@Article{cmes.2020.012846,
AUTHOR = {Majid Monajjemi, Rahim Esmkhani, Fatemeh Mollaamin, Sara Shahriari},
TITLE = {Prediction of Proteins Associated with COVID-19 Based Ligand Designing and Molecular Modeling},
JOURNAL = {Computer Modeling in Engineering \& Sciences},
VOLUME = {125},
YEAR = {2020},
NUMBER = {3},
PAGES = {907--926},
URL = {http://www.techscience.com/CMES/v125n3/40795},
ISSN = {1526-1506},
ABSTRACT = {Current understanding about how the virus that causes COVID-19
spreads is largely based on what is known about similar coronaviruses.
Some of the Natural products are suitable drugs against SARS-CoV-2 main
protease. For recognizing a strong inhibitor, we have accomplished docking studies on the major virus protease with 4 natural product species as
anti COVID-19 (SARS-CoV-2), namely “Vidarabine”, “Cytarabine”, “Gemcitabine” and “Matrine” which have been extracted from Gillan’s leaves plants.
These are known as Chuchaq, Trshvash, Cote-Couto and Khlvash in Iran.
Among these four studied compounds, Cytarabine appears as a suitable compound with high effectiveness inhibitors to this protease. Finally by this work
we present a method on the Computational Prediction of Protein Structure
Associated with COVID-19 Based Ligand Design and Molecular Modeling.
By this investigation, auto dock software (iGEM-DOCK) has been used and
via this tool, the suitable receptors can be distinguished in whole COVID-19
component structures for forming a complex. “iGEMDOCK” is suitable to
define the binding site quickly. With docking simulation and NMR investigation, we have demonstrated these compounds exhibit a suitable binding
energy around 9 Kcal/mol with various ligand proteins modes in the binding to COVID-19 viruses. However, these data need further evaluation for
repurposing these drugs against COVID-19 viruses, in both vivo & vitro.},
DOI = {10.32604/cmes.2020.012846}
}