scholarly journals Comparison between Heat-Clearing Medicine and Antirheumatic Medicine in Treatment of Gastric Cancer Based on Network Pharmacology, Molecular Docking, and Tumor Immune Infiltration Analysis

2022 ◽  
Vol 2022 ◽  
pp. 1-21
Author(s):  
Jiamin Xu ◽  
Fuqin Kang ◽  
Wei Wang ◽  
Shujun Liu ◽  
Jianhui Xie ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Molecular Docking ◽  
Energy Analysis ◽  
Kegg Pathway ◽  
Network Pharmacology ◽  
Important Ingredient ◽  
Immune Infiltration ◽  
Pharmacological Mechanism ◽  
Target Network ◽  
Binding Energy Analysis

Background. Clinical research found that TCM is therapeutic in treating gastric cancer. Clearing heat is the most common method, while some antirheumatic medicines are widely used in treatment as well. To explore the pharmacological mechanism, we researched the comparison between heat-clearing medicine and antirheumatic medicine in treating gastric cancer. Methods. First, related ingredients and targets were searched, respectively, and are shown in an active ingredient-target network. Combining the relevant targets of gastric cancer, we constructed a PPI network and MCODE network. Then, GO and KEGG enrichment analyses were conducted. Molecular docking experiments were performed to verify the affinity of targets and ligands. Finally, we analyzed the tumor immune infiltration on gene expression, somatic CNA, and clinical outcome. Results. A total of 31 ingredients and 90 targets of heat-clearing medicine, 31 ingredients and 186 targets of antirheumatic medicine, and 12,155 targets of gastric cancer were collected. Antirheumatic medicine ranked the top in all the enrichment analyses. In the KEGG pathway, both types of medicines were related to pathways in cancer. In the KEGG map, AR, MMP2, ERBB2, and TP53 were the most crucial targets. Key targets and ligands were docked with low binding energy. Analysis of tumor immune infiltration showed that the expressions of AR and ERBB2 were correlated with the abundance of immune infiltration and made a difference in clinical outcomes. Conclusions. Quercetin is an important ingredient in both heat-clearing medicine and antirheumatic medicine. AR signaling pathway exists in both types of medicines. The mechanism of the antitumor effect in antirheumatic medicine was similar to trastuzumab, a targeted drug aimed at ERBB2. Both types of medicines were significant in tumor immune infiltration. The immunology of gastric tumor deserves further research.

scholarly journals Based on network pharmacology and molecular docking to explore the Traditional Chinese Medicine anti-influenza mechanisms:Chinese protocol for diagnosis and treatment of influenza.

2020 ◽  
Author(s):  
yifei Chen
Keyword(s):  
Molecular Docking ◽  
Influenza A ◽  
Influenza Infection ◽  
Diagnosis And Treatment ◽  
Network Pharmacology ◽  
Ppi Network ◽  
Active Components ◽  
Pharmacological Mechanism ◽  
Severe Influenza ◽  
Target Network

Background Explore the possible mechanism of anti-influenza virus, based on the study of the active components-drug-target network, Protein-Protein Interaction (PPI) network and molecular docking verification, we explored the potential action mechanism of TCM in Chinese protocol for diagnosis and treatment of influenza 2019. Methods Screening the active components and potential targets of 12 drugs in the scheme by using TCMSP database, and Obtaining the target of influenza by GeneCard, Durgbank, OMIM, TTD and PharmGkb databases. Then, constructed the “component-durg-target” network and PPI network were by Cytoscape3.8.0 software. Morethan, analyzed and the biological function and pathway, verified the molecular docking by AutoDock Vina software. Results The 12 drugs in the recommended scheme (XBCQ) for severe influenza contain 192 active components and involve 31 key antiviral targets, which may play an antiviral role through biological processes such as lipopolysaccharide, pathogen molecular reaction and regulate signaling pathway via the IL-17, influenza A, TNF, Toll-like receptors. Conclusion TCM play critical therapeutic roles through “multi-components, multi-targets and multi-pathways” mechanisms in influenza infection. The antiviral pharmacological mechanism of Xuanbai Chengqi decoction, which was analyzed by network pharmacology and molecular docking, provide a new idea for further exploring the diagnosis and treatment of severe influenza.

scholarly journals Molecular mechanism underlying the hypolipidemic effect of Shanmei Capsule based on network pharmacology and molecular docking

