scholarly journals Integrated network pharmacology and molecular docking approaches to reveal the synergistic mechanism of multiple components in Venenum Bufonis for ameliorating heart failure

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e10107
Author(s):  
Wei Ren ◽  
Zhiqiang Luo ◽  
Fulu Pan ◽  
Jiali Liu ◽  
Qin Sun ◽  
...  
Keyword(s):  
Heart Failure ◽  
Molecular Docking ◽  
Docking Studies ◽  
Network Pharmacology ◽  
Active Components ◽  
Integrated Network ◽  
Multiple Components ◽  
Therapeutic Mechanism ◽  
Synergistic Mechanism ◽  
Leading Compounds

Venenum Bufonis (VB), also called Chan Su in China, has been extensively used as a traditional Chinese medicine (TCM) for treating heart failure (HF) since ancient time. However, the active components and the potential anti-HF mechanism of VB remain unclear. In the current study, the major absorbed components and metabolites of VB after oral administration in rats were first collected from literatures. A total of 17 prototypes and 25 metabolites were gathered. Next, a feasible network-based pharmacological approach was developed and employed to explore the therapeutic mechanism of VB on HF based on the collected constituents. In total, 158 main targets were screened out and considered as effective players in ameliorating HF. Then, the VB components–main HF putative targets–main pathways network was established, clarifying the underlying biological process of VB on HF. More importantly, the main hubs were found to be highly enriched in adrenergic signalling in cardio-myocytes. After verified by molecular docking studies, four key targets (ATP1A1, GNAS, MAPK1 and PRKCA) and three potential active leading compounds (bufotalin, cinobufaginol and 19-oxo-bufalin) were identified, which may play critical roles in cardiac muscle contraction. This study demonstrated that the integrated strategy based on network pharmacology and molecular docking was helpful to uncover the synergistic mechanism of multiple constituents in TCM.

scholarly journals Revealing Synergistic Mechanism of Multiple Components in Gandi Capsule for Diabetic Nephropathy Therapeutics by Network Pharmacology

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Jian Zhang ◽  
Qiqiang Zhang ◽  
Xiaofei Chen ◽  
Yan Liu ◽  
Jiyang Xue ◽  
...  
Keyword(s):  
Diabetic Nephropathy ◽  
Interaction Network ◽  
Network Pharmacology ◽  
Active Components ◽  
Multiple Components ◽  
Uniprotkb Database ◽  
Synergistic Mechanism ◽  
Compound Database ◽  
Main Action ◽  
Herbal Medicinal

Gandi capsule, a traditional Chinese herbal medicinal formulation that consists of eight herbs, is used as a clinical therapy for diabetic nephropathy. To clarify the potential synergistic mechanism, this study adopted a network pharmacology strategy to screen the action targets that corresponded to the active components in the Gandi capsule. We first constructed a compound database of 315 components in the Gandi capsule and a target database of diabetic nephropathy, which included 155 target proteins. Six representative compounds were selected to dock with 99 proteins found in the UniProtKB database with their PDB code, and interaction networks between the active ingredients of the Gandi capsule and their targets were mapped out. Results revealed 47 proteins with a high affinity with at least one compound molecule in the Gandi capsule. The main action pathways closely related to the development of diabetic nephropathy were the TGF-β1, AMPK, insulin, TNF-α, and lipid metabolism pathways as per network pharmacology analysis. In the interaction network, ACC1, SOD2, COX2, PKC-B, IR, and ROCK1 proteins had the most frequent interactions with the six compounds. We performed visual molecular docking in silico and experimentally confirmed competitive component-protein binding by SPR and an enzyme activity test, which highlighted the relationships of wogonin to COX2 and SOD2, astragaloside IV to ACC1, and morroniside to ACC1. We concluded that the potential synergistic mechanism of the Gandi capsule resulted from high affinities with multiple proteins and intervention in multiple pathways in combination therapy of diabetic nephropathy.

scholarly journals Mechanism of Cordyceps Cicadae in Treating Diabetic Nephropathy Based on Network Pharmacology and Molecular Docking Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Yi Qian ◽  
Xin Sun ◽  
Xin Wang ◽  
Xin Yang ◽  
Mengyao Fan ◽  
...  
Keyword(s):  
Diabetic Nephropathy ◽  
Molecular Docking ◽  
Docking Studies ◽  
New Drugs ◽  
Network Pharmacology ◽  
Active Components ◽  
Docking Analysis ◽  
Discovery Studio ◽  
Cordyceps Cicadae ◽  
Molecular Docking Analysis

