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<p>The 2024 Chemistry Nobel Prize was awarded to David Baker, Demis Hassabis, and John Jumper for developing computational tools, including artificial intelligence (AI)-powered approaches that can predict the three-dimensional structure of proteins and design new proteins. These computational tools can predict angstrom-level accurate structures of known proteins from primary amino acid sequences and provide new protein structures that are yet to be solved by crystallographic techniques, thus opening up new frontiers in understanding complex biomolecular systems. This article discusses the history of protein structure determination and sequence-to-structure prediction, followed by a brief overview of the AI tools, including AlphaFold2, to determine 3D protein structures solely from protein primary sequences. Finally, the future perspective of this emerging area has been discussed along with some of the open questions in biomolecular systems and processes.</p>

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Nobel Prize in Chemistry 2024

  • 期刊论文

  • 发表日期：

    2025年5月21日

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  • Tarak Karmakar

摘要

The 2024 Chemistry Nobel Prize was awarded to David Baker, Demis Hassabis, and John Jumper for developing computational tools, including artificial intelligence (AI)-powered approaches that can predict the three-dimensional structure of proteins and design new proteins. These computational tools can predict angstrom-level accurate structures of known proteins from primary amino acid sequences and provide new protein structures that are yet to be solved by crystallographic techniques, thus opening up new frontiers in understanding complex biomolecular systems. This article discusses the history of protein structure determination and sequence-to-structure prediction, followed by a brief overview of the AI tools, including AlphaFold2, to determine 3D protein structures solely from protein primary sequences. Finally, the future perspective of this emerging area has been discussed along with some of the open questions in biomolecular systems and processes.