23 Oct 2024
This is the inside story of how AI cracked the protein folding code. In 2024, David Baker, Demis Hassabis and John Jumper won the Nobel Prize in Chemistry for these advances in computer-assisted protein design and structure prediction.

Proteins are biological nano-machines that perform a vast array of vital functions inside of every living organism. For more than half a century, scientists have looked to solve the central mystery of protein science: How does a one-dimensional string of molecules fold innately and near-instantaneously into a complex three-dimensional shape? In 2020, Google DeepMind entered a deep-learning algorithm called AlphaFold2 into the Olympics of protein folding — and to everyone’s shock and surprise, ended up solving a key part of the puzzle. This breakthrough kick-started an AI revolution in biology research, clearing the path to revolutionary new techniques in protein design, which is the process of creating new and novel proteins that could solve some of the world’s biggest problems.

Read the related article at: https://www.quantamagazine.org/how-ai…

Related Papers:
“Highly accurate protein structure prediction with AlphaFold” https://www.nature.com/articles/s4158…
“De novo design of protein structure and function with RFdiffusion” https://www.nature.com/articles/s4158…
“Generalized biomolecular modeling and design with RoseTTAFold All-Atom” https://www.science.org/doi/10.1126/s…
“Accurate structure prediction of biomolecular interactions with AlphaFold 3” https://www.nature.com/articles/s4158…

[…]