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 Application of Network Pharmacology to Elucidate The Potential Mechanism of Finger Citron Against Obesity

2020 ◽  
Author(s):  
Zhen Wu ◽  
Yujiao Yang ◽  
Yao Wei ◽  
Xu-guang Hu
Keyword(s):  
Molecular Docking ◽  
Signaling Pathways ◽  
Target Genes ◽  
Chinese Herbs ◽  
Network Pharmacology ◽  
Potential Mechanism ◽  
Active Components ◽  
Docking Analysis ◽  
Treatment Of Obesity ◽  
Molecular Docking Analysis

Abstract Background: Finger citron (FS) is one of many traditional Chinese herbs that have been used to treat obesity. However, the active components and potential targets of FS in improving obesity remain unclear. Methods：The aim of this study was to elucidate the pharmacological effects and mechanisms of FS on obesity using network pharmacology analysis. We used network pharmacology to determine the active components, potential targets and mechanisms in the treatment of obesity.Results：We identified 25 active ingredients of FS such as diosmetin, hesperidin and sitosterol-alpha1 with important biological effect. A total of 258 key targets were screened, containing TNF，NOS2, MAPK8 which were found to be enriched in 27 signaling pathways, such as apoptosis, TNF, PPAR and AKT1, and Insulin resistance signaling pathways. Moreover, molecular docking analysis showed that the main ingredients were tightly bound to the core targets, further confirming the effects of weight loss. Conclusion: Based on network pharmacology and molecular docking analysis, our study provides insights into the potential mechanism of FS in ameliorating obesity after screening for associated key target genes and signaling pathways. These findings further provide a theoretical basis for further pharmacological research into the potential mechanism of FS in treating obesity.

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 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.

In silico investigation by conceptual DFT and molecular docking of antitrypanosomal compounds for understanding cruzain inhibition

2016 ◽  
Vol 15 (03) ◽  
pp. 1650021 ◽  
Author(s):  
Toufik Salah ◽  
Salah Belaidi ◽  
Nadjib Melkemi ◽  
Ismail Daoud ◽  
Salima Boughdiri
Keyword(s):  
Molecular Docking ◽  
Density Functional ◽  
Current Knowledge ◽  
Protozoan Parasite ◽  
Binding Mode ◽  
New Drugs ◽  
Conceptual Density Functional Theory ◽  
Docking Analysis ◽  
Life Threatening Illness ◽  
Molecular Docking Analysis

Current knowledge about Chagas disease, the potentially life-threatening illness caused by the protozoan parasite (Trypanosoma cruzi), has led to the development of new drugs and the understanding of their mode of action. The Conceptual Density-Functional Theory was applied to determine the active center sites of trypanocidal compounds, extended by the Molecular Docking analysis to identify the most favorable ligand conformation when bound to the active site of cruzain. Results such as CHELPG charges, Fukui function, MESP, and Molecular Docking analysis are reported and discussed in the present investigation. Whereas, a close agreement with experimental results was found to explain the possibility of studying the receptor-binding mode using these different axes.

scholarly journals Novel inhibitors designing against the potential drug target of Plasmodium falciparum M17 Leucyl Aminopeptidase - PfM17LAP

2021 ◽  
Author(s):  
Govinda Rao Dabburu ◽  
Manish Kumar ◽  
Naidu Subbarao
Keyword(s):  
Plasmodium Falciparum ◽  
Molecular Docking ◽  
Drug Target ◽  
Docking Studies ◽  
Simulation Studies ◽  
Docking Analysis ◽  
Discovery Studio ◽  
Potential Inhibitors ◽  
Key Words Malaria ◽  
Leucyl Aminopeptidase

Abstract: Malaria is one of the major disease of concern worldwide especially in the African regions. According to the recent WHO reports, African regions share 95% of the total deaths worldwide that occurs due to malaria. Plasmodium falciparum M17 Leucyl Aminopeptidase (PfM17LAP) plays an important role in the regulation of amino acids release and for the survival of the parasite. We performed molecular docking and simulation studies to find the potential inhibitors against PfM17LAP using ChEMBL antimalarial library. Molecular docking studies and post-docking analysis revealed that molecules CHEMBL369831 and CHEMBL176888 showed better binding than the reference molecule BESTATIN. LibDock and X-SCORES of molecules BES, CHEMBL369831 and CHEMBL176888 are 130.071, 230.38, 223.56 and -8.75 Kcal/mol, -10.90 Kcal/mol, -11.05 Kcal/mol respectively. ADMET profiling of the top ten ranked molecules was done by using the Discovery Studio. Molecular dynamic studies revealed that the complex PfM17LAP-CHEMBL369831 is stable throughout the simulation. Finally, we have reported novel inhibitors which possess more binding affinity towards PfM17LAP. Key words: Malaria, M17 Leucyl Aminopeptidase, ADMET, X-SCORE

scholarly journals Computational Molecular Docking Analysis and Visualisation of Anthocyanins for Anticancer Activity

