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208005

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

Article

Last updated: 25 Dec 2024

Subjects

-

Tags

Medical Engineering.

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.

DOI

10.21608/jaet.2021.58978.1083

Keywords

SARS-CoV-2, COVID-19, protein-ligand docking, AutoDock Vina, MPro

Authors

First Name

Esraa Mamdouh

Last Name

Hashem

MiddleName

-

Affiliation

Biomedical Engineering Department, Faculty of Engineering, Misr University for Science and Technology

Email

esraa.shebib@must.edu.eg

City

-

Orcid

-

First Name

Mai S.

Last Name

Mabrouk

MiddleName

-

Affiliation

Biomedical Engineering, Misr University for science and technology

Email

msm_eng@yahoo.com

City

-

Orcid

-

Volume

42

Article Issue

1

Related Issue

29280

Issue Date

2022-01-01

Receive Date

2021-01-26

Publish Date

2022-01-01

Page Start

55

Page End

67

Print ISSN

2682-2091

Online ISSN

2812-5487

Link

https://jaet.journals.ekb.eg/article_208005.html

Detail API

https://jaet.journals.ekb.eg/service?article_code=208005

Order

5

Type

Original Article

Type Code

1,142

Publication Type

Journal

Publication Title

Journal of Advanced Engineering Trends

Publication Link

https://jaet.journals.ekb.eg/

MainTitle

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

Details

Type

Article

Created At

22 Jan 2023