scholarly journals Molecular Mechanism of Danxiong Tongmai Granules in Treatment of Coronary Heart Disease

2021 ◽  
Author(s):  
Jiahao Ye ◽  
Ruiping Yang ◽  
Zhixi Hu ◽  
Lin Li ◽  
Senjie Zhong ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Coronary Heart Disease ◽  
Heart Disease ◽  
Molecular Docking ◽  
Enrichment Analysis ◽  
Dynamics Simulation ◽  
Venn Diagram ◽  
Network Pharmacology ◽  
Ppi Network ◽  
Ligand Interaction

Abstract Background: Network pharmacology has been widely adopted for mechanistic studies of Traditional Chinese Medicines (TCM). The present study uses network pharmacology to investigate the main ingredients, targets and pathways of Danxiong Tongmai Granules (DXTMG) in the treatment of coronary heart disease (CHD). We aim to validate our findings using molecular docking and molecular dynamics simulations.Methods: TCM compounds and targets were identified via searches in the BATMAN-TCM database, and the GeneCards database were used to obtain the main target genes involved in CHD, We combined disease targets with the drug targets to identify common targets, and draw a Venn diagram to visualize the results. The "TCM-compound-target" network was plotted using Cytoscape 3.7.2 software and a protein-protein interaction (PPI) network was constructed using the STRING database from which core targets were obtained. Gene ontology (GO) function analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed for common drug-disease targets using R Version 4.0.4 (64 bit) software. Molecular docking of core protein-small molecule ligand interaction was modeled using AutoDock Vina software. A simulation of molecular dynamics was conducted for the optimal protein-ligand complex obtained by molecular docking using Amber18 software.Results: 162 potential targets of DXTMG involved in CHD were identified. These included INS, ALB, IL-6 and TNF according to PPI network studies. GO enrichment analysis identified a total of 3365 GO pathways, including 3049 biological process pathways (BP) concerned with the heart and circulatory system;109 cellular component (CC) pathways, including cation channels and membrane rafts and 207 molecular function (MF) pathways related to receptor ligands and activators. KEGG analysis revealed a total of 137 pathways (p<0.05), including those related to AGE-RAGE signaling associated with diabetic complications, fluid shear stress and atherosclerosis. Molecular docking revealed the highest binding energy for Neocryptotanshinone Ii (the key compound of DXTMG) and TNF. Molecular dynamics simulation indicated stable binding for TNF-Neocryptotanshinone Ii with strong hydrophobic interactions mediated predominantly by the hydrophobic residues, Leu279, Val280 and Phe278 plus hydrogen-bonding with Leu279.Conclusion: The present study reveals novel insights into the mechanism of DXTMG in treating CHD. DXTMG can influence oxidative stress、inflammation response and regulating cardiomyocytes, thereby reducing the occurrence and development of CHD.

scholarly journals A network pharmacology-based investigation on the bioactive ingredients and molecular mechanisms of Gelsemium elegans Benth against colorectal cancer

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Wancai Que ◽  
Maohua Chen ◽  
Ling Yang ◽  
Bingqing Zhang ◽  
Zhichang Zhao ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Molecular Dynamics ◽  
Molecular Docking ◽  
Molecular Dynamics Simulation ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Molecular Mechanism ◽  
Enrichment Analysis ◽  
Dynamics Simulation ◽  
Network Pharmacology

