Deciphering the Pharmacological Mechanisms of Guizhi-Fuling Capsule on Primary Dysmenorrhea Through Network Pharmacology

Guizhi-Fuling capsule (GZFLC), originated from a classical traditional Chinese herbal formula Guizhi-Fuling Wan, has been clinically used for primary dysmenorrhea in China. Nonetheless, the underlying pharmacological mechanisms of GZFLC remain unclear. The integration of computational and experimental methods of network pharmacology might be a promising way to decipher the mechanisms. In this study, the target profiles of 51 representative compounds of GZFLC were first predicted by a high-accuracy algorithm, drugCIPHER-CS, and the network target of GZFLC was identified. Then, potential functional modules of GZFLC on primary dysmenorrhea were investigated using functional enrichment analysis. Potential bioactive compounds were recognized by hierarchical clustering analysis of GZFLC compounds and first-line anti-dysmenorrhea drugs. Furthermore, the potential anti-dysmenorrhea mechanisms of GZFLC were verified through enzyme activity assays and immunofluorescence tests. Moreover, effects of GZFLC on primary dysmenorrhea were evaluated in oxytocin-induced dysmenorrhea murine model. In the network target analysis, GZFLC may act on five functional modules of pain, inflammation, endocrine, blood circulation and energy metabolism. Integrating computational and experimental approaches, we found that GZFLC significantly inhibited the writhing response and reduced the degree of uterine lesions in oxytocin-induced dysmenorrhea murine model. Furthermore, GZFLC may partially alleviate primary dysmenorrhea by inhibiting cyclooxygenase 2 (COX2) and downregulating MAPK signaling pathway. Consequently, GZFLC presented pain relief and sustained benefits for primary dysmenorrhea. This study could provide a scientific approach for deciphering pharmacological mechanisms of herbal formulae through network pharmacology.

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Integrated Analyses Identify Immune-Related Signature Associated with Qingyihuaji Formula for Treatment of Pancreatic Ductal Adenocarcinoma Using Network Pharmacology and Weighted Gene Co-Expression Network

Journal of Immunology Research ◽

10.1155/2020/7503605 ◽

2020 ◽

Vol 2020 ◽

pp. 1-17

Author(s):

Xiang Qian ◽

Zhuo Chen ◽

Sha Sha Chen ◽

Lu Ming Liu ◽

Ai Qin Zhang

Keyword(s):

Expression Profiles ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Functional Enrichment ◽

Ductal Adenocarcinoma ◽

Network Pharmacology ◽

Active Ingredients ◽

Kaplan Meier ◽

Human Protein Atlas

The study aimed to clarify the potential immune-related targets and mechanisms of Qingyihuaji Formula (QYHJ) against pancreatic cancer (PC) through network pharmacology and weighted gene co-expression network analysis (WGCNA). Active ingredients of herbs in QYHJ were identified by the TCMSP database. Then, the putative targets of active ingredients were predicted with SwissTargetPrediction and the STITCH databases. The expression profiles of GSE32676 were downloaded from the GEO database. WGCNA was used to identify the co-expression modules. Besides, the putative targets, immune-related targets, and the critical module genes were mapped with the specific disease to select the overlapped genes (OGEs). Functional enrichment analysis of putative targets and OGEs was conducted. The overall survival (OS) analysis of OGEs was investigated using the Kaplan-Meier plotter. The relative expression and methylation levels of OGEs were detected in UALCAN, human protein atlas (HPA), Oncomine, DiseaseMeth version 2.0 and, MEXPRESS database, respectively. Gene set enrichment analysis (GSEA) was conducted to elucidate the key pathways of highly-expressed OGEs further. OS analyses found that 12 up-regulated OGEs, including CDK1, PLD1, MET, F2RL1, XDH, NEK2, TOP2A, NQO1, CCND1, PTK6, CTSE, and ERBB2 that could be utilized as potential diagnostic indicators for PC. Further, methylation analyses suggested that the abnormal up-regulation of these OGEs probably resulted from hypomethylation, and GSEA revealed the genes markedly related to cell cycle and proliferation of PC. This study identified CDK1, PLD1, MET, F2RL1, XDH, NEK2, TOP2A, NQO1, CCND1, PTK6, CTSE, and ERBB2 might be used as reliable immune-related biomarkers for prognosis of PC, which may be essential immunotherapies targets of QYHJ.

