Protein-Ligand In- Silico Molecular Docking Model for Discovering Potential Drugs of COVID-19
Hashem, E., Mabrouk, M. (2022). Protein-Ligand In- Silico Molecular Docking Model for Discovering Potential Drugs of COVID-19. EKB Journal Management System, 42(1), 55-67. doi: 10.21608/jaet.2021.58978.1083
Esraa Mamdouh Hashem; Mai S. Mabrouk. "Protein-Ligand In- Silico Molecular Docking Model for Discovering Potential Drugs of COVID-19". EKB Journal Management System, 42, 1, 2022, 55-67. doi: 10.21608/jaet.2021.58978.1083
Hashem, E., Mabrouk, M. (2022). 'Protein-Ligand In- Silico Molecular Docking Model for Discovering Potential Drugs of COVID-19', EKB Journal Management System, 42(1), pp. 55-67. doi: 10.21608/jaet.2021.58978.1083
Hashem, E., Mabrouk, M. Protein-Ligand In- Silico Molecular Docking Model for Discovering Potential Drugs of COVID-19. EKB Journal Management System, 2022; 42(1): 55-67. doi: 10.21608/jaet.2021.58978.1083

Protein-Ligand In- Silico Molecular Docking Model for Discovering Potential Drugs of COVID-19

Journal of Advanced Engineering Trends
Article 5, Volume 42, Issue 1, January 2022, Page 55-67  XML PDF (580.03 K)
Document Type: Original Article
DOI: 10.21608/jaet.2021.58978.1083
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Authors
Esraa Mamdouh Hashem email 1; Mai S. Mabrouk2
1Biomedical Engineering Department, Faculty of Engineering, Misr University for Science and Technology
2Biomedical Engineering, Misr University for science and technology
Abstract
The novel human coronavirus is known as SARS-CoV-2, first noticed in late 2019 in Wuhan, China causing a respiratory disease known as COVID-19. This disease has extended rapidly around the world, leading to neuroma deaths and economic losses across many countries. There is currently no approved therapeutics, and effective treatment alternatives remain extremely limited; treating is a pressing need. This work aims to find a potential drug candidate by finding the effective binding between a small molecule (ligand) and a protein by applying protein-ligand docking for target 6YNQ Main protease (Mpro) protein using the AutoDock Vina technique. Several compounds have been identified from the in-silico docking model that could prove effective inhibitors for SARS-CoV-2. Among those compounds and related drugs, 5 best compounds were selected, which had a better score and lower root-mean-square deviation as compared to the reference molecule as: 1.067 Å, 1.78 Å, 1.648 Å, 1.533 Å, and0.027 Å. Results revealed that the identified compounds and drugs (Nintedanib, Nifedipine, NNRTI, and Bordetella pertussis toxoid antigen) are recommended for therapeutic development against the virus as these novel molecules may be utilized to advance innovation and development of antiviral compounds among Coronavirus.
Keywords
SARS-CoV-2; COVID-19; protein-ligand docking; AutoDock Vina; Mpro
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