Abstract

A game-changing computational tool has arrived on scene—Alphafold2, the AI-powered protein structure prediction algorithm developed by DeepMind. I will discuss two examples of how we have used AlphaFold2 to inform our experiments to understand biological motility. The first study combines cryo-EM tomography with Alphafold2 to identify novel proteins in mammalian sperm flagella and then study their function in sperm motility. The second study involves dissecting the regulation of adapter proteins that link dynein and kinesin motors onto mitochondria. These case studies reveal how predicted protein structures from AlphaFold2, while imperfect, can guide experiments that yield new insight into cell biological processes