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Functional Enrichment Analysis by David in Transgenic MYCN Zebrafish Model

Blood ◽

10.1182/blood.v120.21.5114.5114 ◽

2012 ◽

Vol 120 (21) ◽

pp. 5114-5114

Author(s):

Li-Jing Shen ◽

Fang-Yuan Chen ◽

Lan-Fang Cao ◽

Yong Zhang ◽

Hua Zhong

Keyword(s):

Cell Cycle ◽

Signaling Pathways ◽

Microarray Analysis ◽

Conflicts Of Interest ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Mapk Signaling ◽

Functional Enrichment ◽

Tgfβ Signaling ◽

Apoptosis Pathway

Abstract Abstract 5114 Introduction The MYCN oncogene encodes a basic helix-loop-helix/leucine zipper (bHLH/LZ) transcription factor that is frequently overexpressed in hematologic malignancies neoplasms (including acute leukemia, T-cell lymphoma, and so on). MYCN acts as a poor prognostic marker to promote an aggressive phenotype. However, the mechanisms of action and pathways affected by MYCN are still largely unclear. Methods We induced murine MYCN gene overexpression in embryonic zebrafish through heat-shock promoter and established stable germline Tg(MYCN:HSE:EGFP) zebrafish. RNA was extracted at 3 days post fertilization from wild type (WT) and transgenic zebrafish F1 generation (TG) embryo hematopoietic cells, collected by the flow cytometer, for microarray analysis. The samples were processed and subsequently analyzed in triplicate on Zebrafish Oligo Microarrays (Agilent Technologies), containing 43, 554 sets of probe, at the Advanced Throughput Inc. The microarrays were scanned in an Agilent DNA Microarray Scanner and the images were processed using Feature Extraction software. A False Discovery Rate≤0. 05 for overall interactions effect and P<0. 001 between comparisons were used to determine differentially expressed genes (DEG). Ingenuity Pathway Analysis and DAVID performed the functional analysis of DEG. Results Microarray analysis revealed 626 (342 genes up-regulated and 284 genes down-regulated) DEG that showed >2-fold change in TG comparing with that of WT. Using functional enrichment analysis by DAVID, several signaling pathways were regulated in TG samples (Table 1). MAPK signaling pathway was high activated through FGF, PDGF, BDNF and CACN high expression, promoting up-regulated of Ras and MKP, enhancing phosphorylation and leading to increase of cells proliferation. TGFβ signaling was inhibited by up-regulation of IFN Ã and Smad 6/7, which negative control of TGFβR and Smad 2/3. Further, we found that MYCN enhances the expression of skp2, via decreased p21 and increased CDK2, promoting cell cycle progression (Fig. 1). In addition, overexpression of MYCN weakened the function of mismatch repair, base excision repair, while increased apoptosis pathway mediated by p53 (up-regulated Bid gene). Meanwhile, Glycolysis/gluconeogenesis pathway was significantly up-regulated in TG fish. Conclusions Overexpression of MYCN induced up-regulation of cell proliferation and Glycolysis/gluconeogenesis pathway (as the Warburg effect in rapidly proliferating tumors), attenuation of repair function, all of which are phenomena associated with proliferation and malignancies transformation of blood cell feature. We found that MYCN down-regulates p27kip1, p57kip2 and p21cip1 through up-regulate Skp2, thus up-regulates CDK2, CycA, CycB, CycD and CycE. All above changes shortened the time taken to progress through the cell cycle. Increased MARK signaling and decreased TGFβ signaling pathways also contributed to promote cell cycle. (Red star marks the up-regulated genes). Disclosures: No relevant conflicts of interest to declare.

