Bioactive compound 1,8-Cineole selectively induces G2/M arrest in A431 cells through the upregulation of the p53 signaling pathway and molecular docking studies

Phytomedicine ◽  
2018 ◽  
Vol 46 ◽  
pp. 57-68 ◽  
Author(s):  
Sowndarya Sampath ◽  
Sangeetha Subramani ◽  
Sridevi Janardhanam ◽  
Preethi Subramani ◽  
Arun Yuvaraj ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Signaling Pathway ◽  
Bioactive Compound ◽  
Docking Studies ◽  
A431 Cells ◽  
Molecular Docking Studies ◽  
P53 Signaling ◽  
P53 Signaling Pathway

The Molecular Docking of Flavonoids Isolated from Daucus carota as a Dual Inhibitor of MDM2 and MDMX

2020 ◽  
Vol 15 (2) ◽  
pp. 154-164 ◽  
Author(s):  
Ijaz Muhammad ◽  
Noor Rahman ◽  
Gul E. Nayab ◽  
Sadaf Niaz ◽  
Mohibullah Shah ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Cancer Therapy ◽  
Natural Product ◽  
Signaling Pathway ◽  
In Silico ◽  
P53 Protein ◽  
Dual Inhibitor ◽  
P53 Signaling ◽  
In Silico Studies ◽  
P53 Signaling Pathway

Background: Cancer is characterized by overexpression of p53 associated proteins, which down-regulate P53 signaling pathway. In cancer therapy, p53 activity can be restored by inhibiting the interaction of MDMX (2N0W) and MDM2 (4JGR) proteins with P53 protein. Objective: In the current, study in silico approaches were adapted to use a natural product as a source of cancer therapy. Methods: In the current study in silico approaches were adapted to use a natural product as a source of cancer therapy. For in silico studies, Chemdraw and Molecular Operating Environment were used for structure drawing and molecular docking, respectively. Flavonoids isolated from D. carota were docked with cancerous proteins. Result: Based on the docking score analysis, we found that compound 7 was the potent inhibitor of both cancerous proteins and can be used as a potent molecule for inhibition of 2N0W and 4JGR interaction with p53. Conclusion: Thus the compound 7 can be used for the revival of p53 signaling pathway function however, intensive in vitro and in vivo experiments are required to prove the in silico analysis.

scholarly journals Molecular Mechanisms of Notopterygii Rhizoma Et Radix for the Treatment of Arrhythmia Based on Network Pharmacology

2021 ◽  
Author(s):  
PL Wei ◽  
Yifei Qi ◽  
Yupei Tan ◽  
Dehuai Long ◽  
Wenlong Xing ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Signaling Pathway ◽  
Venn Diagram ◽  
Network Pharmacology ◽  
Qrt Pcr ◽  
Apoptotic Process ◽  
P53 Signaling ◽  
P53 Signaling Pathway

Abstract Background Many experiments showed that Notopterygii Rhizoma Et Radix (NRR) can resist arrhythmia, but the mechanism of its action has not clear. Here, we investigated the possible mechanisms of NRR by network pharmacology and molecular docking and verified them experimentally. Methods Active componds and targets of NRR were retrieved by the Traditional Chinese Medicine Systems Pharmacology (TCMSP) Database andAnalysis Platform, SymMap, and the Encyclopedia of Traditional Chinese Medicine (ETCM) databases. Arrhythmia-related targets were acquired from Comparative Toxicogenomics Database (CTD) and GeneCards databases. Overlapping targets of NRR associated with arrhythmia were acquired via Venn diagram. DAVID was applied for GO and KEGG pathway analyses. Cytoscape software and its plug-in were used for PPI network construction, module division and hub nodes screening. AutoDock Vina and qRT-PCR were carried out for validation. Results The 21 active compounds and 57 targets were obtained. Of these, coumarin was the predominant category including 15 components and 31 targets. The 5 key targets of NRR in treating arrhythmia, and these targets are involved in the apoptotic process, extrinsic apoptotic signaling pathway in absence of ligand, endopeptidase activity involved in apoptotic process by cytochrome c. The main pathways are p53 signaling pathway, Hepatitis B and Apoptosis. The results of molecular docking and qRT-PCR display good effect on hub node regulation in NRR treatment. Conclusion NRR plays an important role in anti-apoptotic mediated by modulating p53 signaling pathway, which may provide insight into future research and clinical applications in arrhythmia therapy.

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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