scholarly journals Elucidation of the Mechanisms and Molecular Targets of Lianhuaqingwen for Treatment of COVID-19 Based on Network Pharmacology

2021 ◽  
Vol 9 (4) ◽  
pp. 111-122
Author(s):  
Yan Luo ◽  
Si-ting Gao ◽  
Jun-xiong Cheng ◽  
Wei-jian Xiong ◽  
Wen-Fu Cao
Keyword(s):  
Target Genes ◽  
Molecular Targets ◽  
Core Gene ◽  
Mechanisms Of Action ◽  
Network Pharmacology ◽  
Pathway Network ◽  
Functional Annotations ◽  
Gene Pathway ◽  
Protein Protein Interaction ◽  
Ppi Networks

Lianhuaqingwen (LH) is the widely used in the treatment of Coronavirus disease 2019 (COVID-19). However, its mechanisms of action and molecular targets for treatment of COVID-19 are not clear. The active compounds of LH were collected and their targets were identified through the network pharmacology. The mechanism of compound multi components and multi targets and its relationship with disease are analyzed. COVID-19 targets were obtained by analyzing with TCMSP. In total, 282 active ingredients and 510 targets of LH were identified. Twenty-one target genes associated with LH and COVID-19. Protein-protein interaction (PPI) data were then obtained and PPI networks of LH putative targets and COVID-19-related targets were visualized and merged to identify the candidate targets for LH against COVID-19. Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis were carried out. The gene-pathway network was constructed to screen the crucial target genes. The functional annotations of target genes were found to be related to immune regulation, host defense, inflammatory reaction and autoimmune diseases and so on. Twenty pathways including immunology, cancer, and cell processing were significantly enriched. Quercetin and luteolin might be the crucial ingredients. IL6 was the core gene and other several genes including IL1B, STAT1, IFNGR1, and NCF1 were the key genes in the gene-pathway network of LH for treatment of COVID-19. The results indicated that LH’s effects against COVID-19 might relate to regulation of immunological function through the specific biological processes and the related pathways. This study demonstrates the application of network pharmacology in evaluating mechanisms of action and molecular targets of complex herbal formulations.

scholarly journals Identification of the Active Constituents and Significant Pathways of Shen-qi-Yi-zhu Decoction on Antigastric Cancer: A Network Pharmacology Research and Experimental Validation

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Shuhong Zeng ◽  
Zhibao Yu ◽  
Xintian Xu ◽  
Yuanjie Liu ◽  
Jiepin Li ◽  
...  
Keyword(s):  
Experimental Validation ◽  
Target Genes ◽  
Cell Model ◽  
Network Pharmacology ◽  
Disease Network ◽  
Systematic Method ◽  
Protein Protein Interaction ◽  
Ppi Networks ◽  
Underlying Mechanisms

Shen-qi-Yi-zhu decoction (SQYZD) is an empirical prescription with antigastric cancer (GC) property created by Xu Jing-fan, a National Chinese Medical Master. However, its underlying mechanisms are still unclear. Based on network pharmacology and experimental verification, this study puts forward a systematic method to clarify the anti-GC mechanism of SQYZD. The active ingredients of SQYZD and their potential targets were acquired from the TCMSP database. The target genes related to GC gathered from GeneCards, DisGeNET, OMIM, TTD, and DrugBank databases were imported to establish protein-protein interaction (PPI) networks in GeneMANIA. Cytoscape was used to establish the drug-ingredients-targets-disease network. The hub target genes collected from the SQYZD and GC were parsed via GO and KEGG analysis. Our findings from network pharmacology were successfully validated using an in vitro HGC27 cell model experiment. In a word, this study proves that the combination of network pharmacology and in vitro experiments is effective in clarifying the potential molecular mechanism of traditional Chinese medicine (TCM).

scholarly journals Investigating the Mechanisms of Pollen Typhae in the Treatment of Diabetic Retinopathy Based on Network Pharmacology and Molecular Docking

2022 ◽  
Vol 2022 ◽  
pp. 1-14
Author(s):  
Rongrong Zhou ◽  
De Jin ◽  
Yuqing Zhang ◽  
Liyun Duan ◽  
Yuehong Zhang ◽  
...  
Keyword(s):  
Diabetic Retinopathy ◽  
Molecular Docking ◽  
Signaling Pathway ◽  
Target Genes ◽  
Network Pharmacology ◽  
Docking Analysis ◽  
Pathway Network ◽  
Gene Pathway ◽  
Vegf Signaling ◽  
Vegf Signaling Pathway