2021 ◽  
Vol 29 ◽  
pp. 239-256
Author(s):  
Qian Wang ◽  
Lijing Du ◽  
Jiana Hong ◽  
Zhenlin Chen ◽  
Huijian Liu ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Signaling Pathway ◽  
Molecular Mechanism ◽  
Kegg Pathway ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Signal Pathways ◽  
Hypolipidemic Effect ◽  
Active Ingredients ◽  
Pathway Enrichment

BACKGROUND: Shanmei Capsule is a famous preparation in China. However, the related mechanism of Shanmei Capsule against hyperlipidemia has yet to be revealed. OBJECTIVE: To elucidate underlying mechanism of Shanmei Capsule against hyperlipidemia through network pharmacology approach and molecular docking. METHODS: Active ingredients, targets of Shanmei Capsule as well as targets for hyperlipidemia were screened based on database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were performed via Database for Annotation, Visualization, and Integrated Discovery (DAVID) 6.8 database. Ingredient-target-disease-pathway network was visualized utilizing Cytoscape software and molecular docking was performed by Autodock Vina. RESULTS: Seventeen active ingredients in Shanmei Capsule were screened out with a closely connection with 34 hyperlipidemia-related targets. GO analysis revealed 40 biological processes, 5 cellular components and 29 molecular functions. A total of 15 signal pathways were enriched by KEGG pathway enrichment analysis. The docking results indicated that the binding activities of key ingredients for PPAR-α are equivalent to that of the positive drug lifibrate. CONCLUSIONS: The possible molecular mechanism mainly involved PPAR signaling pathway, Bile secretion and TNF signaling pathway via acting on MAPK8, PPARγ, MMP9, PPARα, FABP4 and NOS2 targets.

scholarly journals The Underlying Mechanism of Chinese Herb of Regulating Marrow in the Treatment of  Osteonecrosis of the Femoral Head Based on Network Pharmacology and Molecular Docking

2021 ◽  
Author(s):  
Xiaojian Wang ◽  
Rui Wang ◽  
Ting Xu ◽  
Hongting Jin ◽  
Peijian Tong ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Chinese Medicine ◽  
Signaling Pathway ◽  
Kegg Pathway ◽  
Enrichment Analysis ◽  
Underlying Mechanism ◽  
Chinese Herbs ◽  
Network Pharmacology ◽  
Active Components ◽  
Pathway Enrichment

Abstract Background The lesion of marrow is a crucial factor in orthopedic diseases, which is recognized by orthopedics-traumatology expert from "Zhe-School of Chinese Medicine". The Chinese herbs of regulating marrow has been widely used to treat osteonecrosis of the femoral head (ONFH) in China, while the interaction mechanisms were still elucidated. Thus, we conducted this study to explore the underlying mechanism of the five highest-frequency Chinese herbs of regulating marrow(HF-CHRM) in the treatment of ONFH with the aid of network pharmacology(NP) and molecular docking(MD). Methods The active components and potential targets of HF-CHRM were obtained through several online databases, such as Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCMSP), UniProt database. The gene targets related to ONFH were collected with the help of the OMIM and GeneCards disease-related databases. The "drug- component-target-disease" network and protein-protein interaction(PPI) network of the drug and disease intersecting targets were constructed by using Cytoscape software and the STRING database. R software was used for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. The MD of critical components and targets was carried out using Autodock Vina and Pymol to validate the binding affinity. Results A total of 54 active components, 1074 drug targets and 195 gene targets were obtained. There were 1219 ONFH related targets. 39 drug and disease intersection targets(representative genes: IL6, TP53, VEGFA, ESR1, IL1B) were obtained and considered potential therapeutic targets. 1619 items were obtained by the GO enrichment analysis, including 1517 biological processes, 10 cellular components and 92 molecular functions, which is mainly related to angiogenesis, bone and lipid metabolism and inflammatory reaction. The KEGG pathway enrichment analysis revealed 119 pathways, including AGE-RAGE signaling pathway, PI3K-Akt signaling pathway and IL-17 signaling pathway. MD results showed that quercetin, wogonin, and kaempferol active components had good affinity with IL6, TP53, and VEGFA core proteins. Conclusion The HF-CHRM can treat ONFH by multi-component, multi-target, and multi-pathway comprehensive action.