Abstract Background Colorectal cancer (CRC) remains one of the leading causes of cancer-related death worldwide. Gelsemium elegans Benth (GEB) is a traditional Chinese medicine commonly used for treatment for gastrointestinal cancer, including CRC. However, the underlying active ingredients and mechanism remain unknown. This study aims to explore the active components and the functional mechanisms of GEB in treating CRC by network pharmacology-based approaches. Methods Candidate compounds of GEB were collected from the Traditional Chinese Medicine@Taiwan, Traditional Chinese Medicines Integrated Database, Bioinformatics Analysis Tool for Molecular mechanism of Traditional Chinese Medicine, and published literature. Potentially active targets of compounds in GEB were retrieved from SwissTargetPrediction databases. Keywords “colorectal cancer”, “rectal cancer” and “colon cancer” were used as keywords to search for related targets of CRC from the GeneCards database, then the overlapped targets of compounds and CRC were further intersected with CRC related genes from the TCGA database. The Cytoscape was applied to construct a graph of visualized compound-target and pathway networks. Protein-protein interaction networks were constructed by using STRING database. The DAVID tool was applied to carry out Gene Ontology and Kyoto Encyclopedia of Genes and Genome pathway enrichment analysis of final targets. Molecular docking was employed to validate the interaction between compounds and targets. AutoDockTools was used to construct docking grid box for each target. Docking and molecular dynamics simulation were performed by Autodock Vina and Gromacs software, respectively. Results Fifty-three bioactive compounds were successfully identified, corresponding to 136 targets that were screened out for the treatment of CRC. Functional enrichment analysis suggested that GEB exerted its pharmacological effects against CRC via modulating multiple pathways, such as pathways in cancer, cell cycle, and colorectal cancer. Molecular docking analysis showed that the representative compounds had good affinity with the key targets. Molecular dynamics simulation indicated that the best hit molecules formed a stable protein-ligand complex. Conclusion This network pharmacology study revealed the multiple ingredients, targets, and pathways synergistically involved in the anti-CRC effect of GEB, which will enhance our understanding of the potential molecular mechanism of GEB in treatment for CRC and lay a foundation for further experimental research.

scholarly journals Based on Network Pharmacology to Explore the Molecular Mechanism of Buzhong Yiqi Decoction for the Treatment of Gastric Cancer

2021 ◽  
Author(s):  
Ruiping Yang ◽  
Xiaojing Lin ◽  
Chunhui Tao ◽  
Ruixue Jiang
Keyword(s):  
Gastric Cancer ◽  
Molecular Dynamics ◽  
Molecular Docking ◽  
Signaling Pathway ◽  
Molecular Mechanism ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Dynamics Simulation ◽  
Network Pharmacology ◽  
Active Ingredients

Abstract BackgroundBuzhong Yiqi Decoction (BZYQD) has been widely accepted as an alternative treatment for gastric cancer (GC) in China. The present study set out to determine the potential molecular mechanism of BZYQD in the treatment of GC by means of network pharmacology, molecular docking, and molecular dynamics simulation.MethodsThe potential active ingredients and targets of BZYQD were screened out through the Traditional Chinese Medicine Systems Pharmacology (TCMSP). GC-related targets were screened out through the GeneCards database, and the intersection targets of BZYQD and GC were obtained by using the Venn diagram online tool. Then, the TCM-Active Ingredient-Target network was constructed by using the Cytoscape, and the protein-protein interaction (PPI) network was constructed by using the STRING database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of the effective targets of BZYQD in GC were performed through the Metascape platform. Finally, the molecular docking between the compounds and the target proteins was performed by using the AutoDock Vina software. The simulation of molecular dynamics was conducted for the optimal protein-ligand complex obtained by molecular docking using the Amber18 software.ResultsA total of 150 active ingredients of BZYQD were retrieved, corresponding to 136 targets of GC. The key active ingredients were quercetin, kaempferol, nobiletin, naringenin, and formononetin. The core targets were AKT1, STAT3, TP53, MAPK1, and MAPK3. GO functional enrichment analysis showed that BZYQD treated GC by affecting various biological processes such as oxidative stress, chemical stress, lipopolysaccharide reaction, and apoptosis. KEGG pathway enrichment analysis indicated that the apoptosis signaling pathway, PI3K/Akt signaling pathway, proteoglycan in cancer, IL-17 signaling pathway, TNF signaling pathway, and HIF-1 signaling pathway were involved. Molecular docking results revealed the highest binding energy for MAPK3 and naringenin. The stable binding of MAPK3 and naringenin was also demonstrated in the molecular dynamics simulation test, with the binding free energy of -25kcal/mol.ConclusionThis study preliminarily revealed the multi-component, multi-target, and multi-pathway characteristics of BZYQD against GC, laying a scientific basis for further research on the molecular mechanism of BZYQD.