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Network pharmacology, molecular docking, and experimental study for the mechanisms of Qishen Yiqi Pills against Cardiovascular Diseases

10.21203/rs.3.rs-889464/v1 ◽

2021 ◽

Author(s):

Jie-wen Zhao ◽

Hai-dong Liu ◽

Ming-yin Man ◽

Lv-ya Wang ◽

Ning Li ◽

...

Keyword(s):

Molecular Docking ◽

Cardiovascular Diseases ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Network Pharmacology ◽

Literature Mining ◽

Therapeutic Effects ◽

Active Components

Abstract Background Qishen Yiqi Pills (QSYQP) is a traditional Chinese compound recipe. However, our understanding of its mechanism has been hindered due to the complexity of its components and targets. In this work, the network pharmacology-based approaches were used to explore QSYQP’s pharmacological mechanism on treating cardiovascular diseases (CVD). Results From ETCM and TCM MESH databases we collected QSYQP’s 333 active components and their 674 putative targets. We constructed the sub-network influence by CVD genes and found that 40% QSYQP targets appeared in 20 modules, in which QSYQP’s targets and CVD genes co-existed as hub nodes in the sub-network. Functional enrichment analysis suggested that the 42 key targets were mainly expressed in platelets, blood vessels, cardiomyocytes, and other tissues. The main signaling pathways regulated and controlled by the key targets were inflammation, immunity, blood coagulation and energy metabolism. Network and pathway analysis identified 7 key targets, which were regulated by 7 compounds of QSYQP. 26 of the 42 important targets, including the 7 key targets were verified by literature mining. Twelve pairs of interactions between key targets and QSYQP’s compounds were validated by molecular docking. Further validation experiments suggested that QSYQP suppressed H/R induced apoptosis and cytoskeleton disruption of cardiomyocytes. Western blotting showed that the expression of cardiovascular diseases-related genes including ACTC1, FoxO1 and DIAPH1 was significantly decreased by establishing the hypoxia-reoxygenation model in vitro, while the protein expression of experimental group was significantly increased by adding QSYQP or its ingredients. Conclusion These results indicated the correlation of QSYQP treatment to the therapeutic effects of CVD. At the molecular level, this study revealed the multicomponent and multitargeting mechanisms of QSYQP in the regulation and treatment of cardiovascular diseases, potentially providing a reference for the further utilization of QSYQP.

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Dissecting the Mechanism of Yuzhi Zhixue Granule on Ovulatory Dysfunctional Uterine Bleeding by Network Pharmacology and Molecular Docking

10.21203/rs.3.rs-45961/v2 ◽

2020 ◽

Author(s):

Jialin Li ◽

Hua Luo ◽

Xinkui Liu ◽

Jingyuan Zhang ◽

Wei Zhou ◽

...

Keyword(s):

Molecular Docking ◽

Therapeutic Target ◽

Molecular Mechanisms ◽

Therapeutic Targets ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Uterine Bleeding ◽

Functional Enrichment ◽

Network Pharmacology ◽

Dysfunctional Uterine Bleeding

Abstract Background: Yuzhi Zhixue Granule (YZG)is a traditional Chinese patent medicine for treating excessive menstrual flow caused by ovulatory dysfunctional uterine bleeding (ODUB) accompanied by heat syndrome. However, the underlying molecular mechanisms, potential targets, and active ingredients of this prescription are still unknown. Therefore, it is imperative to explore the molecular mechanism of YZG.Methods: The active compounds in YZG were screened by the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). The putative targets of YZG were collected via TCMSP and Search Tool for Interacting Chemicals (STITCH) databases. The Therapeutic Target Database (TTD) and Pharmacogenomics Knowledgebase (PharmGKB) databases were used to identify the therapeutic targets of ODUB. A protein-protein interaction (PPI) network containing both the putative targets of YZG and known therapeutic targets of ODUB was built. Furthermore, bioinformatics resources from the database for annotation, visualization and integrated discovery (DAVID) were utilized for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Finally, molecular docking was performed to verify the binding effect between the YZG screened compounds and potential therapeutic target molecules.Results: The study employed a network pharmacology method, mainly containing target prediction, network construction, functional enrichment analysis, and molecular docking to systematically research the mechanisms of YZG in treating ODUB. The putative targets of YZG that treat ODUB mainly involved PTGS1, PTGS2, ALOX5, CASP3, LTA4H, F7 and F10. The functional enrichment analysis suggested that the produced therapeutic effect of YZG against ODUB is mediated by synergistical regulation of several biological pathways, including apoptosis arachidonic acid (AA) metabolism, serotonergic synapse, complement and coagulation cascades and C-type lectin receptor signaling pathways. Molecular docking simulation revealed good binding afﬁnity of the seven putative targets with the corresponding compounds.Conclusion: This novel and scientific network pharmacology-based study holistically elucidated the basic pharmacological effects and the underlying mechanisms of YZG in the treatment of ODUB.