Objective. To explore the main bioactive compounds and investigate the underlying mechanism of Pollen Typhae (PT) against diabetic retinopathy (DR) by network pharmacology and molecular docking analysis. Methods. Bioactive ingredients and the target proteins of PT were obtained from TCMSP, and the related target genes were acquired from the SwissTargetPrediction database. The target genes of DR were obtained from GeneCards, TTD database, DisGeNET database, and DrugBank. The compound-target interaction network was established based on Cytoscape 3.7.2. The protein-protein interaction (PPI) network was constructed via STRING database and Cytoscape 3.7.2. Gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were visualized through DAVID database and Bioinformatics. Ingredient-gene-pathway network analysis was conducted to further screen the ingredients, target proteins, and pathways closely related to the biological mechanism on PT for DR, and molecular docking analysis was performed by SYBYL-X 2.1.1 software. Finally, the mechanism and underlying targets of PT in the treatment of DR were predicted. Results. A total of 8 compounds and 171 intersection targets were obtained based on the online network database. 7 main compounds were screened from compound-target network, and 53 targets including the top six key targets (PTGS2, AKT1, VEGFA, MAPK3, TNF, and EGFR) were further acquired from PPI analysis. The 53 key targets covered 80 signaling pathways, among which PI3K-Akt signaling pathway, focal adhesion, Rap1 signaling pathway, VEGF signaling pathway, and HIF-1 signaling pathway were closely connected with the biological mechanism involved in the alleviation of DR by PT. Ingredient-gene-pathway network shows that AKTI, EGFR, and VEGFA were core genes, kaempferol and isorhamnetin were pivotal ingredients, and VEGF signaling pathway and Rap1 signaling pathway were closely involved in anti-DR. The docking results indicated that five main compounds (arachidonic acid, isorhamnetin, quercetin, kaempferol, and (2R)-5,7-dihydroxy-2-(4-hydroxyphenyl)chroman-4-one) had good binding activity with EGFR and AKT1 targets. Conclusion. The active ingredients in PT may regulate the levels of inflammatory factors, suppress the oxidative stress, and inhibit the proliferation, migration, and invasion of retinal pericytes by acting on PTGS2, AKT1, VEGFA, MAPK3, TNF, and EGFR targets through VEGF signaling pathway, PI3K-Akt signaling pathway, Rap1 signaling pathway, and HIF-1 signaling pathway to play a therapeutic role in diabetic retinopathy.

scholarly journals Analysis of the Efficacy and Pharmacological Mechanisms of Action of Zhenren Yangzang Decoction on Ulcerative Colitis Using Meta-Analysis and Network Pharmacology

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Guosheng Xing ◽  
Yufeng Zhang ◽  
Xinlin Wu ◽  
Hua Wang ◽  
Yan Liu ◽  
...  
Keyword(s):  
Target Genes ◽  
Kegg Pathway ◽  
Meta Analysis ◽  
Mechanisms Of Action ◽  
Functional Enrichment ◽  
Network Pharmacology ◽  
Active Compounds ◽  
Pathway Enrichment ◽  
Active Target ◽  
Protein Protein Interaction

Objective. We analyzed the efficacy and pharmacological mechanisms of action of Zhen Ren Yang Zang decoction (ZRYZD) on ulcerative colitis (UC) using meta-analysis and network pharmacology. Methods. The major databases were searched for randomized controlled trials of ZRYZD for the treatment of UC. Meta-analysis of the efficacy of ZRYZD on UC was conducted using RevMan software. Active compounds and target genes were acquired using the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform. UC-related genes were searched using the GeneCards database. Gene Ontology (GO) functional enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using RGUI. A compound-target network was constructed using Cytoscape software, and a protein-protein interaction network was constructed using the STRING database. Molecular docking simulations of the macromolecular protein targets and their corresponding ligand compounds were performed using the AutoDock tool and AutoDock Vina software. Results. Meta-analysis revealed that the total effective rate and recovery rate of clinical efficacy were significantly higher in the experimental group than those of the control group. The screening identified 169 active compounds and 277 active target genes for ZRYZD. The 277 active target genes were compared with the 4,798 UC-related genes. This identified 187 active target genes of ZRYZD for UC that correlated with 138 active compounds. GO functional enrichment and KEGG pathway enrichment analyses were performed, and compound-target and protein-protein interaction networks were constructed. The key compounds and key target proteins were then selected. Finally, target protein binding with the corresponding compound was analyzed using molecular docking. Conclusion. Our findings demonstrate the effectiveness and safety of ZRYZD for the treatment of UC and provide insight into the underlying pharmacological mechanisms of action. Furthermore, key compounds were identified, laying the foundation for future studies on ZRYZD for the treatment of UC.