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

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Jiahao Ye ◽  
Lin Li ◽  
Zhixi Hu
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Mechanism Of Action ◽  
Core Protein ◽  
Enrichment Analysis ◽  
Dynamics Simulation ◽  
Network Pharmacology ◽  
Advanced Glycation ◽  
Active Ingredients ◽  
Glycation End Products

Background. 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. Methods. 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. Results. 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. Conclusion. This study is based on network pharmacology and reveals the potential molecular mechanisms involved in the treatment of hyperlipidemia by Yinchen Wuling powder.

Advancements in Docking and Molecular Dynamics Simulations Towards Ligand-receptor Interactions and Structure-function Relationships

2018 ◽  
Vol 18 (20) ◽  
pp. 1755-1768 ◽  
Author(s):  
Ahmad Abu Turab Naqvi ◽  
Taj Mohammad ◽  
Gulam Mustafa Hasan ◽  
Md. Imtaiyaz Hassan
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Drug Discovery ◽  
Molecular Dynamics Simulations ◽  
Computational Method ◽  
Dynamics Simulation ◽  
Ligand Molecule ◽  
Ligand Interaction ◽  
Modern Drug ◽  
Dynamics Simulations

Protein-ligand interaction is an imperative subject in structure-based drug design and protein function prediction process. Molecular docking is a computational method which predicts the binding of a ligand molecule to the particular receptor. It predicts the binding pose, strength and binding affinity of the molecules using various scoring functions. Molecular docking and molecular dynamics simulations are widely used in combination to predict the binding modes, binding affinities and stability of different protein-ligand systems. With advancements in algorithms and computational power, molecular dynamics simulation is now a fundamental tool to investigative bio-molecular assemblies at atomic level. These methods in association with experimental support have been of great value in modern drug discovery and development. Nowadays, it has become an increasingly significant method in drug discovery process. In this review, we focus on protein-ligand interactions using molecular docking, virtual screening and molecular dynamics simulations. Here, we cover an overview of the available methods for molecular docking and molecular dynamics simulations, and their advancement and applications in the area of modern drug discovery. The available docking software and their advancement including application examples of different approaches for drug discovery are also discussed. We have also introduced the physicochemical foundations of molecular docking and simulations, mainly from the perception of bio-molecular interactions.

scholarly journals Identification of Potential Herbal Inhibitor of Acetylcholinesterase Associated Alzheimer’s Disorders Using Molecular Docking and Molecular Dynamics Simulation

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Chandrabhan Seniya ◽  
Ghulam Jilani Khan ◽  
Kuldeep Uchadia
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Molecular Dynamics Simulations ◽  
Secondary Metabolite ◽  
Therapeutic Potential ◽  
Dynamics Simulation ◽  
Cholinesterase Inhibition ◽  
Ligand Molecule ◽  
Ligand Interaction ◽  
Dynamics Simulations

Cholinesterase inhibitors (ChE-Is) are the standard for the therapy of AD associated disorders and are the only class of approved drugs by the Food and Drug Administration (FDA). Additionally, acetylcholinesterase (AChE) is the target for many Alzheimer’s dementia drugs which block the function of AChE but have some side effects. Therefore, in this paper, an attempt was made to elucidate cholinesterase inhibition potential of secondary metabolite fromCannabisplant which has negligible or no side effect. Molecular docking of 500 herbal compounds, against AChE, was performed using Autodock 4.2 as per the standard protocols. Molecular dynamics simulations have also been carried out to check stability of binding complex in water for 1000 ps. Our molecular docking and simulation have predicted high binding affinity of secondary metabolite (C28H34N2O6) to AChE. Further, molecular dynamics simulations for 1000 ps suggest that ligand interaction with the residues Asp72, Tyr70-121-334, and Phe288 of AChE, all of which fall under active site/subsite or binding pocket, might be critical for the inhibitory activity of AChE. This approach might be helpful to understand the selectivity of the given drug molecule in the treatment of Alzheimer's disease. The study provides evidence for consideration ofC28H34N2O6as a valuable small ligand molecule in treatment and prevention of AD associated disorders and furtherin vitroandin vivoinvestigations may prove its therapeutic potential.