scholarly journals Mechanisms of Compound Kushen Injection for the Treatment of Lung Cancer Based on Network Pharmacology

2019 ◽  
Vol 2019 ◽  
pp. 1-15 ◽  
Author(s):  
Ziqi Meng ◽  
Xinkui Liu ◽  
Jiarui Wu ◽  
Wei Zhou ◽  
Kaihuan Wang ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Molecular Docking ◽  
Small Cell Lung Cancer ◽  
Docking Simulation ◽  
Small Cell ◽  
Network Pharmacology ◽  
Small Cell Lung ◽  
Molecular Docking Simulation ◽  
Target Network ◽  
Compound Kushen Injection

Background. Compound Kushen Injection (CKI) is a Chinese patent drug that shows good efficacy in treating lung cancer (LC). However, its underlying mechanisms need to be further clarified.Methods. In this study, we adopted a network pharmacology method to gather compounds, predict targets, construct networks, and analyze biological functions and pathways. Moreover, molecular docking simulation was employed to assess the binding potential of selected target-compound pairs.Results. Four networks were established, including the compound-putative target network, protein-protein interaction (PPI) network of LC targets, compound-LC target network, and herb-compound-target-pathway network. Network analysis showed that 8 targets (CHRNA3, DRD2, PRKCA, CDK1, CDK2, CHRNA5, MMP1, and MMP9) may be the therapeutic targets of CKI in LC. In addition, molecular docking simulation indicated that CHRNA3, DRD2, PRKCA, CDK1, CDK2, MMP1, and MMP9 had good binding activity with the corresponding compounds. Furthermore, enrichment analysis indicated that CKI might exert a therapeutic role in LC by regulating some important pathways, namely, pathways in cancer, proteoglycans in cancer, PI3K-Akt signaling pathway, non-small-cell lung cancer, and small cell lung cancer.Conclusions. This study validated and predicted the mechanism of CKI in treating LC. Additionally, this study provides a good foundation for further experimental studies and promotes the reasonable application of CKI in the clinical treatment of LC.

scholarly journals Mechanism of Action of Bu-Fei-Yi-Shen Formula in Treating Chronic Obstructive Pulmonary Disease Based on Network Pharmacology Analysis and Molecular Docking Validation

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Longchuan Wu ◽  
Yu Chen ◽  
Jiao Yi ◽  
Yi Zhuang ◽  
Lei Cui ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Mechanism Of Action ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Chronic Obstructive ◽  
Biological Functions ◽  
Active Ingredients ◽  
Obstructive Pulmonary Disease ◽  
The Core ◽  
Target Network

Objective. To explore the mechanism of action of Bu-Fei-Yi-Shen formula (BFYSF) in treating chronic obstructive pulmonary disease (COPD) based on network pharmacology analysis and molecular docking validation. Methods. First of all, the pharmacologically active ingredients and corresponding targets in BFYSF were mined by the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database, the analysis platform, and literature review. Subsequently, the COPD-related targets (including the pathogenic targets and known therapeutic targets) were identified through the TTD, CTD, DisGeNet, and GeneCards databases. Thereafter, Cytoscape was employed to construct the candidate component-target network of BFYSF in the treatment of COPD. Moreover, the cytoHubba plug-in was utilized to calculate the topological parameters of nodes in the network; then, the core components and core targets of BFYSF in the treatment of COPD were extracted according to the degree value (greater than or equal to the median degree values for all nodes in the network) to construct the core network. Further, the Autodock vina software was adopted for molecular docking study on the core active ingredients and core targets, so as to verify the above-mentioned network pharmacology analysis results. Finally, the Omicshare database was applied in enrichment analysis of the biological functions of core targets and the involved signaling pathways. Results. In the core component-target network of BFYSF in treating COPD, there were 30 active ingredients and 37 core targets. Enrichment analysis suggested that these 37 core targets were mainly involved in the regulation of biological functions, such as response to biological and chemical stimuli, multiple cellular life processes, immunity, and metabolism. Besides, multiple pathways, including IL-17, Toll-like receptor (TLR), TNF, and HIF-1, played certain roles in the effect of BFYSF on treating COPD. Conclusion. BFYSF can treat COPD through the multicomponent, multitarget, and multipathway synergistic network, which provides basic data for intensively exploring the mechanism of action of BFYSF in treating COPD.