scholarly journals Uncovering Quercetin’s Effects against Influenza A Virus Using Network Pharmacology and Molecular Docking

Processes ◽  
2021 ◽  
Vol 9 (9) ◽  
pp. 1627
Author(s):  
Minjee Kim ◽  
Young Bong Kim
Keyword(s):  
Molecular Docking ◽  
Influenza A ◽  
Target Genes ◽  
Network Pharmacology ◽  
Binding Affinities ◽  
Anticancer Activities ◽  
Biological Targets ◽  
Protein Protein Interaction ◽  
Ppi Networks ◽  
Docking Method

(1) Background: Re-emerging influenza threats continue to challenge medical and public health systems. Quercetin is a ubiquitous flavonoid found in food and is recognized to possess antioxidant, anti-inflammatory, antiviral, and anticancer activities. (2) Methods: To elucidate the targets and mechanisms underlying the action of quercetin as a therapeutic agent for influenza, network pharmacology and molecular docking were employed. Biological targets of quercetin and target genes associated with influenza were retrieved from public databases. Compound–disease target (C-D) networks were constructed, and targets were further analyzed using KEGG pathway analysis. Potent target genes were retrieved from the compound–disease–pathway (C-D-P) and protein–protein interaction (PPI) networks. The binding affinities between quercetin and the targets were identified using molecular docking. (3) Results: The pathway study revealed that quercetin-associated influenza targets were mainly involved in viral diseases, inflammation-associated pathways, and cancer. Four targets, MAPK1, NFKB1, RELA, and TP53, were identified to be involved in the inhibitory effects of quercetin on influenza. Using the molecular docking method, we evaluated the binding affinity of each ligand (quercetin)–target and discovered that quercetin and MAPK1 showed the strongest calculated binding energy among the four ligand–target complexes. (4) Conclusion: These findings identified potential targets of quercetin and suggest quercetin as a potential drug for influenza treatment.

scholarly journals Determining Pharmacological Mechanisms of Chinese Incompatible Herbs Fuzi and Banxia in Chronic Obstructive Pulmonary Disease: A Systems Pharmacology-Based Study

2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Kaiwen Ni ◽  
Xiaolu Cai ◽  
Yaling Chen ◽  
Linshui Zhou ◽  
Ruilin Chen ◽  
...  
Keyword(s):  
Chronic Obstructive Pulmonary Disease ◽  
Pulmonary Disease ◽  
Target Genes ◽  
Network Pharmacology ◽  
Chronic Obstructive ◽  
Healthy Individuals ◽  
Obstructive Pulmonary Disease ◽  
Pathway Network ◽  
Gene Pathway ◽  
Copd Patients

Aconiti Lateralis Radix Praeparata (Fuzi) and Pinelliae Rhizoma (Banxia) are among the 18 incompatible medications that are forbidden from use in one formulation. However, there is increasing evidence implying that this prohibition is not entirely correct. According to the theory of Chinese traditional medicine, they can be used for the treatment of chronic obstructive pulmonary disease (COPD). Thus, we analyzed the possible approaches for the treatment of COPD using network pharmacology. The active compounds of Fuzi and Banxia (FB) were collected, and their targets were identified. COPD-related targets were obtained by analyzing the differentially expressed genes between COPD patients and healthy individuals, which were expressed using a Venn diagram of COPD and FB. Protein-protein interaction data and network regarding COPD and drugs used were obtained. Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis were conducted. The gene-pathway network was constructed to screen the key target genes. In total, 34 active compounds and 47 targets of FB were identified; moreover, 7,153 differentially expressed genes were identified between COPD patients and healthy individuals. The functional annotations of target genes were found to be related to mechanisms such as transcription, cytosol, and protein binding; furthermore, 68 pathways including neuroactive ligand-receptor interaction, Kaposi sarcoma-associated herpesvirus infection, apoptosis, and measles were significantly enriched. FOS CASP3, VEGFA, ESR1, and PTGS2 were the core genes in the gene-pathway network of FB for the treatment of COPD. Our results indicated that the effect of FB against COPD may involve the regulation of immunological function through several specific biological processes and their corresponding pathways. This study demonstrates the application of network pharmacology in evaluating mechanisms of action and molecular targets of herb-opponents FB.

