The molecular mechanism of TiaoGanYiPi formula for treatment of chronic hepatitis B by network pharmacology and molecular docking verification

Abstract The Chinese herbal formula Tiao-Gan-Yi-Pi (TGYP) showed effective against Chronic Hepatitis B (CHB). In this study, we aimed to clarify the mechanisms and potential targets between TGYP and CHB through network pharmacology and molecular docking verification. The compounds of TGYP were identified in the TCMSP and CNKI databases, and their putative targets were predicted through SwissTargetPrediction and STITCH databases. The targets of CHB were obtained from the GeneCards, NCBI Gene, and DisGeNET databases. The above mentioned data were visualized using Cytoscape, and molecular docking showed the relationship between them. The expression of key targets was verified in GEO databases. Hence, we screened out 11 TGYP-related key targets for CHB included ABL1, CASP8, CCNA2, CCNB1, CDK4, CDKN1A, EP300, HIF1A, IGF1R, MAP2K1 and PGR. The key targets were predominantly enriched in the cancer, cell cycle and hepatitis B pathways and involved in the positive regulation of fibroblast proliferation, signal transduction, and negative regulation of gene expression biological processes, and expression of key target genes was related to HBV infection and liver inflammation. Through this newly constructed interaction network between TGYP and CHB, we identified active compounds and targets which could be further used for providing clinical guidance.

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A Network Pharmacology Approach to Explore the Mechanisms of Artemisiae scopariae Herba for the Treatment of Chronic Hepatitis B

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2021/6614039 ◽

2021 ◽

Vol 2021 ◽

pp. 1-10

Author(s):

Asi He ◽

Wei Wang ◽

Yang Xia ◽

Xiaoping Niu

Keyword(s):

Chronic Hepatitis ◽

Chinese Medicine ◽

Traditional Chinese Medicine ◽

Hepatitis B ◽

Signaling Pathway ◽

Chronic Hepatitis B ◽

Molecular Mechanisms ◽

Target Genes ◽

Network Pharmacology ◽

Active Components

Background. As a traditional Chinese medicine, Artemisiae scopariae Herba (ASH) is used to treat various liver diseases. The purpose of this study was to explore the mechanisms of ASH for treating chronic hepatitis B (CHB) using a network pharmacological method. Methods. Bioactive ingredients and related targets of ASH were obtained from Traditional Chinese Medicine Systems Pharmacology (TCMSP) database. Gene names of targets were extracted from UniProt database. Differentially expressed genes (DEGs) of CHB were obtained from microarray dataset GSE83148. The intersect genes between DEGs and target genes were annotated using clusterProfiler package. The STRING database was used to obtain a network of protein-protein interactions. Cytoscape 3.7.2 was used to construct the “ingredient-gene-pathway” (IGP) network. Molecular docking studies were performed using Autodock vina. Results. A total of 13 active components were extracted from TCMSP database. Fifteen intersect genes were obtained between 183 target genes and 403 DEGs of GSE83148. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis results showed that ASH against CHB mainly involved in toll-like receptor signaling pathway, cellular senescence, hepatitis B, and chemokine signaling pathway. We screened one hub compound, five core targets, and four key pathways from constructed networks. The docking results indicated the strong binding activity between quercetin and AKT1. Conclusions. This study provides potential molecular mechanisms of ASH against CHB based on exploration of network pharmacology.