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Dissecting the mechanism of Yuzhi Zhixue granule on ovulatory dysfunctional uterine bleeding by network pharmacology and molecular docking

Chinese Medicine ◽

10.1186/s13020-020-00392-0 ◽

2020 ◽

Vol 15 (1) ◽

Author(s):

Jialin Li ◽

Hua Luo ◽

Xinkui Liu ◽

Jingyuan Zhang ◽

Wei Zhou ◽

...

Keyword(s):

Molecular Docking ◽

Therapeutic Target ◽

Molecular Mechanisms ◽

Therapeutic Targets ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Uterine Bleeding ◽

Functional Enrichment ◽

Network Pharmacology ◽

Dysfunctional Uterine Bleeding

Abstract Background Yuzhi Zhixue Granule (YZG) is a traditional Chinese patent medicine for treating excessive menstrual flow caused by ovulatory dysfunctional uterine bleeding (ODUB) accompanied by heat syndrome. However, the underlying molecular mechanisms, potential targets, and active ingredients of this prescription are still unknown. Therefore, it is imperative to explore the molecular mechanism of YZG. Methods The active compounds in YZG were screened by the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). The putative targets of YZG were collected via TCMSP and Search Tool for Interacting Chemicals (STITCH) databases. The Therapeutic Target Database (TTD) and Pharmacogenomics Knowledgebase (PharmGKB) databases were used to identify the therapeutic targets of ODUB. A protein–protein interaction (PPI) network containing both the putative targets of YZG and known therapeutic targets of ODUB was built. Furthermore, bioinformatics resources from the database for annotation, visualization and integrated discovery (DAVID) were utilized for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Finally, molecular docking was performed to verify the binding effect between the YZG screened compounds and potential therapeutic target molecules. Results The study employed a network pharmacology method, mainly containing target prediction, network construction, functional enrichment analysis, and molecular docking to systematically research the mechanisms of YZG in treating ODUB. The putative targets of YZG that treat ODUB mainly involved PTGS1, PTGS2, ALOX5, CASP3, LTA4H, F7 and F10. The functional enrichment analysis suggested that the produced therapeutic effect of YZG against ODUB is mediated by synergistical regulation of several biological pathways, including apoptosis arachidonic acid (AA) metabolism, serotonergic synapse, complement and coagulation cascades and C-type lectin receptor signaling pathways. Molecular docking simulation revealed good binding affinity of the seven putative targets with the corresponding compounds. Conclusion This novel and scientific network pharmacology-based study holistically elucidated the basic pharmacological effects and the underlying mechanisms of YZG in the treatment of ODUB.

