binding energy of coumaroyltyramine with MAOB was the lowest, that is, −9.6 kcal/mol, and the binding method was hydrogen bonding. Conclusions. SZRT produces antianxiety effects mainly by affecting the neurotransmitter release, transmission, and immunoregulation. This study provides a new approach to elucidating the molecular mechanism and material basis of SZRT in the treatment of anxiety, and it will also benefit the application of TCM in modern medicine.

scholarly journals Systematic elucidation of the pharmacological mechanisms of Rhynchophylline for treating epilepsy via network pharmacology

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Hua Geng ◽  
Xuqin Chen ◽  
Chengzhong Wang
Keyword(s):  
Gene Ontology ◽  
Oral Bioavailability ◽  
Target Genes ◽  
Interaction Analysis ◽  
Network Pharmacology ◽  
Receptor Interaction ◽  
Biological Processes ◽  
Pathway Network ◽  
Protein Protein Interaction ◽  
Network Analyses

Abstact Background Epilepsy, one of the most common neurological disorders, affects over 70 million people worldwide. Rhynchophylline displays a wide variety of pharmacologic actives. However, the pharmacologic effects of rhynchophylline and its mechanisms against epilepsy have not been systematically elucidated. Methods The oral bioavailability and druglikeness of rhynchophylline were evaluated using the Traditional Chinese Medicine Systems Pharmacology Database. Rhynchophylline target genes to treat epilepsy were identified using PharmMapper, SwissTargetPrediction and DrugBank databases integration. Protein-protein interaction analysis was carried out by utilizing the GeneMANIA database. WebGestalt was employed to perform Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses. The drug-disease-target-Gene Ontology-pathway network was constructed using Cytoscape. Results The oral bioavailability and druglikeness of rhynchophylline were calculated to be 41.82% and 0.57, respectively. A total of 20 rhynchophylline target genes related to epilepsy were chosen. Among the 20 genes and their interacting genes, 54.00% shared protein domains and 16.61% displayed co-expression characteristics. Gene ontology, Kyoto Encyclopedia of Genes and Genomes and network analyses illustrate that these targets were significantly enriched in regulation of sensory perception, morphine addiction, neuroactive ligand-receptor interaction and other pathways or biological processes. Conclusion In short, rhynchophylline targets multiple genes or proteins, biological processes and pathways. It shapes a multiple-layer network that exerts systematic pharmacologic activities on epilepsy.

scholarly journals Network pharmacology and molecular docking study on the active ingredients of qidengmingmu capsule for the treatment of diabetic retinopathy

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Mingxu Zhang ◽  
Jiawei Yang ◽  
Xiulan Zhao ◽  
Ying Zhao ◽  
Siquan Zhu
Keyword(s):  
Diabetic Retinopathy ◽  
Molecular Docking ◽  
Molecular Mechanisms ◽  
Hypoxia Inducible Factor ◽  
Enrichment Analysis ◽  
Docking Study ◽  
Network Pharmacology ◽  
Biological Processes ◽  
Active Ingredients ◽  
Molecular Docking Study

AbstractDiabetic retinopathy (DR) is a leading cause of irreversible blindness globally. Qidengmingmu Capsule (QC) is a Chinese patent medicine used to treat DR, but the molecular mechanism of the treatment remains unknown. In this study, we identified and validated potential molecular mechanisms involved in the treatment of DR with QC via network pharmacology and molecular docking methods. The results of Ingredient-DR Target Network showed that 134 common targets and 20 active ingredients of QC were involved. According to the results of enrichment analysis, 2307 biological processes and 40 pathways were related to the treatment effects. Most of these processes and pathways were important for cell survival and were associated with many key factors in DR, such as vascular endothelial growth factor-A (VEGFA), hypoxia-inducible factor-1A (HIF-1Α), and tumor necrosis factor-α (TNFα). Based on the results of the PPI network and KEGG enrichment analyses, we selected AKT1, HIF-1α, VEGFA, TNFα and their corresponding active ingredients for molecular docking. According to the molecular docking results, several key targets of DR (including AKT1, HIF-1α, VEGFA, and TNFα) can form stable bonds with the corresponding active ingredients of QC. In conclusion, through network pharmacology methods, we found that potential biological mechanisms involved in the alleviation of DR by QC are related to multiple biological processes and signaling pathways. The molecular docking results also provide us with sound directions for further experiments.

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