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Network Pharmacology and Molecular Docking Suggest the Mechanism for Biological Activity of Rosmarinic Acid

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2021/5190808 ◽

2021 ◽

Vol 2021 ◽

pp. 1-10

Author(s):

Minglong Guan ◽

Lan Guo ◽

Hengli Ma ◽

Huimei Wu ◽

Xiaoyun Fan

Keyword(s):

Biological Activity ◽

Molecular Docking ◽

Protein Interaction ◽

Protein Interaction Network ◽

Rosmarinic Acid ◽

Target Genes ◽

Interaction Network ◽

Enrichment Analysis ◽

Network Pharmacology ◽

Pathway Enrichment Analysis

Rosmarinic acid (RosA) is a natural phenolic acid compound, which is mainly extracted from Labiatae and Arnebia. At present, there is no systematic analysis of its mechanism. Therefore, we used the method of network pharmacology to analyze the mechanism of RosA. In our study, PubChem database was used to search for the chemical formula and the Chemical Abstracts Service (CAS) number of RosA. Then, the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) was used to evaluate the pharmacodynamics of RosA, and the Comparative Toxicogenomics Database (CTD) was used to identify the potential target genes of RosA. In addition, the Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of target genes were carried out by using the web-based gene set analysis toolkit (WebGestalt). At the same time, we uploaded the targets to the STRING database to obtain the protein interaction network. Then, we carried out a molecular docking about targets and RosA. Finally, we used Cytoscape to establish a visual protein-protein interaction network and drug-target-pathway network and analyze these networks. Our data showed that RosA has good biological activity and drug utilization. There are 55 target genes that have been identified. Then, the bioinformatics analysis and network analysis found that these target genes are closely related to inflammatory response, tumor occurrence and development, and other biological processes. These results demonstrated that RosA can act on a variety of proteins and pathways to form a systematic pharmacological network, which has good value in drug development and utilization.

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Potential Molecular Target Prediction and Docking Verification of Hua-Feng-Dan in Stroke Based on Network Pharmacology

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2020/8872593 ◽

2020 ◽

Vol 2020 ◽

pp. 1-12

Author(s):

Ping Yang ◽

Haifeng He ◽

Shangfu Xu ◽

Ping Liu ◽

Xinyu Bai

Keyword(s):

Molecular Docking ◽

Signaling Pathways ◽

Target Genes ◽

Target Prediction ◽

Interaction Network ◽

Network Pharmacology ◽

Core Network ◽

Active Ingredients ◽

Protein Protein Interaction ◽

Highly Correlated

Objective. Hua-Feng-Dan (HFD) is a Chinese medicine for stroke. This study is to predict and verify potential molecular targets and pathways of HFD against stroke using network pharmacology. Methods. The TCMSP database and TCMID were used to search for the active ingredients of HFD, and GeneCards and DrugBank databases were used to search for stroke-related target genes to construct the “component-target-disease” by Cytoscape 3.7.1, which was further filtered by MCODE to build a core network. The STRING database was used to obtain interrelationships by topology and to construct a protein-protein interaction network. GO and KEGG were carried out through DAVID Bioinformatics. Autodock 4.2 was used for molecular docking. BaseSpace was used to correlate target genes with the GEO database. Results. Based on OB ≥ 30% and DL ≥ 0.18, 42 active ingredients were extracted from HFD, and 107 associated targets were obtained. PPI network and Cytoscape analysis identified 22 key targets. GO analysis suggested 51 cellular biological processes, and KEGG suggested that 60 pathways were related to the antistroke mechanism of HFD, with p53, PI3K-Akt, and apoptosis signaling pathways being most important for HFD effects. Molecular docking verified interactions between the core target (CASP8, CASP9, MDM2, CYCS, RELA, and CCND1) and the active ingredients (beta-sitosterol, luteolin, baicalein, and wogonin). The identified gene targets were highly correlated with the GEO biosets, and the stroke-protection effects of Xuesaitong in the database were verified by identified targets. Conclusion. HFD could regulate the symptoms of stroke through signaling pathways with core targets. This work provided a bioinformatic method to clarify the antistroke mechanism of HFD, and the identified core targets could be valuable to evaluate the antistroke effects of traditional Chinese medicines.

