E3S Web Conf.
Volume 319, 2021International Congress on Health Vigilance (VIGISAN 2021)
|Number of page(s)||6|
|Published online||09 November 2021|
Assessment of asthma treatment against SARS CoV-2 by using a computer approach
1 1Molecular chemistry and Natural Substances Laboratory, Faculty of Science, University Moulay Ismail, Meknes, Morocco
2 health, environment, and epigenetics research team, Faculty of Science, University Moulay Ismail, Meknes, Morocco
3 Superior School of Technology - Khenifra (EST-Khenifra), University of Sultan My Slimane, PB 170, Khenifra 54000 Morocco.
The disease caused by the coronavirus is called COVID-19. The degree of infection varies from one person to another. According to the data collected to date, people with asthma and obesity are over-represented among adults hospitalized for COVID-19. The reason is very simple: COVID-19 is a disease that particularly attacks the respiratory system, including the lungs. This pandemic has led us to return to plants. Modern medicine has found its success thanks to traditional medicine, the effectiveness of which comes from medicinal plants. Currently, in China, many people believe in the miraculous power of plants, boosting their immunity to protect against asthma. Therefore, this work aimed to study components of natural origin that have an anti-asthma effect that can be considered as the panacea against Covid-19, by using the most important method, which is molecular docking. In this research, we performed a molecular docking study on molecules naturally occurring molecules based on the recently crystallized SARS CoV-2 protein (pdb code 7C6S). ADMET prediction was performed for the selected inhibitors. The results of molecular docking and ADMET prediction support the potential of the five selected molecules to be further developed as novel inhibitors for the treatment of SARS CoV-2.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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