scholarly journals Systematic Elucidation of the Mechanism of Sappan Lignum in the Treatment of Diabetic Peripheral Neuropathy Based on Network Pharmacology

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Xiaomin Kang ◽  
De Jin ◽  
Yuqing Zhang ◽  
Rongrong Zhou ◽  
Yuehong Zhang ◽  
...  
Keyword(s):  
Peripheral Neuropathy ◽  
Diabetic Peripheral Neuropathy ◽  
Target Prediction ◽  
Scientific Basis ◽  
Network Pharmacology ◽  
Therapeutic Effects ◽  
Physical And Mental Health ◽  
Protein Protein Interaction ◽  
Target Network ◽  
Compound Target

Background. Diabetic peripheral neuropathy (DPN) is one of the most common chronic complications of diabetes, which seriously affects the physical and mental health of patients. Sappan Lignum (SL) is effective in treating DPN. Previous reports have shown that SL has a clear hypoglycemic and anti-inflammatory effect. However, the study of SL in the treatment of DPN is still limited and rare. Objective. To investigate the mechanism of SL in the treatment of DPN based on network pharmacology. Methods. The active ingredients of SL were screened by related databases. The compound targets were collected by the target prediction platforms. The DPN-related targets were gathered through disease databases. The intersection targets were obtained by uploading the compound targets and disease targets to Venny 2.1.0, and a compound-target network was constructed by Cytoscape3.7.2. The protein-protein interaction (PPI) relationships were obtained by the STRING11.0 database. Genome Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed using the DAVID6.8 database. Molecular docking of key compounds and core targets was performed by DockThor. Results. A total of 29 compounds and 51 intersection targets with potential therapeutic effects on DPN were obtained. The compound-target network construction resulted in four key compounds: protostemonine, 3-deoxysappanchalcone, 7,3′,4′-trihydroxy-3-benzyl-2H-chromene, and o-12′-methylergocornine. PPI network analysis yielded 10 core targets: AKT1, MAPK3, CXCL8, TNF, OPRM1, MTOR, STAT3, MAPK8, SIRT1, and HSP90AA1. KEGG analysis resulted in 82 signaling pathways ( P < 0.05 ), including insulin resistance, HIF-1 signaling pathway, and type II diabetes. The docking results indicated that the main active compounds could stably bind to core targets. Conclusion. SL had the mechanism of multiple ingredients, multiple targets, and multiple pathways in the treatment of DPN. This study provided a scientific basis for further research on the treatment of DPN with SL and its extracts.

scholarly journals The Methodological Trends of Traditional Herbal Medicine Employing Network Pharmacology

Biomolecules ◽  
2019 ◽  
Vol 9 (8) ◽  
pp. 362 ◽  
Author(s):  
Won-Yung Lee ◽  
Choong-Yeol Lee ◽  
Youn-Sub Kim ◽  
Chang-Eop Kim
Keyword(s):  
Herbal Medicine ◽  
Network Pharmacology ◽  
Therapeutic Effects ◽  
Systems Pharmacology ◽  
Traditional Herbal Medicine ◽  
Affiliation Networks ◽  
Target Network ◽  
Analysis Platform ◽  
Combining Methods ◽  
Compound Target

Natural products, including traditional herbal medicine (THM), are known to exert their therapeutic effects by acting on multiple targets, so researchers have employed network pharmacology methods to decipher the potential mechanisms of THM. To conduct THM-network pharmacology (THM-NP) studies, researchers have employed different tools and databases for constructing and analyzing herb–compound–target networks. In this study, we attempted to capture the methodological trends in THM-NP research. We identified the tools and databases employed to conduct THM-NP studies and visualized their combinatorial patterns. We also constructed co-author and affiliation networks to further understand how the methodologies are employed among researchers. The results showed that the number of THM-NP studies and employed databases/tools have been dramatically increased in the last decade, and there are characteristic patterns in combining methods of each analysis step in THM-NP studies. Overall, the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) was the most frequently employed network pharmacology database in THM-NP studies. Among the processes involved in THM-NP research, the methodology for constructing a compound–target network has shown the greatest change over time. In summary, our analysis describes comprehensive methodological trends and current ideas in research design for network pharmacology researchers.

scholarly journals Identify the Key Active Ingredients and Pharmacological Mechanisms of Compound XiongShao Capsule in Treating Diabetic Peripheral Neuropathy by Network Pharmacology Approach

