The neural network is looking for the most dangerous mutations of COVID-19

The new tool can prevent potentially dangerous variants of the virus development that will

to bind with human cells even more actively. If biologists know in advance about possible mutations, it will make it easier to deal with them.

It is important to be able to assess in advance howamino acid changes can increase the infectivity of the virus. Our structure is a powerful tool for understanding how amino acids influence changes in the SARS-CoV-2 spike protein.

Research text

The authors of the new work used a two-step computational procedure to create a model to predict changes in amino acids - the building blocks of all proteins in the body.

Changes can occur in the receptor binding (RBD) process of the SARS-CoV-2 spike protein. This will affect the ability of the virus to bind to the ACE2 receptors in human and other animal cells.

During the work, the researchers trained the neural networkon experimental data on the activity of a new type of coronavirus, depending on changes in one amino acid. They found that they could predict with about 80% accuracy whether certain amino acid changes would improve or worsen SARS-CoV-2's ability to infect humans and animals.

The model also predicted how changes in SARS-CoV-2 amino acids affected the activity of the alpha, beta, gamma, and delta variants.

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