UT Dallas Protein Engineering Collaboration Develops Machine-Learning Model for More Precise Therapeutic Enzyme Design
Researchers at UT Dallas have developed a machine-learning model called ProSSpeC that predicts how proteases enzymes that act like molecular scissors will behave before they are tested in the lab. The system analyzes evolutionary patterns across thousands of enzymes to design synthetic variants that can outperform existing proteases used in drug development and research. This advancement could accelerate the creation of more precise therapies for diseases such as cancer and viral infections by reducing the trial-and-error process in protein engineering. 
UT Dallas Protein Engineering Collaboration Develops Machine-Learning Model for More Precise Therapeutic Enzyme Design