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1.
J Recept Signal Transduct Res ; 41(3): 217-233, 2021 Jun.
Article in English | MEDLINE | ID: mdl-32787531

ABSTRACT

Cancer is caused by a variety of pathways, involving numerous types of enzymes. Among them three enzymes i.e. Cyclin-dependent kinase-2 (CDK-2), Human topoisomerase IIα, and Vascular Endothelial Growth Factor Receptor-2 (VEGFR-2) are three of the most common enzymes that are involved in the cancer development. Although many chemical drugs are already available in the market for cancer treatment, plant sources are known to contain a wide variety of agents that are proved to possess potential anticancer activity. In this experiment, total thirty phytochemicals were analyzed against the mentioned three enzymes using different tools of bioinformatics and in silico biology like molecular docking study, drug likeness property experiment, ADME/T test, PASS prediction, and P450 site of metabolism prediction as well as DFT calculation to determine the three best ligands among them that have the capability to inhibit the mentioned enzymes. From the experiment, Epigallocatechin gallate was found to be the best ligand to inhibit CDK-2, Daidzein showed the best inhibitory activities towards the Human topoisomerase IIα, and Quercetin was predicted to be the best agent against VEGFR-2. They were also predicted to be quite safe and effective agents to treat cancer. However, more in vivo and in vitro analyses are required to finally confirm their safety and efficacy in this regard.


Subject(s)
Antineoplastic Agents/pharmacology , Cyclin-Dependent Kinase 2/antagonists & inhibitors , DNA Topoisomerases, Type II/metabolism , Phytochemicals/pharmacology , Vascular Endothelial Growth Factor Receptor-2/antagonists & inhibitors , Cyclin-Dependent Kinase 2/metabolism , Cytochrome P-450 Enzyme System/metabolism , Density Functional Theory , Humans , Ligands , Molecular Docking Simulation , Neoplasms/pathology , Plants/chemistry , Vascular Endothelial Growth Factor Receptor-2/metabolism
2.
Immunobiology ; 225(3): 151949, 2020 05.
Article in English | MEDLINE | ID: mdl-32444135

ABSTRACT

Ebola virus is a highly pathogenic RNA virus that causes the Ebola haemorrhagic fever in human. This virus is considered as one of the dangerous viruses in the world with very high mortality rate. To date, no epitope-based subunit vaccine has yet been discovered to fight against Ebola although the outbreaks of this deadly virus took many lives in the past. In this study, approaches of reverse vaccinology were utilized in combination with different tools of immunoinformatics to design subunit vaccines against Ebola virus strain Mayinga-76. Three potential antigenic proteins of this virus i.e., matrix protein VP40, envelope glycoprotein and nucleoprotein were selected to construct the subunit vaccine. The MHC class-I, MHC class-II and B-cell epitopes were determined initially and after some robust analysis i.e., antigenicity, allergenicity, toxicity, conservancy and molecular docking study, EV-1, EV-2 and EV-3 were constructed as three potential vaccine constructs. These vaccine constructs are also expected to be effective on few other strains of Ebola virus since the highly conserved epitopes were used for vaccine construction. Thereafter, molecular docking study was conducted on these vaccines and EV-1 emerged as the best vaccine construct. Afterward, molecular dynamics simulation study revealed the good performances and stability of the intended vaccine protein. Finally, codon adaptation and in silico cloning were carried out to design a possible plasmid (pET-19b plasmid vector was used) for large scale production of the EV-1 vaccine. However, further in vitro and in vivo studies might be required on the predicted vaccines for final validation.


Subject(s)
Ebola Vaccines/immunology , Ebolavirus/immunology , Hemorrhagic Fever, Ebola/prevention & control , Vaccines, Subunit/immunology , Vaccinology , Antigens, Viral/chemistry , Antigens, Viral/immunology , Computational Biology/methods , Ebolavirus/classification , Epitopes/chemistry , Epitopes/immunology , Genetic Engineering , Humans , Models, Molecular , Reproducibility of Results , Structure-Activity Relationship , Vaccinology/methods
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