scholarly journals Systematic elucidation of the pharmacological mechanisms of Rhynchophylline for treating epilepsy via network pharmacology

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Hua Geng ◽  
Xuqin Chen ◽  
Chengzhong Wang
Keyword(s):  
Gene Ontology ◽  
Oral Bioavailability ◽  
Target Genes ◽  
Interaction Analysis ◽  
Network Pharmacology ◽  
Receptor Interaction ◽  
Biological Processes ◽  
Pathway Network ◽  
Protein Protein Interaction ◽  
Network Analyses

Abstact Background Epilepsy, one of the most common neurological disorders, affects over 70 million people worldwide. Rhynchophylline displays a wide variety of pharmacologic actives. However, the pharmacologic effects of rhynchophylline and its mechanisms against epilepsy have not been systematically elucidated. Methods The oral bioavailability and druglikeness of rhynchophylline were evaluated using the Traditional Chinese Medicine Systems Pharmacology Database. Rhynchophylline target genes to treat epilepsy were identified using PharmMapper, SwissTargetPrediction and DrugBank databases integration. Protein-protein interaction analysis was carried out by utilizing the GeneMANIA database. WebGestalt was employed to perform Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses. The drug-disease-target-Gene Ontology-pathway network was constructed using Cytoscape. Results The oral bioavailability and druglikeness of rhynchophylline were calculated to be 41.82% and 0.57, respectively. A total of 20 rhynchophylline target genes related to epilepsy were chosen. Among the 20 genes and their interacting genes, 54.00% shared protein domains and 16.61% displayed co-expression characteristics. Gene ontology, Kyoto Encyclopedia of Genes and Genomes and network analyses illustrate that these targets were significantly enriched in regulation of sensory perception, morphine addiction, neuroactive ligand-receptor interaction and other pathways or biological processes. Conclusion In short, rhynchophylline targets multiple genes or proteins, biological processes and pathways. It shapes a multiple-layer network that exerts systematic pharmacologic activities on epilepsy.

Brief Survey of Biological Network Alignment and a Variant with Incorporation of Functional Annotations

2018 ◽  
Vol 14 (1) ◽  
pp. 4-10
Author(s):  
Fang Jing ◽  
Shao-Wu Zhang ◽  
Shihua Zhang
Keyword(s):  
Gene Ontology ◽  
Topological Structure ◽  
Metabolic Networks ◽  
Biological Network ◽  
Genomic Sequence ◽  
Network Alignment ◽  
Future Directions ◽  
Functional Annotations ◽  
Protein Protein Interaction ◽  
Ppi Networks

Background:Biological network alignment has been widely studied in the context of protein-protein interaction (PPI) networks, metabolic networks and others in bioinformatics. The topological structure of networks and genomic sequence are generally used by existing methods for achieving this task.Objective and Method:Here we briefly survey the methods generally used for this task and introduce a variant with incorporation of functional annotations based on similarity in Gene Ontology (GO). Making full use of GO information is beneficial to provide insights into precise biological network alignment.Results and Conclusion:We analyze the effect of incorporation of GO information to network alignment. Finally, we make a brief summary and discuss future directions about this topic.

scholarly journals Identification of Key Genes and miRNAs in Osteosarcoma Patients with Chemoresistance by Bioinformatics Analysis

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Binbin Xie ◽  
Yiran Li ◽  
Rongjie Zhao ◽  
Yuzi Xu ◽  
Yuhui Wu ◽  
...  
Keyword(s):  
Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Differentially Expressed ◽  
Pathway Enrichment Analysis ◽  
Regulation Of Transcription ◽  
Functional Annotations ◽  
Protein Protein Interaction ◽  
Ppi Networks ◽  
Search Tool ◽  
Poor Outcomes

