What is it about?
This paper presents a deep learning application designed to identify foods, plants, and other natural sources that may contain inhibitors targeting key enzymes of the SARS-CoV-2 virus. These inhibitors can potentially slow or halt the virus’s replication inside the human body, helping to prevent severe illness or death. The researchers have trained the application using a variety of foods, plants, and drugs to detect which ones are rich in inhibitors that could help fight COVID-19 in its early stages. The app currently focuses on thirteen key enzymes of the virus and can identify potential sources just by their names, providing a promising tool in the search for natural treatments.
Featured Image
Photo by Fusion Medical Animation on Unsplash
Why is it important?
The COVID-19 pandemic has been a global crisis, with immense consequences on human health, lives, and economies. While vaccines have made a significant impact, finding early-stage treatments that can help prevent the virus from replicating inside the body is crucial. Identifying natural sources, such as foods and plants, that contain these inhibitors could be a game-changer in our fight against COVID-19. These natural compounds can be used to support traditional treatment methods and could help reduce the severity of the virus, potentially saving lives and minimizing long-term health impacts. The deep learning application developed in this research is a smart and innovative approach to accelerating the discovery of these valuable compounds.
Perspectives
The implications of this research go beyond just COVID-19. By developing an AI-based tool to identify inhibitors, it can be adapted to help fight other viral diseases or even be used in the discovery of novel treatments for a wide range of illnesses. As the application is refined and expanded, it could include more natural sources, and even target more viruses or medical conditions. Additionally, this approach could revolutionize how we explore the medicinal properties of plants, foods, and other natural products, making the process faster and more precise. With the team’s dedication, we are one step closer to finding new, accessible solutions to fight viral diseases, proving once again that technology and nature can work hand in hand to solve some of the world’s most urgent health challenges.
Leila BENAROUS
University of Laghouat
Read the Original
This page is a summary of: Deep learning application detecting SARS-CoV-2 key enzymes inhibitors, Cluster Computing, July 2022, Springer Science + Business Media,
DOI: 10.1007/s10586-022-03656-6.
You can read the full text:
Contributors
The following have contributed to this page
