scholarly journals Exploring the Biological Mechanism of Huang Yam in Treating Tumors and Preventing Antitumor Drug-Induced Cardiotoxicity Using Network Pharmacology and Molecular Docking Technology

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Hui Zhang ◽  
Wenchao Dan ◽  
Qingyong He ◽  
Jianbo Guo ◽  
Shuang Dai ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Antitumor Drugs ◽  
Network Pharmacology ◽  
Chemical Components ◽  
Active Ingredients ◽  
Drug Induced ◽  
Anticancer Properties ◽  
The Core

Drugs for the treatment of tumors could result in cardiotoxicity and cardiovascular diseases. We aimed to explore the anticancer properties of Huang yam as well as its cardioprotective properties using network pharmacology and molecular docking technology. The cardiovascular targets of the major chemical components of Huang yam were obtained from the following databases: TCMSP, ETCM, and BATMAN-TCM. The active ingredients of Huang yam were obtained from SwissADME. The cardiovascular targets of antitumor drugs were obtained using GeneCards, OMIM, DrugBank, DisGeNET, and SwissTargetPrediction databases. The drug-disease intersection genes were used to construct a drug-compound-target network using Cytoscape 3.7.1. A protein-protein interaction network was constructed using Cytoscape’s BisoGenet, and the core targets of Huang yam were screened to determine their antitumor properties and identify the cardiovascular targets based on topological parameters. Potential targets were imported into the Metascape platform for GO and KEGG analysis. The results were saved and visualized using R software. The components with higher median values in the network were molecularly docked with the core targets. The network contained 10 compounds, including daucosterol, delusive, dioxin, panthogenin-B, and 124 targets, such as TP53, RPS27A, and UBC. The GO function enrichment analysis showed that there were 478 items in total. KEGG enrichment analysis showed a total of 140 main pathways associated with abnormal transcription of cancer, PI3K-Akt signaling pathway, cell cycle, cancer pathway, ubiquitination-mediated proteolysis, and other pathways. Molecular docking results showed that daucosterol, delusive, dioxin, and panthogenin-B had the highest affinity for TP53, RPS27A, and UBC. The treatment of diseases using traditional Chinese medicine encompasses multiple active ingredients, targets, and pathways. Huang yam has the potential to treat cardiotoxicity caused by antitumor drugs.

scholarly journals Mechanism of Compound Houttuynia Mixture as an Anti-COVID-19 Drug Based on Network Pharmacology and Molecular Docking

2021 ◽  
Vol 16 (5) ◽  
pp. 1934578X2110167
Author(s):  
Xing-Pan Wu ◽  
Tian-Shun Wang ◽  
Zi-Xin Yuan ◽  
Yan-Fang Yang ◽  
He-Zhen Wu
Keyword(s):  
Molecular Docking ◽  
Target Prediction ◽  
Interaction Network ◽  
Scientific Basis ◽  
Network Pharmacology ◽  
Chemical Components ◽  
Active Components ◽  
Discovery Studio ◽  
The Core ◽  
Pathway Annotation

Objective To explore the anti-COVID-19 active components and mechanism of Compound Houttuynia mixture by using network pharmacology and molecular docking. Methods First, the main chemical components of Compound Houttuynia mixture were obtained by using the TCMSP database and referring to relevant chemical composition literature. The components were screened for OB ≥30% and DL ≥0.18 as the threshold values. Then Swiss Target Prediction database was used to predict the target of the active components and map the targets of COVID-19 obtained through GeneCards database to obtain the gene pool of the potential target of COVID-19 resistance of the active components of Compound Houttuynia mixture. Next, DAVID database was used for GO enrichment and KEGG pathway annotation of targets function. Cytoscape 3.8.0 software was used to construct a “components-targets-pathways” network. Then String database was used to construct a “protein-protein interaction” network. Finally, the core targets, SARS-COV-2 3 Cl, ACE2 and the core active components of Compound Houttuyna Mixture were imported into the Discovery Studio 2016 Client database for molecular docking verification. Results Eighty-two active compounds, including Xylostosidine, Arctiin, ZINC12153652 and ZINC338038, were screened from Compound Houttuyniae mixture. The key targets involved 128 targets, including MAPK1, MAPK3, MAPK8, MAPK14, TP53, TNF, and IL6. The HIF-1 signaling, VEGF signaling, TNF signaling and another 127 signaling pathways associated with COVID-19 were affected ( P < 0.05). From the results of molecular docking, the binding ability between the selected active components and the core targets was strong. Conclusion Through the combination of network pharmacology and molecular docking technology, this study revealed that the therapeutic effect of Compound Houttuynia mixture on COVID-19 was realized through multiple components, multiple targets and multiple pathways, which provided a certain scientific basis of the clinical application of Compound Houttuynia mixture.