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The relationship between HBV-DNA levels and cirrhosis-related complications in Chinese with chronic hepatitis B

Journal of Viral Hepatitis ◽

10.1111/j.1365-2893.2005.00603.x ◽

2005 ◽

Vol 12 (4) ◽

pp. 373-379 ◽

Cited By ~ 59

Author(s):

H.-J. Yuan ◽

M.-F. Yuen ◽

D. Ka-Ho Wong ◽

E. Sablon ◽

C.-L. Lai

Keyword(s):

Chronic Hepatitis ◽

Hepatitis B ◽

Chronic Hepatitis B ◽

Hbv Dna ◽

The Relationship

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Circulating miR-583 and miR-663 Refer to ZHENG Differentiation in Chronic Hepatitis B

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2013/751341 ◽

2013 ◽

Vol 2013 ◽

pp. 1-8 ◽

Cited By ~ 5

Author(s):

Hui Zhang ◽

Yan Guan ◽

Yi-Yu Lu ◽

Yi-Yang Hu ◽

Shuang Huang ◽

...

Keyword(s):

Chronic Hepatitis ◽

Hepatitis B ◽

Chronic Hepatitis B ◽

Target Genes ◽

Enrichment Analysis ◽

Deficiency Syndrome ◽

Mapk Signaling ◽

Pathway Enrichment Analysis ◽

Roc Curve Analysis ◽

Zheng Differentiation

Traditional Chinese medicine (TCM) ZHENG as the key pathological principle is to understand the human homeostasis and guide TCM treatment. Here, circulating microRNAs (miRNAs) were utilized to differentiate between ZHENGs including liver-gallbladder dampness-heat syndrome (LGDHS) and liver-kidney yin deficiency syndrome (LKYDS) in chronic hepatitis B (CHB). Sera samples of CHB patients with LGDHS (n=35), LKYDS (n=24), and healthy controls (Ctrls,n=21) were analyzed by microarray and real-time RT-PCR. Receiver-operator characteristic (ROC) curves were established to evaluate the levels of serum miRNA for discriminating LGDHS and LKYDS. The target genes of miRNAs were predicted by TargetScan. Gene Ontology (GO) and pathways were analyzed using DAVID tool. The results showed that 22 miRNAs were differentially expressed between LGDHS and LKYDS (fold change>2.0 andP<0.01). Circulating miR-583 and miR-663 were significantly higher (P<0.001) in CHB patients with LGDHS than those with LKYDS and Ctrls. ROC curve analysis revealed that miR-583 and miR-663 were sensitive and specific enough to distinguish LGDHS from LKYDS. Pathway enrichment analysis indicated that 354 putative targets for miR-583 and 68 putative targets for miR-663 were mainly involved in Axon guidance, Neurotrophin, and MAPK signaling pathway. miR-583 and miR-663 may be potential markers for ZHENG differentiation in CHB.

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Evaluation of the relationship between ABO/Rh blood groups and severity of liver fibrosis in patients with chronic hepatitis B

Viral Hepatitis Journal ◽

10.4274/vhd.49368 ◽

2016 ◽

Vol 22 (1) ◽

pp. 23-27

Author(s):

İsmail Necati HAKYEMEZ ◽

Bülent DURDU ◽

Sibel BOLUKÇU ◽

Turan ASLAN

Keyword(s):

Chronic Hepatitis ◽

Liver Fibrosis ◽

Hepatitis B ◽

Chronic Hepatitis B ◽

Blood Groups ◽

The Relationship

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Correlation of Small Dense Low Density Lipoprotein, Tumour Necrosis Factor - alpha with Liver Enzymes in Chronic Hepatitis B Patients

International Journal of TROPICAL DISEASE & Health ◽

10.9734/ijtdh/2019/v37i430172 ◽

2019 ◽

pp. 1-8

Author(s):

Isaac Oluwole Adediji ◽

Adeolu Sunday Oluremi ◽

Ayodele Ademola Adelakun ◽

Paul Olusegun Adepoju ◽

Dominion Akingbade ◽

...