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Meixiang Yu ◽  
Xin Song ◽  
Wanhua Yang ◽  
Ziwei Li ◽  
Xiaoqin Ma ◽  
...  
Keyword(s):  
Peripheral Neuropathy ◽  
Signaling Pathway ◽  
Clinical Efficacy ◽  
Diabetic Peripheral Neuropathy ◽  
Kinase Activity ◽  
Network Pharmacology ◽  
Therapeutic Effects ◽  
Molecular Function ◽  
Active Ingredients ◽  
Xiongshao Capsule

Compound XiongShao Capsule (CXSC), a traditional herb mixture, has shown significant clinical efficacy against diabetic peripheral neuropathy (DPN). However, its multicomponent and multitarget features cause difficulty in deciphering its molecular mechanisms. Our study aimed to identify the key active ingredients and potential pharmacological mechanisms of CXSC in treating DPN by network pharmacology and provide scientific evidence of its clinical efficacy. CXSC active ingredients were identified from both the Traditional Chinese Medicine Systems Pharmacology database, with parameters of oral bioavailability ≥ 30% and drug-likeness ≥ 0.18, and the Herbal Ingredients’ Targets (HIT) database. The targets of those active ingredients were identified using ChemMapper based on 3D-structure similarity and using HIT database. DPN-related genes were acquired from microarray dataset GSE95849 and five widely used databases (TTD, Drugbank, KEGG, DisGeNET, and OMIM). Next, we obtained candidate targets with therapeutic effects against DPN by mapping active ingredient targets and DPN-related genes and identifying the proteins interacting with those candidate targets using STITCH 5.0. We constructed an “active ingredients-candidate targets-proteins” network using Cytoscape 3.61 and identified key active ingredients and key targets in the network. We identified 172 active ingredients in CXSC, 898 targets of the active ingredients, 110 DPN-related genes, and 38 candidate targets with therapeutic effects against DPN. Three key active ingredients, namely, quercetin, kaempferol, and baicalein, and 25 key targets were identified. Next, we input all key targets into ClueGO plugin for KEGG enrichment and molecular function analyses. The AGE-RAGE signaling pathway in diabetic complications and MAP kinase activity were determined as the main KEGG pathway and molecular function involved, respectively. We determined quercetin, kaempferol, and baicalein as the key active ingredients of CXSC and the AGE-RAGE signaling pathway and MAP kinase activity as the main pharmacological mechanisms of CXSC against DPN, proving the clinical efficacy of CXSC against DPN.

scholarly journals An Analysis of the Anti-Neuropathic Effects of Qi She Pill Based on Network Pharmacology

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Yong-jia Song ◽  
Jia-min Bao ◽  
Long-yun Zhou ◽  
Gan Li ◽  
Kim Sia Sng ◽  
...  
Keyword(s):  
Mechanism Of Action ◽  
Protein Interaction ◽  
Protein Interaction Network ◽  
Biological Process ◽  
Interaction Network ◽  
Network Pharmacology ◽  
Protein Protein Interaction ◽  
Target Network ◽  
Protein Protein Interaction Network ◽  
Compound Target

Background. Qi She Pill (QSP) is a traditional prescription for the treatment of neuropathic pain (NP) that is widely used in China. However, no network pharmacology studies of QSP in the treatment of NP have been conducted to date. Objective. To verify the potential pharmacological effects of QSP on NP, its components were analyzed via target docking and network analysis, and network pharmacology methods were used to study the interactions of its components. Materials and Methods. Information on pharmaceutically active compounds in QSP and gene information related to NP were obtained from public databases, and a compound-target network and protein-protein interaction network were constructed to study the mechanism of action of QSP in the treatment of NP. The mechanism of action of QSP in the treatment of NP was analyzed via Gene Ontology (GO) biological process annotation and Kyoto Gene and Genomics Encyclopedia (KEGG) pathway enrichment, and the drug-like component-target-pathway network was constructed. Results. The compound-target network contained 60 compounds and 444 corresponding targets. The key active compounds included quercetin and beta-sitosterol. Key targets included PTGS2 and PTGS1. The protein-protein interaction network of the active ingredients of QSP in the treatment of NP featured 48 proteins, including DRD2, CHRM, β2-adrenergic receptor, HTR2A, and calcitonin gene-related peptide. In total, 53 GO entries, including 35 biological process items, 7 molecular function items, and 11 cell related items, were identified. In addition, eight relevant (KEGG) pathways were identified, including calcium, neuroactive ligand-receptor interaction, and cAMP signaling pathways. Conclusion. Network pharmacology can help clarify the role and mechanism of QSP in the treatment of NP and provide a foundation for further research.