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 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.

scholarly journals A Network Pharmacology Approach and Molecular Docking Technology to Uncover the Potential Molecular Mechanism of Astragalus -Scorpion on Prostate Cancer

2021 ◽  
Author(s):  
Litong Wu ◽  
Ying Chen ◽  
Mingjing Chen ◽  
Yueqin Yang ◽  
Zuzhao Che ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Molecular Docking ◽  
Active Ingredient ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Active Ingredients ◽  
Disease Network ◽  
The Core ◽  
Target Disease ◽  
The Common

Abstract Objective: To investigate the molecular mechanism of Astragalus-Scorpion in the treatment of prostate cancer by network pharmacology and molecular docking technology.Methods: Using TCMSP, BATMAN-TCM, TCMID and Swiss TargetPrediction Databases to retrieve the active ingredients and corresponding targets of Astragalus-Scorpion. The targets related to prostate cancer were retrieved through GeneCards, so as to obtain the common targets of Astragalus-Scorpion and prostate cancer. The common targets were input into the STRING database for protein interaction analysis. Cytoscape software was used to construct the active “ingredient-target-disease” network, and GO and KEGG enrichment analysis were performed on the common targets. To screen the core ingredients and targets that play therapeutic roles, Autodock software was used for molecular docking verification. Results: 27 active ingredients, 340 potential targets related to active ingredients, 898 targets related to disease and 122 common targets were screened from Astragalus-Scorpion totally. The core targets of PPI network were JUN, AKT1, IL6, MAPK1 and RELA, while the core active ingredients in the active ingredient-target-disease network were quercetin, kaempferol, formononetin, 7-o-methylisomucronulatol and calycosin.762 GO entries and 154 pathways were obtained by enrichment analysis totally. The molecular docking results showed that quercetin binds to AKT1 and RELA, kaempferol to AKT1, and formononetin to RELA, all of which were stable. Conclusion: Quercetin, kaempferol and others in the Astragalus-Scorpion can regulate multiple signaling pathways such as PI3K-Akt signaling pathway by binding to targets such as AKT1 related to prostate cancer, inhibit the proliferation of tumor to play a role for prostate cancer.

scholarly journals Decoding the Mechanism of Huanglian Jiedu Decoction in Treating Pneumonia Based on Network Pharmacology and Molecular Docking

2021 ◽  
Vol 9 ◽  
Author(s):  
Xianhai Li ◽  
Hua Tang ◽  
Qiang Tang ◽  
Wei Chen
Keyword(s):  
Molecular Docking ◽  
Signaling Pathway ◽  
Molecular Mechanisms ◽  
Clinical Symptoms ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Interleukin 17 ◽  
Active Ingredients ◽  
Hub Genes

Huang-Lian-Jie-Du decoction (HLJDD) has been used to treat pneumonia for thousands of years in China. However, our understanding of its mechanisms on treating pneumonia is still unclear. In the present work, network pharmacology was used to analyze the potential active ingredients and molecular mechanisms of HLJDD on treating pneumonia. A total of 102 active ingredients were identified from HLJDD, among which 54 were hit by the 69 targets associated with pneumonia. By performing Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, we obtained the main pathways associated with pneumonia and those associated with the mechanism of HLJDD in the treatment of pneumonia. By constructing the protein–protein interaction network of common targets, 10 hub genes were identified, which were mainly involved in the tumor necrosis factor (TNF) signaling pathway, interleukin 17 (IL-17) signaling pathway, and nucleotide-binding oligomerization domain (NOD)-like receptor signaling pathway. Moreover, the results of molecular docking showed that the active ingredients of HLJDD had a good affinity with the hub genes. The final results indicate that HLJDD has a greater effect on bacterial pneumonia than on viral pneumonia. The therapeutic effect is mainly achieved by regulating the host immune inflammatory response and oxidative stress reaction, antibacterial microorganisms, alleviating the clinical symptoms of pneumonia, repairing damaged cells, and inhibiting cell migration.