Chemoresistance is a significant factor associated with poor outcomes of osteosarcoma patients. The present study aims to identify Chemoresistance-regulated gene signatures and microRNAs (miRNAs) in Gene Expression Omnibus (GEO) database. The results of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) included positive regulation of transcription, DNA-templated, tryptophan metabolism, and the like. Then differentially expressed genes (DEGs) were uploaded to Search Tool for the Retrieval of Interacting Genes (STRING) to construct protein-protein interaction (PPI) networks, and 9 hub genes were screened, such as fucosyltransferase 3 (Lewis blood group) (FUT3) whose expression in chemoresistant samples was high, but with a better prognosis in osteosarcoma patients. Furthermore, the connection between DEGs and differentially expressed miRNAs (DEMs) was explored. GEO2R was utilized to screen out DEGs and DEMs. A total of 668 DEGs and 5 DEMs were extracted from GSE7437 and GSE30934 differentiating samples of poor and good chemotherapy reaction patients. The Database for Annotation, Visualization, and Integrated Discovery (DAVID) was used to perform GO and KEGG pathway enrichment analysis to identify potential pathways and functional annotations linked with osteosarcoma chemoresistance. The present study may provide a deeper understanding about regulatory genes of osteosarcoma chemoresistance and identify potential therapeutic targets for osteosarcoma.

scholarly journals Identification and Classification of Hubs in microRNA Target Gene Networks in Human Neural Stem/Progenitor Cells following Japanese Encephalitis Virus Infection

mSphere ◽  
2019 ◽  
Vol 4 (5) ◽  
Author(s):  
Sriparna Mukherjee ◽  
Irshad Akbar ◽  
Reshma Bhagat ◽  
Bibhabasu Hazra ◽  
Arindam Bhattacharyya ◽  
...  
Keyword(s):  
Progenitor Cells ◽  
Gene Networks ◽  
Mirna Target ◽  
Target Gene ◽  
Target Genes ◽  
Hub Genes ◽  
Protein Protein Interaction ◽  
Ppi Networks ◽  
Neural Stem Progenitor Cells

ABSTRACT RNA viruses are known to modulate host microRNA (miRNA) machinery for their own benefit. Japanese encephalitis virus (JEV), a neurotropic RNA virus, has been reported to manipulate several miRNAs in neurons or microglia. However, no report indicates a complete sketch of the miRNA profile of neural stem/progenitor cells (NSPCs), hence the focus of our current study. We used an miRNA array of 84 miRNAs in uninfected and JEV-infected human neuronal progenitor cells and primary neural precursor cells isolated from aborted fetuses. Severalfold downregulation of hsa-miR-9-5p, hsa-miR-22-3p, hsa-miR-124-3p, and hsa-miR-132-3p was found postinfection in both of the cell types compared to the uninfected cells. Subsequently, we screened for the target genes of these miRNAs and looked for the biological pathways that were significantly regulated by the genes. The target genes involved in two or more pathways were sorted out. Protein-protein interaction (PPI) networks of the miRNA target genes were formed based on their interaction patterns. A binary adjacency matrix for each gene network was prepared. Different modules or communities were identified in those networks by community detection algorithms. Mathematically, we identified the hub genes by analyzing their degree centrality and participation coefficient in the network. The hub genes were classified as either provincial (P < 0.4) or connector (P > 0.4) hubs. We validated the expression of hub genes in both cell line and primary cells through qRT-PCR after JEV infection and respective miR mimic transfection. Taken together, our findings highlight the importance of specific target gene networks of miRNAs affected by JEV infection in NSPCs. IMPORTANCE JEV damages the neural stem/progenitor cell population of the mammalian brain. However, JEV-induced alteration in the miRNA expression pattern of the cell population remains an open question, hence warranting our present study. In this study, we specifically address the downregulation of four miRNAs, and we prepared a protein-protein interaction network of miRNA target genes. We identified two types of hub genes in the PPI network, namely, connector hubs and provincial hubs. These two types of miRNA target hub genes critically influence the participation strength in the networks and thereby significantly impact up- and downregulation in several key biological pathways. Computational analysis of the PPI networks identifies key protein interactions and hubs in those modules, which opens up the possibility of precise identification and classification of host factors for viral infection in NSPCs.

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

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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