scholarly journals Network Pharmacology Identifies the Mechanisms of Action of Tongxie Anchang Decoction in the Treatment of Irritable Bowel Syndrome with Diarrhea Predominant

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Xiang Tan ◽  
Wenjing Pei ◽  
Chune Xie ◽  
Zhibin Wang ◽  
Tangyou Mao ◽  
...  
Keyword(s):  
Irritable Bowel Syndrome ◽  
Target Genes ◽  
Alternative Therapy ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Active Compounds ◽  
Complementary And Alternative Therapy ◽  
Pharmacological Mechanism ◽  
Target Network ◽  
Irritable Bowel

Aim. This study aims to uncover the pharmacological mechanism of Tongxie Anchang Decoction (TXACD), a new and effective traditional Chinese medicine (TCM) prescription, for treating irritable bowel syndrome with diarrhea predominant (IBS-D) using network pharmacology. Methods. The active compounds and putative targets of TXACD were retrieved from TCMSP database and published literature; related target genes of IBS-D were retrieved from GeneCards; PPI network of the common target hub gene was constructed by STRING. Furthermore, these hub genes were analyzed using gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Results. A total of 54 active compounds and 639 targets were identified through a database search. The compound-target network was constructed, and the key compounds were screened out according to the degree. By using the PPI and GO and KEGG enrichment analyses, the pharmacological mechanism network of TXACD in the treatment of IBS-D was constructed. Conclusions. This study revealed the possible mechanisms by which TXACD treatment alleviated IBS-D involvement in the modulation of multiple targets and multiple pathways, including the immune regulation, inflammatory response, and oxidative stress. These findings provide novel insights into the regulatory role of TXACD in the prevention and treatment of IBS-D and hold promise for herb-based complementary and alternative therapy.

scholarly journals Network Pharmacology-Based Study on the Mechanism of Aloe Vera for Treating Cancer

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Jing Xie ◽  
Jun Wu ◽  
Sihui Yang ◽  
Huaijun Zhou
Keyword(s):  
Molecular Docking ◽  
Drug Targets ◽  
Aloe Vera ◽  
Beta Carotene ◽  
Network Pharmacology ◽  
Potential Mechanism ◽  
Active Ingredients ◽  
Protein Protein Interaction ◽  
Target Network ◽  
Molecule Docking

Background. Aloe vera has long been considered an anticancer herb in different parts of the world. Objective. To explore the potential mechanism of aloe vera in the treatment of cancer using network pharmacology and molecule docking approaches. Methods. The active ingredients and corresponding protein targets of aloe vera were identified from the TCMSP database. Targets related to cancer were obtained from GeneCards and OMIM databases. The anticancer targets of aloe vera were obtained by intersecting the drug targets with the disease targets, and the process was presented in the form of a Venn plot. These targets were uploaded to the String database for protein-protein interaction (PPI) analysis, and the result was visualized by Cytoscape software. Go and KEGG enrichment were used to analyze the biological process of the target proteins. Molecular docking was used to verify the relationship between the active ingredients of aloe vera and predicted targets. Results. By screening and analyzing, 8 active ingredients and 174 anticancer targets of aloe vera were obtained. The active ingredient-anticancer target network constructed by Cytoscape software indicated that quercetin, arachidonic acid, aloe-emodin, and beta-carotene, which have more than 4 gene targets, may play crucial roles. In the PPI network, AKT1, TP53, and VEGFA have the top 3 highest values. The anticancer targets of aloe vera were mainly involved in pathways in cancer, prostate cancer, bladder cancer, pancreatic cancer, and non-small-cell lung cancer and the TNF signaling pathway. The results of molecular docking suggested that the binding ability between TP53 and quercetin was the strongest. Conclusion. This study revealed the active ingredients of aloe vera and the potential mechanism underlying its anticancer effect based on network pharmacology and provided ideas for further research.

scholarly journals Elucidation of the mechanism of action of the anticholecystitis effect of the Tibetan medicine “Dida” using network pharmacology

2020 ◽  
Vol 19 (7) ◽  
pp. 1449-1457
Author(s):  
Chuan Liu ◽  
Fang-Fang Fan ◽  
Xuan-Hao Li ◽  
Wen-Xiang Wang ◽  
Ya Tu ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Bioactive Compounds ◽  
Kegg Pathway ◽  
Docking Simulation ◽  
Cell Receptor ◽  
Mapk Signaling ◽  
Tibetan Medicine ◽  
Network Pharmacology ◽  
Molecular Docking Simulation ◽  
Pathway Network

