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Scientists Have Created an AI Platform That Can Help Identify Covid-fighting Molecules

Image for representation: AP.

Image for representation: AP.

The platform is publicly available as a web application and anyone can enter details of a molecule to test how that will work against the COVID19 infections.

While we have entered the second year of the viral apocalypse and more than three million people have died, we do not yet have a medicine that can effectively treat COVID-19. Even as people are getting vaccinated and hope of herd immunity is tantalizing, it is realistic that the herd immunity may not be fully achieved, at least at this point.

The deadly variations of the mutating virus may not give us time to break the chain of infections. And then there are Covid patients, who cannot take vaccines until their symptoms start improving, there is nothing for them. While doctors are using pre-existing medicines, blood plasma and other therapeutics, these methods do not have strong decisive data leading to a clinical conviction. Some potential methods are under clinical trials but scientists are still looking for a drug that can effectively kill coronavirus without harming human cells.

To speed up the process and reduce the burden of experimentation, scientists have built a machine learning tool to screen molecules for anti-coronavirus properties in them. REDIAL-20, which is a suite of computational models, can help scientists look for material that can stop SARS-CoV-2 based on already existing data that the AI models have been trained on. The platform is publicly available as a web application and anyone can enter details of a molecule to test how that will work against the COVID19 infections. The tool can test molecules against a number of factors such as viral entry, viral replication, live virus infectivity, human cell toxicity and many more.

“To some extent, this replaces (lab) experiments,” says Tudor Opera, the leading scientist of the project and the chief of Translational Informatics Division at the University of New Mexico. The research was published in Nature Machine Intelligence on May 2, 2021.

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The unique tool was developed by joint collaboration of Opera’s team at UNM and another team at the University of Texas, El Paso, led by Suman Srimulla. In Srimulla’s team, there is a 2020 graduate of Birla Institute of Technology and Science, Pilani, Srijan Jain, who hails from Gurugram, Haryana.

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