Objective. To systematically study the mechanism of cordyceps cicadae in the treatment of diabetic nephropathy (DN) with the method of network pharmacology and molecular docking analysis, so as to provide theoretical basis for the development of new drugs for the treatment of DN. Methods. TCMSP, Symmap, PubChem, PubMed, and CTD database were used to predict and screen the active components and therapeutic targets for DN. The network of active components and targets was drawn by Cytoscape 3.6.0, the protein-protein interaction (PPI) was analyzed by the STRING database, and the DAVID database was used for the enrichment analysis of intersection targets. Molecular docking studies were finished by Discovery Studio 3.5. Results. A total of 36 active compounds, including myriocin, guanosine, and inosine, and 378 potential targets of cordyceps cicadae were obtained. PPI network analysis showed that AKT1, MAPK8, and TP53 and other targets were related to both cordyceps cicadae and DN. GO and KEGG pathway analysis showed that these targets were mostly involved in R-HSA-450341, 157.14-3-3 cell cycle, and PDGF pathways. Docking studies suggested that myriocin can fit in the binding pocket of two target proteins (AKT1 and MAPK8). Conclusion. Active ingredients of cordyceps cicadae such as myriocin may act on DN through different targets such as AKT1, MAPK8, and TP53 and other targets, which can help to develop innovative drugs for effective treatment of DN.

scholarly journals Network Pharmacology Integrated Molecular Docking Reveals The Mechanism of Huanglian Wendan Decotion Against Metabolic Syndrome

2020 ◽  
Author(s):  
Junli Bao ◽  
Xinyuan Gao ◽  
Yubo Han ◽  
Ke Zhang ◽  
Li Liu
Keyword(s):  
Metabolic Syndrome ◽  
Molecular Docking ◽  
Cellular Response ◽  
Enrichment Analysis ◽  
Docking Studies ◽  
Network Pharmacology ◽  
Pathway Enrichment Analysis ◽  
Core Network ◽  
Active Components ◽  
R Program

Abstract Background: Metabolic syndrome (MetS) is a group of abnormalities which includes abdominal obesity, hypertension, insulin resistance, and dyslipidemia. Many clinical studies showed that Huanglian Wendan Decoction(HWD) is effective in the treatment of MetS.Methods: In this study, the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database, STITCH database and Swisstargetpredicition database were used to excavate the active components of HWD and to predict the potential targets. The key targets of MetS are screened through GeneCards database and DisGeNET database. Moreover, we obtained the overlapping target of HWD and MetS based on venndiagram of "R program". Next, we performed enrichment analysis for common-target network and protein-protein interaction (PPI) network. Afterwards, Cytoscape was used to construct the components-targets core network for HWD in treating MetS, and R program was used to perform GO-BP and KEGG pathway enrichment analysis on these core targets. Last, we further investigated our predictions of crucial targets by performing molecular docking studies with components of HWD.Results: The component-target core network of HWD against MetS was screened to contain 22 active components, which corresponded to 77 core targets. Additionally, enrichment analysis suggested that targets of HWD against MetS were mainly clustered into multiple biological processes (response to nutrient levels, gland development, response to steroid hormone, cellular response to oxidative stress, reproductive structure development etc and related pathways (AGE-RAGE, AMPK, JAK-STAT, MAPK), indicating the underlying mechanisms of HWD on MetS. The results of molecular docking showed that beta-sitost, naringenin, berberine and baicalein bound well to IL6 and AKT1.Conclusion: The network pharmacological strategy integrated molecular docking to explore the mechanism of HWD against MetS. Our present outcomes might shed light on the further clinical application of HWD on MetS treatment.

scholarly journals Network Pharmacology Integrated Molecular Docking Reveals the Anti-COVID-19 Mechanism of Xingnaojing Injection

2020 ◽  
Vol 15 (12) ◽  
pp. 1934578X2097802
Author(s):  
Bing Yu ◽  
Xin-Ge Ke ◽  
Chong Yuan ◽  
Peng-Yu Chen ◽  
Ying Zhang ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Signaling Pathway ◽  
Growth Factor Receptor ◽  
Docking Studies ◽  
Mitogen Activated Protein Kinase ◽  
Network Pharmacology ◽  
Active Components ◽  
Molecular Docking Studies ◽  
Discovery Studio ◽  
Xingnaojing Injection

