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This paper analyzes the contributions of David Baker, Demis Hassabis, and John M. Jumper, recipients of the 2024 Nobel Prize in Chemistry, for their work on computational protein design and protein structure prediction. Baker developed methods for creating novel protein structures with applications in biochemistry and medicine, while Hassabis and Jumper created AlphaFold, an open-access AI tool for predicting protein folding. The analysis highlights the impact of these advancements on structural biology and related fields.
AlphaFold's ability to predict protein structures is revolutionizing structural biology, making previously intractable research avenues now accessible.
ABSTRACT The 2024 Nobel Prize in Chemistry recognized three scientists who each contributed to the development of predictive protein folding and artificial intelligence tools to predict the structure of nearly all known proteins. Proteins are composed of long, three-dimensional chains, formed by combining twenty different types of amino acids, that fold into unique structures which determine their function. David Baker has demonstrated new ways to create protein structures that have the capacity for discoveries imperative to biochemistry and medicine. Demis Hassabis and John M. Jumper, both from Google DeepMind, developed the open access AlphaFold artificial intelligence tool, which can predict protein folding structures and enable large-scale structural biology.
DeepMind