scholarly journals A Network Pharmacology Approach for Exploring the Mechanisms of Panax notoginseng Saponins in Ischaemic Stroke

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Cong Wang ◽  
Hao Chen ◽  
Shi-tang Ma ◽  
Bin-bin Mao ◽  
Yu Chen ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Ischaemic Stroke ◽  
Panax Notoginseng ◽  
Docking Studies ◽  
Network Pharmacology ◽  
Therapeutic Effects ◽  
Panax Notoginseng Saponins ◽  
Ginsenoside Re ◽  
Molecular Docking Studies ◽  
Ppi Networks

Background. Panax notoginseng saponins (PNS) have been deemed effective herb compounds for treating ischaemic stroke (IS) and improving the quality of life of IS patients. This study aimed to investigate the underlying mechanisms of PNS in the treatment of IS based on network pharmacology. Methods. PNS were identified from the Traditional Chinese Medicine System Pharmacology (TCMSP) database, and their possible targets were predicted using the PharmMapper database. IS-related targets were identified from the GeneCards database, OMIM database, and DisGeNET database. A herb-compound-target-disease network was constructed using Cytoscape, and protein-protein interaction (PPI) networks were established with STRING. GO enrichment and KEGG pathway analysis were performed using DAVID. The binding of the compounds and key targets was validated by molecular docking studies using AutoDock Vina. The neuroprotective effect of TFCJ was substantiated in terms of oxidative stress (superoxide dismutase, glutathione peroxidase, catalase, and malondialdehyde) and the levels of IGF1/PI3K/Akt pathway proteins. Results. A total of 375 PNS targets and 5111 IS-related targets were identified. Among these targets, 241 were common to PNS, and IS network analysis showed that MAPK1, AKT1, PIK3R1, SRC, MAPK8, EGFR, IGF1, HRAS, RHOA, and HSP90AA1 are key targets of PNS against IS. Furthermore, GO and KEGG enrichment analysis indicated that PNS probably exert therapeutic effects against IS by regulating many pathways, such as the Ras, oestrogen, FoxO, prolactin, Rap1, PI3K-Akt, insulin, PPAR, and thyroid hormone signalling pathways. Molecular docking studies further corroborated the experimental results.The network pharmacology results were further verified by molecular docking and in vivo experiments. Conclusions. The ameliorative effects of PNS against IS were predicted to be associated with the regulation of the IGF1-PI3K-Akt signalling pathway. Ginsenoside Re and ginsenoside Rb1 may play an important role in the treatment of IS.

scholarly journals Elucidating the Effects of Curcumin against Influenza Using In Silico and In Vitro Approaches

2021 ◽  
Vol 14 (9) ◽  
pp. 880
Author(s):  
Minjee Kim ◽  
Hanul Choi ◽  
Sumin Kim ◽  
Lin Woo Kang ◽  
Young Bong Kim
Keyword(s):  
Influenza Virus ◽  
Molecular Docking ◽  
Mdck Cells ◽  
Influenza Infection ◽  
Network Pharmacology ◽  
Therapeutic Effects ◽  
In Vitro Experiments ◽  
Target Interaction ◽  
Ppi Networks

The influenza virus is a constantly evolving pathogen that challenges medical and public health systems. Traditionally, curcumin has been used to treat airway inflammatory diseases, such as bronchitis and pneumonia. To elucidate common targets of curcumin and influenza infection and underlying mechanisms, we employed network pharmacology and molecular docking approaches and confirmed results using in vitro experiments. Biological targets of curcumin and influenza were collected, and potential targets were identified by constructing compound–disease target (C-D) and protein–protein interaction (PPI) networks. The ligand–target interaction was determined using the molecular docking method, and in vitro antiviral experiments and target confirmation were conducted to evaluate curcumin’s effects on influenza. Our network and pathway analyses implicated the four targets of AKT1, RELA, MAPK1, and TP53 that could be involved in the inhibitory effects of curcumin on influenza. The binding energy calculations of each ligand–target interaction in the molecular docking showed that curcumin bound to AKT1 with the highest affinity among the four targets. In vitro experiments, in which influenza virus-infected MDCK cells were pre-, co-, or post-treated with curcumin, confirmed curcumin’s prophylactic and therapeutic effects. Influenza virus induction increased the level of mRNA expression of AKT in MDCK cells, and the level was attenuated by curcumin treatment. Collectively, our findings identified potential targets of curcumin against influenza and suggest curcumin as a potential therapy for influenza infection.

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.

Homology Modeling of Mus Musculus CDK5 and Molecular Docking Studies with Flavonoids

2017 ◽  
Vol 9 (6) ◽  
Author(s):  
Sowmya Suri ◽  
Rumana Waseem ◽  
Seshagiri Bandi ◽  
Sania Shaik
Keyword(s):  
Molecular Docking ◽  
3D Model ◽  
Structural Features ◽  
Docking Studies ◽  
Amino Acid Residues ◽  
Cyclin Dependent Kinase ◽  
Ligand Complex ◽  
Ligand Interaction ◽  
Molecular Docking Studies ◽  
Cyclin Dependent Kinase 5

A 3D model of Cyclin-dependent kinase 5 (CDK5) (Accession Number: Q543f6) is generated based on crystal structure of P. falciparum PFPK5-indirubin-5-sulphonate ligand complex (PDB ID: 1V0O) at 2.30 Å resolution was used as template. Protein-ligand interaction studies were performed with flavonoids to explore structural features and binding mechanism of flavonoids as CDK5 (Cyclin-dependent kinase 5) inhibitors. The modelled structure was selected on the basis of least modeler objective function. The model was validated by PROCHECK. The predicted 3D model is reliable with 93.0% of amino acid residues in core region of the Ramachandran plot. Molecular docking studies with flavonoids viz., Diosmetin, Eriodictyol, Fortuneletin, Apigenin, Ayanin, Baicalein, Chrysoeriol and Chrysosplenol-D with modelled protein indicate that Diosmetin is the best inhibitor containing docking score of -8.23 kcal/mol. Cys83, Lys89, Asp84. The compound Diosmetin shows interactions with Cys83, Lys89, and Asp84.

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