scholarly journals Molecular Mechanism of Gelsemium elegans (Gardner and Champ.) Benth. Against Neuropathic Pain Based on Network Pharmacology and Experimental Evidence

2022 ◽  
Vol 12 ◽  
Author(s):  
Wancai Que ◽  
Zhaoyang Wu ◽  
Maohua Chen ◽  
Binqing Zhang ◽  
Chuihuai You ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Neuropathic Pain ◽  
Molecular Dynamics Simulation ◽  
Experimental Evidence ◽  
Signaling Pathway ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Dynamics Simulation ◽  
Network Pharmacology ◽  
Holistic View

Gelsemium elegans (Gardner and Champ.) Benth. (Gelsemiaceae) (GEB) is a toxic plant indigenous to Southeast Asia especially China, and has long been used as Chinese folk medicine for the treatment of various types of pain, including neuropathic pain (NPP). Nevertheless, limited data are available on the understanding of the interactions between ingredients-targets-pathways. The present study integrated network pharmacology and experimental evidence to decipher molecular mechanisms of GEB against NPP. The candidate ingredients of GEB were collected from the published literature and online databases. Potentially active targets of GEB were predicted using the SwissTargetPrediction database. NPP-associated targets were retrieved from GeneCards, Therapeutic Target database, and DrugBank. Then the protein-protein interaction network was constructed. The DAVID database was applied to Gene Ontology and Kyoto Encyclopedia of Genes and Genome pathway enrichment analysis. Molecular docking was employed to validate the interaction between ingredients and targets. Subsequently, a 50 ns molecular dynamics simulation was performed to analyze the conformational stability of the protein-ligand complex. Furthermore, the potential anti-NPP mechanisms of GEB were evaluated in the rat chronic constriction injury model. A total of 47 alkaloids and 52 core targets were successfully identified for GEB in the treatment of NPP. Functional enrichment analysis showed that GEB was mainly involved in phosphorylation reactions and nitric oxide synthesis processes. It also participated in 73 pathways in the pathogenesis of NPP, including the neuroactive ligand-receptor interaction signaling pathway, calcium signaling pathway, and MAPK signaling pathway. Interestingly, 11-Hydroxyrankinidin well matched the active pockets of crucial targets, such as EGFR, JAK1, and AKT1. The 11-hydroxyrankinidin-EGFR complex was stable throughout the entire molecular dynamics simulation. Besides, the expression of EGFR and JAK1 could be regulated by koumine to achieve the anti-NPP action. These findings revealed the complex network relationship of GEB in the “multi-ingredient, multi-target, multi-pathway” mode, and explained the synergistic regulatory effect of each complex ingredient of GEB based on the holistic view of traditional Chinese medicine. The present study would provide a scientific approach and strategy for further studies of GEB in the treatment of NPP in the future.

scholarly journals Network Pharmacology and Molecular Docking-Based Analysis on Bioactive Anticoronary Heart Disease Compounds in Trichosanthes kirilowii Maxim and Bulbus allii Macrostemi

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Yi-Ding Yu ◽  
Wang-Jun Hou ◽  
Juan Zhang ◽  
Yi-Tao Xue ◽  
Yan Li
Keyword(s):  
Insulin Resistance ◽  
Heart Disease ◽  
Molecular Docking ◽  
Hypoxia Inducible Factor ◽  
Enrichment Analysis ◽  
Ethyl Linoleate ◽  
Arachidonic Acid Metabolism ◽  
Network Pharmacology ◽  
Active Compounds ◽  
Trichosanthes Kirilowii

