AI software can provide 'roadmap' for biological discoveries MizzouNews
, with the ability to provide more targeted predictions, including specific models for animals, humans and plants. The model was created 10 years ago by Xu and fellow MU researcher Jay Thelen, a professor of biochemistry, to originally study proteins in mitochondria.
"Many biological discoveries need to be validated by experiments, but we don't want researchers to have to spend time and money conducting thousands of experiments to get there," Xu said."A more targeted approach saves time. Our tool provides a useful resource for researchers by helping them get to their discoveries faster because we can help them design more targeted experiments from which to advance their research more effectively.
By harnessing the power of artificial intelligence through a machine learning technique—training computers to make predictions using existing data—the model can help researchers who are studying the mechanisms associated with irregular locations of proteins, known as"mislocalization," or where a protein goes to a different place than it's supposed to. This abnormality is often associated with diseases such as metabolic disorders, cancers and neurological disorders.
"Some diseases are caused by mislocalization, which causes the protein to be unable to perform a function as expected because it either cannot go to a target or goes there inefficiently," Xu said. Another application of the team's predictive model is assisting with drug design by targeting an improperly located protein and moving it to the correct location, Xu said."We want to continue improving the model to determine whether a mutation in a protein could cause mislocalization, whether proteins are distributed in more than one cellular compartment, or how signal peptides can help predict localization more precisely," Xu said.
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