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Using AI to Analyze Large Amounts of Biological Data


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Said University of Michigan's Dong Xu, “Our method provides a systematic review of the data involved when studying proteins, as well as a protein’s energy state, which could help when identifying any possible mutation’s effect."

Credit: University of Missouri

University of Missouri (MU) researchers have demonstrated that a graph neural network could speed up the development of new drugs to treat cancer and other diseases by more quickly sifting through large amounts of data on protein dynamics.

Said MU's Dong Xu, "Previously, drug designers may have known about a couple places on a protein's structure to target with their therapies.

"A novel outcome of this method is that we identified a pathway between different areas of the protein structure, which could potentially allow scientists who are designing drugs to see additional possible target sites for delivering their targeted therapies. This can increase the chances that the therapy may be successful."

The method also permits researchers to simulate changes in proteins that occur with cancer and other conditions, and to study interactions within different areas of the protein structure.

From University of Missouri News Bureau
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Abstracts Copyright © 2022 SmithBucklin, Washington, DC, USA


 

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