Trichosanthes kirilowii Maxim. and Bulbus allii Macrostemi are the components of Gualou Xiebai decoction (GLXB), a commonly used herbal combination for the treatment of coronary heart disease (CHD) in traditional Chinese medicine. Although GLXB is associated with a good clinical effect, its active compounds and mechanism of action remain unclear, which limits its clinical application and the development of novel drugs. In this study, we explored key compounds, targets, and mechanisms of action for GLXB in the treatment of CHD using the network pharmacology approach. We identified 18 compounds and 21 action targets via database screening. Enrichment analysis indicated that the effects of GLXB in patients with CHD are primarily associated with the regulation of signalling pathways for tumour necrosis factor, nuclear factor-kappa B, hypoxia-inducible factor-1, arachidonic acid metabolism, and insulin resistance. GLXB thus exerts anti-inflammatory, antihypoxic, and antiagglutinating effects; regulates lipid metabolism; and combats insulin resistance in CHD via these pathways, respectively. After reverse targeting, we observed that the main active compounds of GLXB in the treatment of CHD were quercetin, naringenin, β-sitosterol, ethyl linolenate, ethyl linoleate, and prostaglandin B1. To explore the potential of these compounds in the treatment of CHD, we verified the affinity of the compounds and targets via molecular docking analysis. Our study provides a bridge for the transformation of natural herbs and molecular compounds into novel drug therapies for CHD.

scholarly journals Identifying a Serum Exosomal-Associated lncRNA/circRNA-miRNA-mRNA Network in Coronary Heart Disease

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Jia Mao ◽  
Yufei Zhou ◽  
Licheng Lu ◽  
Ping Zhang ◽  
Runhua Ren ◽  
...  
Keyword(s):  
Coronary Heart Disease ◽  
Heart Disease ◽  
Regulation Of Gene Expression ◽  
Enrichment Analysis ◽  
Cellular Protein ◽  
Functional Enrichment ◽  
Ppi Network ◽  
Hub Genes ◽  
Cerna Network ◽  
Normal Controls

Background. Accumulating evidence supports the importance of noncoding RNAs and exosomes in coronary heart disease (CHD). However, exosomal-associated competing endogenous RNA- (ceRNA-) mediated regulatory mechanisms in CHD are largely unexplored. The present study aimed to explore exosomal-associated ceRNA networks in CHD. Methods. Data from 6 CHD patients and 32 normal controls were downloaded from the ExoRBase database. CHD and normal controls were compared by screening differentially expressed mRNAs (DEMs), lncRNAs (DELs), and circRNAs (DECs) in serum exosomes. MicroRNAs (miRNAs) targeting DEMs were predicted using the Targetscan and miRanda databases, and miRNAs targeted by DELs and DECs were predicted using the miRcode and starBase databases, respectively. The biological functions and related signaling pathways of DEMs were analyzed using the David and KOBAS databases. Subsequently, a protein-protein interaction (PPI) network was established to screen out on which hub genes enrichment analyses should be performed, and a ceRNA network (lncRNA/circRNA-miRNA-mRNA) was constructed to elucidate ceRNA axes in CHD. Results. A total of 312 DEMs, 43 DELs, and 85 DECs were identified between CHD patients and normal controls. Functional enrichment analysis showed that DEMs were significantly enriched in “chromatin silencing at rDNA,” “telomere organization,” and “negative regulation of gene expression, epigenetic.” PPI network analysis showed that 25 hub DEMs were closely related to CHD, of which ubiquitin C (UBC) was the most important. Hub genes were mainly enriched in “cellular protein metabolic process” functions. The exosomal-associated ceRNA regulatory network incorporated 48 DEMs, 73 predicted miRNAs, 10 DELs, and 15 DECs. The LncRNA/circRNA-miRNA-mRNA interaction axes (RPL7AP11/hsa-miR-17-5p/UBC and RPL7AP11/hsa-miR-20b-5p/UBC) were obtained from the network. Conclusions. Our findings provide a novel perspective on the potential role of exosomal-associated ceRNA network regulation of the pathogenesis of CHD.

scholarly journals Investigating the pharmacological mechanisms of SheXiang XinTongNing against coronary heart disease based on network pharmacology

