UVA’s Nikolay V. Dokholyan, PhD, and colleagues have developed a suite of artificial intelligence-powered tools, called YuelDesign, YuelPocket and YuelBond, that work together to transform how new drugs are created. The centerpiece, YuelDesign, uses a cutting-edge form of AI called diffusion models to design new drug molecules tailored to fit their protein targets exactly, even accounting for the way proteins flex and shift shape during binding.
A companion tool, YuelPocket, identifies exactly where on a protein a drug can attach, while YuelBond ensures the chemical bonds in designed molecules are accurate. Together, the approach is poised to improve both how new drugs are designed and how quickly and efficiently existing drugs can be evaluated for new purposes.
A companion tool, YuelPocket, uses graph neural networks to identify precisely where on a protein a drug should bind, even on predicted protein structures from existing tools such as AlphaFold. “Most existing AI tools treat the protein as a frozen statue, but that’s not how biology works. Our approach lets the protein and the drug candidate evolve together during the design process, just as they would in the body,” said researcher Dr. Jian Wang. “We showed, for example, that when designing molecules for a well-known cancer-related protein called CDK2, only YuelDesign could capture the critical structural changes that happen when a drug binds.”
Read more about Dr. Dokholyan’s work here.
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