Alexis Courbet
David Baker Lab, Howard Hughes Medical Institute &
University of Washington, Seattle, WA, US
Biomolecular machines have so far remained inaccessible to synthetic approaches. In this talk, I will discuss our recent efforts to leverage advances in computational protein design for the fabrication of genetically encodable nanoscale machinery. I will present novel computational methods powered by the deep learning revolution, and show how to use them for the systematic design and experimental realization of functional de novo protein folds and mechanical systems approaching natural complexity.