Systematic Investigation of Quercetin for Treating Cardiovascular Disease Based on Network Pharmacology

2019 ◽  
Vol 22 (6) ◽  
pp. 411-420 ◽  
Author(s):  
Xian-Jun Wu ◽  
Xin-Bin Zhou ◽  
Chen Chen ◽  
Wei Mao
Keyword(s):  
Cardiovascular Disease ◽  
Cardiovascular Diseases ◽  
Signaling Pathway ◽  
Kegg Pathway ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Therapeutic Effects ◽  
Pathway Enrichment ◽  
Compound Target

Aim and Objective: Cardiovascular disease is a serious threat to human health because of its high mortality and morbidity rates. At present, there is no effective treatment. In Southeast Asia, traditional Chinese medicine is widely used in the treatment of cardiovascular diseases. Quercetin is a flavonoid extract of Ginkgo biloba leaves. Basic experiments and clinical studies have shown that quercetin has a significant effect on the treatment of cardiovascular diseases. However, its precise mechanism is still unclear. Therefore, it is necessary to exploit the network pharmacological potential effects of quercetin on cardiovascular disease. Materials and Methods: In the present study, a novel network pharmacology strategy based on pharmacokinetic filtering, target fishing, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, compound-target-pathway network structured was performed to explore the anti- cardiovascular disease mechanism of quercetin. Results:: The outcomes showed that quercetin possesses favorable pharmacokinetic profiles, which have interactions with 47 cardiovascular disease-related targets and 12 KEGG signaling pathways to provide potential synergistic therapeutic effects. Following the construction of Compound-Target-Pathway (C-T-P) network, and the network topological feature calculation, we obtained top 10 core genes in this network which were AKT1, IL1B, TNF, IL6, JUN, CCL2, FOS, VEGFA, CXCL8, and ICAM1. KEGG pathway enrichment analysis. These indicated that quercetin produced the therapeutic effects against cardiovascular disease by systemically and holistically regulating many signaling pathways, including Fluid shear stress and atherosclerosis, AGE-RAGE signaling pathway in diabetic complications, TNF signaling pathway, MAPK signaling pathway, IL-17 signaling pathway and PI3K-Akt signaling pathway.

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 Network Pharmacology-Based Study of the Underlying Mechanisms of Huangqi Sijunzi Decoction for Alzheimer’s Disease

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Wei Zhang ◽  
Mingti Lv ◽  
Yating Shi ◽  
Yonghui Mu ◽  
Zhaoyang Yao ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Neuroprotective Effect ◽  
Signalling Pathway ◽  
Signalling Pathways ◽  
Network Pharmacology ◽  
Neuroprotective Effects ◽  
Target Network ◽  
Compound Target

Background. Huangqi Sijunzi decoction (HQSJZD) is a commonly used conventional Chinese herbal medicine prescription for invigorating Qi, tonifying Yang, and removing dampness. Modern pharmacology and clinical applications of HQSJZD have shown that it has a certain curative effect on Alzheimer’s disease (AD). Methods. The active components and targets of HQSJZD were searched in the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). The genes corresponding to the targets were retrieved using UniProt and GeneCard database. The herb-compound-target network and protein-protein interaction (PPI) network were constructed by Cytoscape. The core targets of HQSJZD were analysed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). The main active compounds of HQSJZD were docked with acetylcholinesterase (AChE). In vitro experiments were conducted to detect the inhibitory and neuroprotective effects of AChE. Results. Compound-target network mainly contained 132 compounds and 255 corresponding targets. The main compounds contained quercetin, kaempferol, formononetin, isorhamnetin, hederagenin, and calycosin. Key targets contained AChE, PTGS2, PPARG, IL-1B, GSK3B, etc. There were 1708 GO items in GO enrichment analysis and 310 signalling pathways in KEGG, mainly including the cAMP signalling pathway, the vascular endothelial growth factor (VEGF) signalling pathway, serotonergic synapses, the calcium signalling pathway, type II diabetes mellitus, arginine and proline metabolism, and the longevity regulating pathway. Molecular docking showed that hederagenin and formononetin were the top 2 compounds of HQSJZD, which had a high affinity with AChE. And formononetin has a good neuroprotective effect, which can improve the oxidative damage of nerve cells. Conclusion. HQSJZD was found to have the potential to treat AD by targeting multiple AD-related targets. Formononetin and hederagenin in HQSJZD may regulate multiple signalling pathways through AChE, which might play a therapeutic role in AD.

