Open Access
ARTICLE
Prediction of Proteins Associated with COVID-19 Based Ligand Designing and Molecular Modeling
Majid Monajjemi1,*, Rahim Esmkhani2, Fatemeh Mollaamin1, Sara Shahriari3
1 Department of Chemical Engineering, Central Tehran Branch, Islamic Azad University, Tehran, 14987-54891, Iran
2 Department of Chemistry, Khoy Branch, Islamic Azad University, Khoy, 58159-88838, Iran
3 Department of Chemistry, Central Tehran Branch, Islamic Azad University, Tehran, 1498754891, Iran
* Corresponding Author: Majid Monajjemi. Email:
(This article belongs to the Special Issue: Computer Modelling of Transmission, Spread, Control and Diagnosis of COVID-19)
Computer Modeling in Engineering & Sciences 2020, 125(3), 907-926. https://doi.org/10.32604/cmes.2020.012846
Received 14 July 2020; Accepted 29 October 2020; Issue published 15 December 2020
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.
Keywords
Cite This Article
Monajjemi, M., Esmkhani, R., Mollaamin, F., Shahriari, S. (2020). Prediction of Proteins Associated with COVID-19 Based Ligand Designing and Molecular Modeling.
CMES-Computer Modeling in Engineering & Sciences, 125(3), 907–926. https://doi.org/10.32604/cmes.2020.012846