2020 ◽  
Author(s):  
Li-ying Jia ◽  
Jia Li ◽  
Gui-yun Cao ◽  
Zhao-qing Meng ◽  
Lu Gan ◽  
...  
Keyword(s):  
Coronary Heart Disease ◽  
Heart Disease ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Signaling Pathway ◽  
Protein Interaction ◽  
Protein Interaction Network ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Network Pharmacology

Abstract Background SheXiang XinTongNing, a commercially available Chinese patent medicine, has been widely used in the treatment of coronary heart disease. However, the mechanisms of SheXiang XinTongNing are still unclear. The aim of this study was to investigate the pharmacological mechanisms of SheXiang XinTongNing against coronary heart disease via network analysis. Method The traditional Chinese medicine system pharmacology analysis platform was used to screen the potential active constituents of the six traditional Chinese medicines in SheXiang XinTongNing, and the potential targets were obtained from PharmMapper. The genome annotation database platform was used to screen the candidate targets related to coronary heart disease. Then the drug-components-targets network and protein interaction network were built by Cytoscape 3.6.0 software. Further, GO bio-functional enrichment analysis and KEGG pathway enrichment analysis were performed through annotation, visualization and integrated discovery database. Results Results showed that the drugs-components-targets network contains 104 targets and 62 key components. The protein interaction network consisted of 107 nodes; key targets included Bcl2l1, IGF1, SRC, CASP3, et al. Functionally, the candidate targets were significantly associated with multiple pathways such as PI3K-Akt signaling pathway, MAPK signaling pathway, Ras signaling pathway, FoxO signaling pathway, Endocrine resistance. Given the above, the pharmacological activities of SheXiang XinTongNing may be predominantly related to several factors such as cell apoptosis, inflammation and angiogenesis. Conclusion XTN can effectively attenuate the symptoms of coronary heart disease through diverse pathways. The research proves that network pharmacology can successfully reveal the mechanisms of traditional Chinese medicine in a holistic view. Our systematic analysis lays a foundation for further studying.

scholarly journals Uncovering the Pharmacological of Xiaochaihu Decoction in the Treatment of Pancreatitis Based on the Network Pharmacology

2020 ◽  
Author(s):  
Lianghui Zhan ◽  
Jinbao Pu ◽  
Yijuan Hu ◽  
Pan Xu ◽  
Weiqing Liang ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Pancreatic Neoplasms ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Mapk Signaling ◽  
Network Pharmacology ◽  
Potential Mechanism ◽  
Ppi Network ◽  
Kegg Analysis ◽  
Key Genes

Abstract BackgroundXiaochaihu Decoction (XD) was a traditional prescription, has been demonstrated the pharmacodynamic on pancreatitis. But the underline mechanism remained to be explored. Therefore, this study was aimed to combined network pharmacology method and molecular docking technology to demonstrate the potential mechanism of XD treated with pancreatitis.MethodsFirstly, compounds of seven herbs containing XD were collected from TCMSP Database and the putative targets of Pancreatitis were obtained from OMIM, TTD, Genecards Database. Then PPI network was constructed according to the matching results between XD potential targets and pancreatic neoplasms targets. Furthermore, enrichment analysis on GO and KEGG by DAVID utilized bioinformatics resources. Finally, Molecular Docking was performed to simulate the interaction between the active compound of XD and putative targets.ResultsA total of 196 active ingredients and 91 putative targets were selected out. The PPI interaction network analysis demonstrated that Quercetin was the candidate agents and MAPK3, IL-6 and TP53 were the potential targets for the XD treatment of pancreatitis. The KEGG analysis revealed that pathways in cancers, TNF signaling way, MAPK signaling way might play an important role in pancreatitis therapy. And Molecular Docking results showed that Quercetin combined well with MAPK3, IL-6 and TP53.ConclusionThis study illustrated that Quercetin containing in XD might played an important role in pancreatitis therapy by acting the key genes of MPAK3, IL-6 and TP53. And it also provided a strategy to elucidate the mechanisms of Traditional Chinese Medicine (TCM) at the level of network pharmacology.

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