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Network Pharmacology Prediction: The Possible Mechanisms of Cinobufotalin against Osteosarcoma

Computational and Mathematical Methods in Medicine ◽

10.1155/2022/3197402 ◽

2022 ◽

Vol 2022 ◽

pp. 1-9

Author(s):

Riyu Chen ◽

Zeyi Guan ◽

Xianxing Zhong ◽

Wenzheng Zhang ◽

Ya Zhang

Keyword(s):

Survival Curve ◽

Therapeutic Targets ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Network Pharmacology ◽

Hub Genes ◽

Survival Prognosis ◽

Active Compounds ◽

Protein Protein Interaction

Objective. To explore the active compounds and targets of cinobufotalin (huachansu) compared with the osteosarcoma genes to obtain the potential therapeutic targets and pharmacological mechanisms of action of cinobufotalin on osteosarcoma through network pharmacology. Methods. The composition of cinobufotalin was searched by literature retrieval, and the target was selected from the CTD and TCMSP databases. The osteosarcoma genes, found from the GeneCards, OMIM, and other databases, were compared with the cinobufotalin targets to obtain potential therapeutic targets. The protein-protein interaction (PPI) network of potential therapeutic targets, constructed through the STRING database, was inputted into Cytoscape software to calculate the hub genes, using the NetworkAnalyzer. The hub genes were inputted into the Kaplan-Meier Plotter online database for exploring the survival curve. Functional enrichment analysis was identified using the DAVID database. Results. 28 main active compounds of cinobufotalin were explored, including bufalin, adenosine, oleic acid, and cinobufagin. 128 potential therapeutic targets on osteosarcoma are confirmed among 184 therapeutic targets form cinobufotalin. The hub genes included TP53, ACTB, AKT1, MYC, CASP3, JUN, TNF, VEGFA, HSP90AA1, and STAT3. Among the hub genes, TP53, ACTB, MYC, TNF, VEGFA, and STAT3 affect the patient survival prognosis of sarcoma. Through function enrichment analysis, it is found that the main mechanisms of cinobufotalin on osteosarcoma include promoting sarcoma apoptosis, regulating the cell cycle, and inhibiting proliferation and differentiation. Conclusion. The possible mechanisms of cinobufotalin against osteosarcoma are preliminarily predicted through network pharmacology, and further experiments are needed to prove these predictions.

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Network Pharmacology Reveals the Molecular Mechanism of Cuyuxunxi Prescription in Promoting Wound Healing in Patients with Anal Fistula

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2019/3865121 ◽

2019 ◽

Vol 2019 ◽

pp. 1-9 ◽

Cited By ~ 3

Author(s):

Yin Qu ◽

Zhijun Zhang ◽

Yafeng Lu ◽

De Zheng ◽

Yang Wei

Keyword(s):

Chinese Medicine ◽

Traditional Chinese Medicine ◽

Target Genes ◽

Herbal Medicines ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Network Pharmacology ◽

Surgical Wound ◽

Active Compounds

Background. The healing process of the surgical wound of anal fistulotomy is much slower because of the presence of stool within the wound. Cuyuxunxi (CYXX) prescription is a Chinese herbal fumigant that is being used to wash surgical wound after anal fistulotomy. This study aimed at investigating the molecular mechanism of CYXX prescription using a network pharmacology-based strategy. Materials and Methods. The active compounds in each herbal medicine were retrieved from the traditional Chinese medicine systems pharmacology (TCMSP) database and in Traditional Chinese Medicine Integrated Database (TCMID) analysis platform based on the criteria of oral bioavailability ≥40% and drug-likeness ≥0.2. The disease-related target genes were extracted from the Comparative Toxicogenomics Database. Protein-protein interaction network was built for the overlapped genes as well as functional enrichment analysis. Finally, an ingredient-target genes-pathway network was built by integrating all information. Results. A total of 375 chemical ingredients of the 5 main herbal medicines in CYXX prescription were retrieved from TCMSP database and TCMID. Among the 375 chemical ingredients, 59 were active compounds. Besides, 325 target genes for 16 active compounds in 3 herbal medicines were obtained. Functional enrichment analysis revealed that these overlapped genes were significantly related with immune response, biosynthesis of antibiotics, and complement and coagulation cascades. A comprehensive network which contains 133 nodes (8 disease nodes, 3 drug nodes, 8 ingredients, 103 target gene nodes, 7 GO nodes, and 4 pathway nodes) was built. Conclusion. The network built in this study might aid in understanding the action mechanism of CYXX prescription at molecular level to pathway level.