In the process of fighting against COVID-19 in China, Xingnaojing injection has been recommended for its clinical treatment, but the information about its active components and mechanism is still lacking. Therefore, in this work, using network pharmacology and molecular docking, we studied the active components of Xingnaojing injection having anti-COVID-19 properties. Using the DL parameter, TCMSP and CNKI databases were used to screen the active components of the Xingnaojing injection. Then, the SwissTargetPrediction webserver was used to collect the corresponding gene targets, and the gene targets related to COVID-19 were searched in the Genecards database. The DAVID database was used to enrich the function of gene targets, and the KOBAS3.0 database for the annotation of related KEGG pathways. The “components–targets–pathways” network of Xingnaojing injection was constructed with Cytoscape 3.6.1 software. The protein–protein interaction networks were analyzed using the String database. Specific proteins, SARS-COV-2 3 Cl, ACE2, and the active components were imported into Discovery Studio 2016 Client for molecular docking studies. From the Xingnaojing injection, a total of 58 active components, including Divanillalaceton and Q27139023, were screened. These were linked to 53 gene targets including mitogen-activated protein kinase 1 (MAPK1), tumor necrosis factorTNF, epidermal growth factor receptor, MAPK3, and 196 signaling pathways related to COVID-19, such as apoptosis, C-type lectin receptor signaling pathway, and hypoxia-inducible factor 1 signaling pathway. Furthermore, molecular docking studies were performed to study potential binding between the key targets and selected active components. Xingnaojing injection exhibits anti-COVID-19 effects via multiple components, multiple targets, and multiple pathways. These results set a scientific basis for further elucidation of the anti-COVID-19 mechanism of Xingnaojing injection.

scholarly journals Network Pharmacology Integrated Molecular Docking Reveals the Anti-COVID-19 and SARS Mechanism of Fufang Banlangen Keli

2021 ◽  
Vol 16 (1) ◽  
pp. 1934578X2098842
Author(s):  
Li Cheng ◽  
Fei Wang ◽  
Shun Bo Zhang ◽  
Qiu Yun You
Keyword(s):  
Molecular Docking ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Docking Studies ◽  
Functional Enrichment ◽  
Network Pharmacology ◽  
Active Components

Purpose Fufang Banlangen Keli (FBK) has been recommended for its clinical treatment of Coronavirus disease 2019 (COVID-19) and severe acute respiratory syndrome (SARS), but the mechanism of action is unclear. So, using network pharmacology and molecular docking, we studied the active components and mechanism of FBK in the treatment of COVID-19 and SARS. Methods The Encyclopedia of Traditional Chinese Medicine and Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform were used to screen the active components by oral bioactivity and drug likeness. Then, PharmMapper and SwissTargetPrediction databases were used to screen potential target genes of active components; the related target genes of COVID-19 and SARS were obtained from the GeneCards database. The intersection of the active components and disease-related targets was performed by the Venny2.1.0 database. The DAVID6.8 database and KOBAS3.0 database were used to get gene ontology (GO) function enrichment and Kyoto Encyclopedia of Genes and Genomes pathway annotation of gene targets. The “components-targets-pathways (C-T-P)” network of FBK was conducted by Cytoscape3.6.1 software. The top active components, angiotensin-converting enzyme 2 (ACE2) and SARS-CoV-2 3 Cl, were imported into AutoDock and PyMOL for molecular docking. Results From the FBK, a total of 28 active components and 73 gene targets were screened through network pharmacology. Twenty pathways were analyzed, including pathways in cancer, nod-like receptor signaling pathway, and pancreatic cancer, etc. ( P < 0.05). A total of 337 items were obtained by GO functional enrichment analysis ( P < 0.05), including 257 items for biological process, 38 items for cell composition, and 42 items for molecular function. Furthermore, molecular docking studies were performed to study potential binding between the key gene targets and selected active components. Conclusion Based on network pharmacology and molecular docking technology, qingdainone, (2Z)-2-(2-oxoindolin-3-ylidene) indolin-3-one, sinensetin, and acacetin in FBK were verified to bind to ACE2 and SARS-COV-2 3 Cl, so as to treat COVID-19 and SARS.

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