2021 ◽  
Vol 8 (1) ◽  
pp. 154-161
Author(s):  
Mahankali Sravani ◽  
Akash Kumaran ◽  
Aditi Tulshiram Dhamdhere ◽  
Nachimuthu Senthil Kumar
Keyword(s):  
Molecular Docking ◽  
Anticancer Activity ◽  
Complex Compounds ◽  
Potential Drug ◽  
Drug Molecule ◽  
Docking Analysis ◽  
Discovery Studio ◽  
Almost All ◽  
Molecular Docking Analysis ◽  
Computational Molecular Docking

Various invitro and computational methods were implemented to evaluate the anticancer potential of anthocyanidins, namely cyanidin, malvidin, delphinidin, peonidin, pelargonidin, and petunidin. These anthocyanidins were docked with CDK-2, CDK-6 and IGF-1R kinase proteins. Additionally, known inhibitors (KIs) such as SU9516, Palbociclib, OSI-906 are compared with their respective macromolecules, including, CDK-2, CDK-6 and IGF-1R kinase, in to compare results of the study based on Lipinski rule of 5.  The Auto Dock Tool (Autodock 4) was used for molecular docking, and the docked complex compounds were visualised and interpreted using the Bio via Discovery Studio 2020 client. The Docking results obtained showed a very good inhibitory binding to almost all the selected cancer proteins, and these compounds might be a potential drug molecule.

scholarly journals A Network Pharmacology and Molecular Docking Approach to Investigate the Anticoronavirus-Induced Diseases Effect of Yinqiao Powder Combined With Modified Sangju Decoction

2021 ◽  
Vol 16 (9) ◽  
pp. 1934578X2110352
Author(s):  
Tian-Shun Wang ◽  
Xing-Pan Wu ◽  
Qiu-Yuan Jian ◽  
Yan-Fang Yang ◽  
Wu He-Zhen
Keyword(s):  
Molecular Docking ◽  
Signaling Pathway ◽  
Treatment Strategies ◽  
Interaction Network ◽  
Mitogen Activated Protein Kinase ◽  
Network Pharmacology ◽  
Common Mechanism ◽  
Active Components ◽  
Discovery Studio ◽  
The Core

Severe acute respiratory syndrome (SARS) once caused great harm in China, but now it is the coronavirus disease 2019 (COVID-19) pandemic that has become a huge threat to global health, which raises urgent demand for developing effective treatment strategies to avoid the recurrence of tragedies. Yinqiao powder, combined with modified Sangju decoction (YPCMSD), has been clinically proven to have a good therapeutic effect on COVID-19 in China. This study aimed to analyze the common mechanism of YPCMSD in the treatment of SARS and COVID-19 through network pharmacology and molecular docking and further explore the potential application value of YPCMSD in the treatment of coronavirus infections. Firstly, the active components were collected from the literature and Traditional Chinese Medicine Systems Pharmacology database platform. The COVID-19 and SARS associated targets of the active components were forecasted by the SwissTargetPrediction database and GeneCards. A protein–protein-interaction network was drawn and the core targets were obtained by selecting the targets larger than the average degree. By importing the core targets into database for annotation, visualization, and integrated discovery, enrichment analysis of gene ontology, and construction of a Kyoto Encyclopedia of genes and genomes pathway was conducted. Cytoscape 3.6.1 software was used to construct a “components–targets–pathways” network. Active components were selected to dock with acute respiratory syndrome coronavirus type 2 (SARS-COV-2) 3CL and angiotensin-converting enzyme 2 (ACE2) through Discovery Studio 2016 software. A network of “components–targets–pathways” was successfully constructed, with key targets involving mitogen-activated protein kinase 1, caspase-3 (CASP3), tumor necrosis factor (TNF), and interleukin 6. Major metabolic pathways affected were those in cancer, the hypoxia-inducible factor 1 signaling pathway, the TNF signaling pathway, the Toll-like receptor signaling pathway, and the PI3K-Akt signaling pathway. The core components, such as arctiin, scopolin, linarin, and isovitexin, showed a strong binding ability with SARS-COV-2 3CL and ACE2. We predicted that the mechanism of action of this prescription in the treatment of COVID-19 and SARS might be associated with multicomponents that bind to SARS-COV-2 3CL and ACE2, thereby regulating targets that coexpressed with them and pathways related to inflammation and the immune system.

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