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How we built AlphaFold 3 to predict the structure and interaction of all of life’s molecules

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Since its launch in 2020, more than 2 million researchers have used Google DeepMind’s AlphaFold 2 model for protein predictions in their work on vaccine development, cancer treatments and more — helping solve a problem that researchers had been working on for over 50 years. After helping scientists predict hundreds of millions of structures, it would’ve been easy for the team to rest on their laurels. Instead, they got started on AlphaFold 3. This newer model, which the teams at Google DeepMind and Isomorphic Labs launched in May, builds on our previous models by predicting not just protein folding structures, but predicting the structure and interactions of all of life's molecules, including DNA, RNA and ligands (small molecules that bind to proteins). “With AlphaFold 2, we made enormous progress on this decades-old open problem of protein folding, but if you look at recent high-impact research, researchers are moving beyond that,” says Jonas Adler, research scientist at Google DeepMi

How we built AlphaFold 3 to predict the structure and interaction of all of life’s molecules Jul 16, 2024 | x.com Facebook LinkedIn Mail Copy link Here’s how this model came to be. Chaim Gartenberg Contributor Share x.com Facebook LinkedIn Mail Copy link Since its launch in 2020, more than 2 million researchers have used Google DeepMind’s AlphaFold 2 model for protein predictions in their work on vaccine development, cancer treatments and more — helping solve a problem that researchers had been working on for over 50 years . After helping scientists predict hundreds of millions of structures,

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