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Using Machine Learning to Combat the Coronavirus

Using Machine Learning to Combat the Coronavirus

A joint team of researchers from TU Berlin and the University of Luxembourg is exploring why a spike protein in the SARS-CoV-2 virus is able to bind much more effectively to human cells than other coronaviruses. Google.org is funding the research with 125,000 US dollars.

BIFOLD Principle Investigator Dr. Grégoire Montavon of TU Berlin’s Machine Learning group leads the project together with Professor Alexandre Tkatchenko of the University of Luxembourg. Using an approach which combines quantum mechanics and Machine Learning, their project seeks to gain a deeper understanding of the binding behavior of the novel coronavirus (SARS-CoV-2).

We are delighted to be receiving this funding and support for our fundamental research. Upon completion of the project, we will be publishing our findings for the entire scientific community.

Dr. Grégoire Montavon

The researchers are analyzing the mechanism which accounts for the unusually high binding affinity displayed by the SARS-CoV-2 spike protein regarding ACE2 human host cell receptors: Discovering this process would represent an important first step towards the future development of treatments for the coronavirus. Using precise, long-term simulations of the molecular dynamics of the spike protein and the human receptor, the researchers aim to gain a better understanding of how they interact.

More information is available in the press release of TU Berlin.