Keyword(s):

Chronic Hepatitis ◽

Hepatitis B ◽

Chronic Hepatitis B ◽

Low Density Lipoprotein ◽

Density Lipoprotein ◽

Necrosis Factor Alpha ◽

Tnf Α ◽

Factor Alpha ◽

The Relationship ◽

Necrosis Factor

Aim: This study investigated the relationship between small dense low density lipoprotein (sdLDL), tumour necrosis factor-alpha (TNF-α), aspartate aminotransferase (AST), alanine aminotransferase (ALT) and alkaline phosphatase (ALP) in chronic hepatitis B patients. Duration of Study: June 2018- March 2019. Subjects and Methods: Sixty (60) participants were recruited for this cross sectional study. They comprised thirty (30) clinically diagnosed chronic hepatitis B virus (HBV) infected patients attending clinic at a tertiary hospital in Osogbo, Osun state, Nigeria. Thirty (30) apparently healthy volunteers were recruited as control subjects after fulfilling the inclusion criteria. Anthropometric measurements were performed using standard method. About 6mL of venous blood was collected from each study participant, serum was extracted and kept at -80oC until time of analysis. Small dense LDL, TNF-α, AST, ALT and ALP were determined using enzyme linked immunosorbent assay and colorimetric method as appropriate. Data analysis was done using Student’s t-test for comparison of variables and Pearson’s correlation was used to determine the relationship between variables. P–value less than 0.05 was considered significant. Results: SdLDL, TNF-α, AST and ALT were significantly elevated in HBV patients when compared with the control subjects (P<0.05). SdLDL had a significant positive correlation with TNF-α (P=0.03), AST (P=0.01), ALT (P=0.00). TNF-α had a significant positive correlation with AST (P=0.02) and ALT (P=0.00). Conclusion: This study revealed a noteworthy positive relationship between sdLDL, TNF-α and hepatic aminotransferases in chronic hepatitis B patients.

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Uncovering the mechanism of Ge-Gen-Qin-Lian decoction for treating ulcerative colitis based on network pharmacology and molecular docking verification

Bioscience Reports ◽

10.1042/bsr20203565 ◽

2021 ◽

Vol 41 (2) ◽

Author(s):

Lin Xu ◽

Jiaqi Zhang ◽

Yifan Wang ◽

Zedan Zhang ◽

Fengyun Wang ◽

...

Keyword(s):

Ulcerative Colitis ◽

Molecular Docking ◽

Interaction Network ◽

Network Pharmacology ◽

Potential Candidate ◽

Active Ingredients ◽

Protein Protein Interaction ◽

Pharmacological Mechanism ◽

Th17 Cell Differentiation ◽

The Relationship

Abstract Background: Ge-Gen-Qin-Lian Decoction (GGQLD), a traditional Chinese medicine (TCM) formula, has been widely used for ulcerative colitis (UC) in China, but the pharmacological mechanisms remain unclear. This research was designed to clarify the underlying pharmacological mechanism of GGQLD against UC. Method: In this research, a GGQLD-compound-target-UC network was constructed based on public databases to clarify the relationship between active compounds in GGQLD and potential targets. Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (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. Molecular docking was used to verify the activities of binding between hub targets and ingredients. Results: Finally, 83 potential therapeutic targets and 118 corresponding active ingredients were obtained by network pharmacology. Quercetin, kaempferol, wogonin, baicalein, and naringenin were identified as potential candidate ingredients. GO and KEGG enrichment analyses revealed that GGQLD had anti-inflammatory, antioxidative, and immunomodulatory effects. The effect of GGQLD on UC might be achieved by regulating the balance of cytokines (e.g., IL-6, TNF, IL-1β, CXCL8, CCL2) in the immune system and inflammation-related pathways, such as the IL-17 pathway and the Th17 cell differentiation pathway. In addition, molecular docking results demonstrated that the main active ingredient, quercetin, exhibited good affinity to hub targets. Conclusion: This research fully reflects the multicomponent and multitarget characteristics of GGQLD in the treatment of UC. Furthermore, the present study provided new insight into the mechanisms of GGQLD against UC.

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