scholarly journals Therapeutic effects of moxibustion simultaneously targeting Nrf2 and NF-κB in diabetic peripheral neuropathy

2019 ◽  
Vol 189 (4) ◽  
pp. 1167-1182 ◽  
Author(s):  
Jia Li ◽  
Xia Hu ◽  
Fengxia Liang ◽  
Jianmin Liu ◽  
Huanjiao Zhou ◽  
...  
Keyword(s):  
Peripheral Neuropathy ◽  
Diabetic Peripheral Neuropathy ◽  
Therapeutic Effects

scholarly journals Investigation of the Potential Mechanism Governing the Effect of the Shen Zhu San on COVID-19 by Network Pharmacology

2020 ◽  
Vol 2020 ◽  
pp. 1-23 ◽  
Author(s):  
Yuxuan Wang ◽  
Yuhua Ru ◽  
Guowei Zhuo ◽  
Maozheng Sheng ◽  
Shuangqiu Wang ◽  
...  
Keyword(s):  
Combined Therapy ◽  
Target Prediction ◽  
Interaction Network ◽  
Modern Medicine ◽  
Network Pharmacology ◽  
Target Tissue ◽  
Protein Protein Interaction ◽  
Compound Screening ◽  
Therapeutic Mechanisms ◽  
Microarray Analyses

Background. Since December 2019, coronavirus disease 2019 (COVID-19) due to SARS-CoV-2 infection has emerged in Wuhan and rapidly spread throughout China and even to other countries. Combined therapy with modern medicine and traditional Chinese medicine has been proposed, in which Shen Zhu San (SZS) was regarded as one of the basic prescriptions. Methods. Network pharmacological approaches along with candidate compound screening, target prediction, target tissue location, protein-protein interaction network, gene ontology (GO), KEGG enrichment analyses, and gene microarray analyses were applied. Results. A total of 627 targets of the 116 active ingredients of SZS were identified. Targets in immune cells and tissues were much more abundant than those in other tissues. A total of 597 targets were enriched in the GO biological cellular process, while 153 signaling pathways were enriched according to the KEGG analysis. A total of 450 SARS-related targets were integrated and intersected with the targets of SZS to identify 40 common targets that were significantly enriched in five immune function aspects of the immune system process during GO analysis. Several inflammation-related pathways were found to be significantly enriched throughout the study. Conclusions. The therapeutic mechanisms of the effects of SZS on COVID-19 potentially involve four effects: suppressing cytokine storms, protecting the pulmonary alveolar-capillary barrier, regulating the immune response, and mediating cell death and survival.

scholarly journals Network Pharmacology-Based Investigation into the Mechanisms of Quyushengxin Formula for the Treatment of Ulcerative Colitis

2019 ◽  
Vol 2019 ◽  
pp. 1-22
Author(s):  
Haojie Yang ◽  
Ying Li ◽  
Sichen Shen ◽  
Dan Gan ◽  
Changpeng Han ◽  
...  
Keyword(s):  
Ulcerative Colitis ◽  
Bioactive Compounds ◽  
Functional Enrichment ◽  
Network Pharmacology ◽  
Disease Network ◽  
Pathway Network ◽  
Similarity Algorithm ◽  
Target Network ◽  
Target Disease ◽  
Compound Target

Objective. Ulcerative colitis (UC) is a chronic idiopathic inflammatory bowel disease whose treatment strategies remain unsatisfactory. This study aims to investigate the mechanisms of Quyushengxin formula acting on UC based on network pharmacology. Methods. Ingredients of the main herbs in Quyushengxin formula were retrieved from the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database. Absorption, distribution, metabolism, and excretion properties of all ingredients were evaluated for screening out candidate bioactive compounds in Quyushengxin formula. Weighted ensemble similarity algorithm was applied for predicting direct targets of bioactive ingredients. Functional enrichment analyses were performed for the targets. In addition, compound-target network, target-disease network, and target-pathway network were established via Cytoscape 3.6.0 software. Results. A total of 41 bioactive compounds in Quyushengxin formula were selected out from the TCMSP database. These bioactive compounds were predicted to target 94 potential proteins by weighted ensemble similarity algorithm. Functional analysis suggested these targets were closely related with inflammatory- and immune-related biological progresses. Furthermore, the results of compound-target network, target-disease network, and target-pathway network indicated that the therapeutic effects of Quyushengxin on UC may be achieved through the synergistic and additive effects. Conclusion. Quyushengxin may act on immune and inflammation-related targets to suppress UC progression in a synergistic and additive manner.

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