scholarly journals Uncovering the Mechanism of Ge-Gen-Qin-Lian Decoction for Treating Ulcerative Colitis Based on Network Pharmacology and Molecular Docking Verification

2020 ◽  
Author(s):  
Lin Xu ◽  
Jiaqi Zhang ◽  
Zedan Zhang ◽  
Yifan Wang ◽  
Fengyun Wang ◽  
...  
Keyword(s):  
Ulcerative Colitis ◽  
Molecular Docking ◽  
Kegg Pathway ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Underlying Mechanism ◽  
Network Pharmacology ◽  
Active Ingredients ◽  
Hub Genes ◽  
Pathway Analyses

Abstract Background and objective: Ge-Gen-Qin-Lian Decoction (GGQLD), a traditional Chinese medicine (TCM) formula, has been widely used for ulcerative colitis (UC) in China while the pharmacological mechanisms still remain unclear. The present research was designed to clarify the underlying mechanism of GGQD against UC. Methods: In this research, a GGQLD-compound-target-UC (G-U) network was constructed based on public databases to clarify the relationship between active compounds in GGQLD and potential targets. GO and KEGG pathway enrichment analyses were performed to investigate biological functions associated with potential targets. A protein-protein interaction network was constructed to screen and evaluate hub genes and key active ingredients, another GO and KEGG pathway analyses were subsequently performed on hub genes. Molecular docking was used to verify the activities of binding between hub targets and ingredients. Results: Finally, 83 potential therapeutic targets and 118 correspond active ingredients were obtained by network pharmacology. GO and KEGG enrichment analysis revealed that GGQLD had an effect of anti-inflammation, antioxidation, and immunomodulatory. The effect of GGQLD on UC might be achieved by regulating the balance of cytokines (eg., IL6, TNF, IL1β, CXCL8, CCL2, IL10, IL4, IL2) in immune system and inflammation-related pathways, such as IL-17 pathway and Th17 cell differentiation pathway. Besides, molecular docking results demonstrated that the main active ingredients, quercetin, exhibited good affinity to hub targets. Conclusion: This research fully reflects the characteristics of multi-component and multi-target for GGQLD in the treatment of UC. Furthermore, the present study provided new insight into the mechanisms of GGQLD against UC.

scholarly journals The Potential Effect of Rhizoma coptidis on Polycystic Ovary Syndrome Based on Network Pharmacology and Molecular Docking

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Liyun Duan ◽  
De Jin ◽  
Xuedong An ◽  
Yuehong Zhang ◽  
Shenghui Zhao ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Polycystic Ovary ◽  
Enrichment Analysis ◽  
Potential Effect ◽  
Network Pharmacology ◽  
Receptor Interaction ◽  
Core Network ◽  
Active Ingredients ◽  
Rhizoma Coptidis ◽  
The Core

Background. Rhizoma coptidis (RC) showed a significant effect on PCOS, but its mechanism in PCOS remains unclear. Methods. The components of RC were searched by TCMSP. The Smiles number of the active ingredients was queried through PubChem, and the predicted targets were obtained from the SwissTargetPrediction database. The DrugBank, GeneCards, and DisGeNET databases were retrieved to acquire the related targets of PCOS. Then, the network of compound-target was constructed. The core targets were analyzed using protein-protein interaction (PPI) analysis, and the binding activities were verified by molecular docking. The enriched pathways of key targets were examined by GO and KEGG. Results. 13 components and 250 targets of RC on PCOS were screened. The core network was filtered based on topological parameters, and the key components were palmatine, berberine, berberrubine, quercetin, and epiberberine. The key targets included DRD2, SLC6A4, CDK2, DPP4, ESR1, AKT2, PGR, and AKT1. Molecular docking displayed that the active ingredients of RC had good binding activities with potential targets of PCOS. After enrichment analysis, 30 functional pathways were obtained, including neuroactive ligand-receptor interaction, dopaminergic synapse, and cAMP signaling pathway. Conclusion. In summary, this study clarified the potential effect of RC on PCOS, which is helpful to provide references for clinical practice. It is also conducive to the secondary development of RC and its monomer components.