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Identifying Synergistic Mechanisms of Multiple Ingredients in Shuangbai Tablets against Proteinuria by Virtual Screening and a Network Pharmacology Approach

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2020/1027271 ◽

2020 ◽

Vol 2020 ◽

pp. 1-15

Author(s):

Xiaoqin Ma ◽

Meixiang Yu ◽

Chenxia Hao ◽

Wanhua Yang

Keyword(s):

Molecular Docking ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Functional Enrichment ◽

Network Pharmacology ◽

Pathway Enrichment Analysis ◽

Active Ingredients ◽

Human Phenotype ◽

Herbal Mixture ◽

Relationship Of

Shuangbai Tablets (SBT), a traditional herbal mixture, has shown substantial clinical efficacy. However, a systematic mechanism of its active ingredients and pharmacological mechanisms of action against proteinuria continues being lacking. A network pharmacology approach was effectual in discovering the relationship of multiple ingredients and targets of the herbal mixture. This study aimed to identify key targets, major active ingredients, and pathways of SBT against proteinuria by network pharmacology approach combined with thin layer chromatography (TLC). Human phenotype (HP) disease analysis, gene ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, and molecular docking were used in this study. To this end, a total of 48 candidate targets of 118 active ingredients of SBT were identified. Network analysis showed PTGS2, ESR1, and NOS2 to be the three key targets, and beta-sitosterol, quercetin, and berberine were the three major active ingredients; among them one of the major active ingredients, quercetin, was discriminated by TLC. These results of the functional enrichment analysis indicated that the most relevant disease including these 48 candidate proteins is proteinuria, SBT treated proteinuria by sympathetically regulating multiple biological pathways, such as the HIF-1, RAS, AGE-RAGE, and VEGF signaling pathways. Additionally, molecular docking validation suggested that major active ingredients of SBT were capable of binding to HIF-1A and VEGFA of the main pathways. Consequently, key targets, major active ingredients, and pathways based on data analysis of SBT against proteinuria were systematically identified confirming its utility and providing a new drug against proteinuria.

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Dissecting the Mechanism of Yuzhi Zhixue Granule on Ovulatory Dysfunctional Uterine Bleeding by Network Pharmacology and Molecular Docking

10.21203/rs.3.rs-45961/v3 ◽

2020 ◽

Author(s):

Jialin Li ◽

Hua Luo ◽

Xinkui Liu ◽

Jingyuan Zhang ◽

Wei Zhou ◽

...

Keyword(s):

Molecular Docking ◽

Therapeutic Target ◽

Molecular Mechanisms ◽

Therapeutic Targets ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Uterine Bleeding ◽

Functional Enrichment ◽

Network Pharmacology ◽

Dysfunctional Uterine Bleeding

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Gene Network Analysis of Alzheimer’s Disease Based on Network and Statistical Methods

Entropy ◽

10.3390/e23101365 ◽

2021 ◽

Vol 23 (10) ◽

pp. 1365

Author(s):

Chen Zhou ◽

Haiyan Guo ◽

Shujuan Cao

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Gene Network ◽

Functional Module ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Essential Genes ◽

Functional Enrichment ◽

Network Pharmacology ◽

Core Network

Gene network associated with Alzheimer’s disease (AD) is constructed from multiple data sources by considering gene co-expression and other factors. The AD gene network is divided into modules by Cluster one, Markov Clustering (MCL), Community Clustering (Glay) and Molecular Complex Detection (MCODE). Then these division methods are evaluated by network structure entropy, and optimal division method, MCODE. Through functional enrichment analysis, the functional module is identified. Furthermore, we use network topology properties to predict essential genes. In addition, the logical regression algorithm under Bayesian framework is used to predict essential genes of AD. Based on network pharmacology, four kinds of AD’s herb-active compounds-active compound targets network and AD common core network are visualized, then the better herbs and herb compounds of AD are selected through enrichment analysis.

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