The advancement in AI made by the 'AlphaFold' paper includes solving the protein folding problem through a deep learning model that predicts protein structures from amino acid sequences with remarkable accuracy. AlphaFold showed a median backbone accuracy of 0.96 Å root-mean-square deviation, significantly surpassing other methods, and indicated a solution to a 50-year challenge in structural biology [2].

Following the initial success, subsequent models like AlphaFold2 and AlphaFold3 expanded the capabilities to predict not only proteins but also ligands, DNA, and RNA structures, further enhancing applications in drug discovery and understanding biological processes [3][5][6].

How AI Revolutionized Protein Science, but Didn’t End It

What advancements in AI were made by the "AlphaFold" paper?

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