scholarly journals A Network Pharmacology Approach and Molecular Docking Technology to Uncover the Potential Molecular Mechanism of Astragalus -Scorpion on Prostate Cancer

2021 ◽  
Author(s):  
Litong Wu ◽  
Ying Chen ◽  
Minjing Chen ◽  
Yueqin Yang ◽  
Zuzhao Che ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Molecular Docking ◽  
Active Ingredient ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Active Ingredients ◽  
Disease Network ◽  
The Core ◽  
Target Disease ◽  
The Common

Abstract Objective: To investigate the molecular mechanism of Astragalus-Scorpion in the treatment of prostate cancer by network pharmacology and molecular docking technology. Methods: Using TCMSP, BATMAN-TCM, TCMID and Swiss TargetPrediction Databases to retrieve the active ingredients and corresponding targets of Astragalus-Scorpion. The targets related to prostate cancer were retrieved through GeneCards, so as to obtain the common targets of Astragalus-Scorpion and prostate cancer. The common targets were input into the STRING database for protein interaction analysis. Cytoscape software was used to construct the active “ingredient-target-disease” network, and GO and KEGG enrichment analysis were performed on the common targets. To screen the core ingredients and targets that play therapeutic roles, Autodock software was used for molecular docking verification. Results: 27 active ingredients, 340 potential targets related to active ingredients, 898 targets related to disease and 122 common targets were screened from Astragalus-Scorpion totally. The core targets of PPI network were JUN, AKT1, IL6, MAPK1 and RELA, while the core active ingredients in the active ingredient-target-disease network were quercetin, kaempferol, formononetin, 7-o-methylisomucronulatol and calycosin.762 GO entries and 154 pathways were obtained by enrichment analysis totally. The molecular docking results showed that quercetin binds to AKT1 and RELA, kaempferol to AKT1, and formononetin to RELA, all of which were stable. Conclusion: Quercetin, kaempferol and others in the Astragalus-Scorpion can regulate multiple signaling pathways such as PI3K-Akt signaling pathway by binding to targets such as AKT1 related to prostate cancer, inhibit the proliferation of tumor to play a role for prostate cancer.

scholarly journals The Study on the Mechanism of Hugan Tablets in Treating Drug-Induced Liver Injury Induced by Atorvastatin

2021 ◽  
Vol 12 ◽  
Author(s):  
Shujing Lv ◽  
Honghong Yu ◽  
Xinyue Liu ◽  
Xiaoyan Gao
Keyword(s):  
Molecular Docking ◽  
Liver Injury ◽  
Protein Interactions ◽  
Enrichment Analysis ◽  
Lipid Lowering ◽  
Network Pharmacology ◽  
Active Ingredients ◽  
Drug Induced ◽  
Literature Research ◽  
Drug Induced Liver Injury

Atorvastatin is a widely used lipid-lowering drug in the clinic. Research shows that taking long-term atorvastatin has the risk of drug-induced liver injury (DILI) in most patients. Hugan tablets, a commonly used drug for liver disease, can effectively lower transaminase and protect the liver. However, the underlying mechanism of Hugan tablets alleviating atorvastatin-induced DILI remains unclear. To address this problem, comprehensive chemical profiling and network pharmacology methods were used in the study. First, the strategy of “compound−single herb−TCM prescription” was applied to characterize the ingredients of Hugan tablets. Then, active ingredients and potential targets of Hugan tablets in DILI treatment were screened using network pharmacology, molecular docking, and literature research. In the end, the mechanism of Hugan tablets in treating atorvastatin-induced DILI was elucidated. The results showed that Hugan tablets can effectively alleviate DILI induced by atorvastatin in model rats, and 71 compounds were characterized from Hugan tablets. Based on these compounds, 271 potential targets for the treatment of DILI were predicted, and 10 key targets were chosen by characterizing protein–protein interactions. Then, 30 potential active ingredients were screened through the molecular docking with these 10 key targets, and their biological activity was explained based on literature research. Finally, the major 19 active ingredients of Hugan tablets were discovered. In addition, further enrichment analysis of 271 targets indicated that the PI3K-Akt, TNF, HIF-1, Rap1, and FoxO signaling pathways may be the primary pathways regulated by Hugan tablets in treating DILI. This study proved that Hugan tablets could alleviate atorvastatin-induced DILI through multiple components, targets, and pathways.

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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