Purpose: To study the mechanism involved in the anti-cholecystitis effect the Tibetan medicine “Dida”, using network pharmacology-integrated molecular docking simulationsMethods: In this investigation, the bioactive compounds of Dida were collected, network pharmacology methods to predict their targets, and networks were constructed through GO and KEGG pathway analyses. The potential binding between the bioactive compounds and the targets were demonstrated using molecular docking simulations.Results: A total of 12 bioactive compounds and 50 key targets of Dida were identified. Two networks, namely, protein–protein interaction (PPI) network of cholecystitis targets, and compound–target– pathway network, were established. Network analysis showed that 10 targets (GAPDH, AKT1, CASP3, EGFR, TNF, MAPK3, MAPK1, HSP90AA1, STAT3, and BCL2L1) may be the therapeutic targets of Dida in cholecystitis. Analysis of the KEGG pathway indicated that the anti-cholecystitis effect of Dida may its regulation of a few crucial pathways, such as apoptosis, as well as toll-like  receptor, T cell receptor, NOD-like receptor, and MAPK signaling pathways. Furthermore, molecular docking simulation revealed that CASP3, CAPDH, HSP90AA1, MAPK3, MAPK1, and STAT3 had well-characterized interactions with the corresponding compounds.Conclusion: The mechanism underlying the anti-cholecystitis effect of Dida has been successfully predicted and verified using a combination of network pharmacology and molecular docking simulation. This provides a firm basis for the experimental verification of the use of Dida in the treatment of cholecystitis, and enhances its rational application in clinical practice. Keywords: Tibetan medicine, Dida, Cholecystitis, Mechanism, Network pharmacology, Molecular docking simulation

scholarly journals Mechanism of Fei-Xian Formula in the Treatment of Pulmonary Fibrosis on the Basis of Network Pharmacology Analysis Combined with Molecular Docking Validation

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Xiao-Li Chen ◽  
Cheng Tang ◽  
Qing-Ling Xiao ◽  
Zhong-Hua Pang ◽  
Dan-Dan Zhou ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Virus Infection ◽  
Pulmonary Fibrosis ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Core Network ◽  
Active Ingredients ◽  
Molecular Docking Study ◽  
The Core ◽  
Target Network

Objective. This study aimed to clarify the mechanism of Fei-Xian formula (FXF) in the treatment of pulmonary fibrosis based on network pharmacology analysis combined with molecular docking validation. Methods. Firstly, ingredients in FXF with pharmacological activities, together with specific targets, were identified based on the BATMA-TCM and TCMSP databases. Then, targets associated with pulmonary fibrosis, which included pathogenic targets as well as those known therapeutic targets, were screened against the CTD, TTD, GeneCards, and DisGeNet databases. Later, Cytoscape was employed to construct a candidate component-target network of FXF for treating pulmonary fibrosis. In addition, for nodes within the as-constructed network, topological parameters were calculated using CytoHubba plug-in, and the degree value (twice as high as the median degree value for all the nodes) was adopted to select core components as well as core targets of FXF for treating pulmonary fibrosis, which were subsequently utilized for constructing the core network. Furthermore, molecular docking study was carried out on those core active ingredients together with the core targets using AutoDock Vina for verifying results of network pharmacology analysis. At last, OmicShare was employed for enrichment analysis of the core targets. Results. Altogether 12 active ingredients along with 13 core targets were identified from our constructed core component-target network of FXF for the treatment of pulmonary fibrosis. As revealed by enrichment analysis, the 13 core targets mostly concentrated in regulating biological functions, like response to external stimulus (from oxidative stress, radiation, UV, chemical substances, and virus infection), apoptosis, cell cycle, aging, immune process, and protein metabolism. In addition, several pathways, like IL-17, AGE-RAGE, TNF, HIF-1, PI3K-AKT, NOD-like receptor, T/B cell receptor, and virus infection-related pathways, exerted vital parts in FXF in the treatment of pulmonary fibrosis. Conclusions. FXF can treat pulmonary fibrosis through a “multicomponent, multitarget, and multipathway” mean. Findings in this work lay foundation for further exploration of the FXF mechanism in the treatment of pulmonary fibrosis.

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