About This Episode
Can AI help us model biology down to the molecular level? Neil deGrasse Tyson, Chuck Nice, and Gary O’Reilly learn about Nobel-prize-winning Alphafold, the protein folding problem, and how solving it could end disease with AI researcher and Chief AI Officer of Isomorphic Labs, Max Jaderberg.
We break down the protein folding problem and why it was so hard to crack. How do we learn to decode how strings of amino acids fold into complex, dynamic shapes that power our biology? How did AlphaFold crack this decades-old puzzle? We explore how Alphafold 3 uses the shapes of proteins to predict protein-drug interactions. How close are we to using AI and deep learning to design new medicines instead of discovering them by chance? Could generative AI invent molecules that precisely target the cause of a disease?
We take these ideas into the future: Could AI help us fix misfolded proteins that cause illness? Can we use these tools to create personalized drugs tailored to your unique genome? Will it make it economically feasible to treat rare diseases? Could this even help us slow aging or regenerate limbs, like salamanders do? Could this technology combat cancer, fix rare genetic disorders, or even digest plastic? And with quantum computing on the horizon, what happens when we combine it with AI? Will chemistry ever be done the same way again?
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