2024 Nobel Prize in Chemistry: Pioneering Work on Proteins

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2024 Nobel Prize in Chemistry: Pioneering Work on Proteins
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2024 Nobel Prize in Chemistry: Pioneering Work on Proteins

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The 2024 Nobel Prize in Chemistry honours Demis Hassabis and John M. Jumper (Google DeepMind) for using AI to predict protein structures and David Baker (University of Washington) for designing new proteins that do not exist in nature.

Demis Hassabis and John M. Jumper: AI and Protein Structure Prediction

  • Achievement: Awarded for developing an AI model, AlphaFold2, that predicts the 3D structure of nearly all known proteins.
  • Significance: Solved a 50-year-old problem of predicting protein structures from amino acid sequences.
  • Impact: Predicted the 3D structures of almost all 200 million known proteins using AI.
  • Technique: The model uses databases of known protein sequences and identifies co-evolving amino acids, predicting their structural folds.
  • Result: AI matched the accuracy of X-ray crystallography in protein structure determination, which had previously been the standard.

 

David Baker: Designing New Proteins

  • Achievement: Recognised for creating computational tools to design proteins that had never existed in nature.
  • First Innovation: Designed the protein Top7 in 2003, containing 93 amino acids, the largest man-made protein at the time.
  • Applications: New proteins have potential applications in nanomaterials, pharmaceuticals, vaccines, and environmentally friendly industries.
  • Significance: Protein design can lead to the development of sensitive sensors, targeted therapies, and a greener chemical industry.

 

Key Facts

  • Nature of Proteins: Proteins are composed of 20 different amino acids, with their sequence determining their 3D structure and function (e.g., enzymes, hormones, antibodies).
  • Significant Developments: AI model trained on known amino acid sequences to predict structures of unknown sequences.
  • AlphaFold2’s Training: Trained on known amino acid sequences and 3D structures, AI predicts proteins by analysing evolutionary patterns.
  • AlphaFold2 used by over 2 million researchers across 190 countries since its inception.
  • Impact of Discoveries: The discoveries fulfil a 50-year quest in the field of protein research, enhancing the understanding of protein folding and function.

 


 

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