The 2024 Nobel Prize for Chemistry was shared by David Baker “for computational protein design” along with Demis Hassabis and John Jumper “for protein structure prediction”.
More on the news
- David Baker receives half of the Nobel Prize for his pioneering efforts in computational protein design.
- The other half has been awarded to Demis Hassabis and John M. Jumper for developing AlphaFold 2, an artificial intelligence model that can predict the structures of millions of proteins.
- David Baker: Based at the University of Washington in Seattle.
- He has been a leading figure in the field of protein design, combining computational methods with biological principles to innovate in protein engineering.
- Demis Hassabis and John M. Jumper: Both researchers work at Google DeepMind in London.
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Computational protein design
- In 2003, Baker led a team that utilised bespoke software methods to create a new protein.
- Since then, his team has refined these techniques, enabling the design of ‘designer’ proteins tailored for specific applications
- The technology has potential to develop different varieties of proteins with the possibility of constructing nearly any type of protein
Bespoke Software Methods
- Bespoke software : It refers to custom solutions developed to meet the specific needs of an organisation or project.
- Rosetta Software: It was developed by David Baker’s team.
- It employs computational algorithms to predict protein structures and design novel proteins with designated functions.
- Significance: The newly designed proteins can perform functions that naturally occurring proteins are not capable of, such as:
- Example: Creating synthetic proteins that can degrade plastics, which are otherwise non-biodegradable.
Nobel Prize Overview
- The Nobel Prize aims to honor individuals whose contributions have significantly benefited humanity, established by Swedish inventor Alfred Nobel.
Award Money: Winners of the Nobel Prize in Chemistry 2024 will receive 10 million Swedish kronor (approximately $900,000).
Other 2024 Awards
- Physiology or Medicine award: Victor Ambros and Gary Ruvkun for their work on the discovery of microRNA
- Physics Prize: John Hopfield and Geoffrey Hinton for their contributions to machine learning.
- The official award ceremony is scheduled for December 10, 2024.
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Protein structure prediction
In 2020 Demis Hassabis and John M. Jumper Developed AlphaFold 2.
It can predict the structures of millions of proteins.
- Prior to their work, human scientists had only mapped approximately 170,000 protein structures.
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AlphaFold 2
- Foundation: It is developed by DeepMind using the Deep Neural Network system.
- Data Utilization: Neural networks utilize large datasets, specifically from the Protein Data Bank (PDB), to train the model, mimicking the human brain’s learning process.
- Learning Mechanism: After training, AlphaFold can make structural predictions for proteins not included in the PDB.
- Input/Output Process: Protein sequences enter one end of the system, and the predicted three-dimensional structures from amino acid sequences with atomic-level accuracy.
What are proteins and what do they do?
- Proteins are large, complex molecules that play many critical roles in the body.
- They do most of the work in cells and are required for the structure, function, and regulation of the body’s tissues and organs.
- Proteins are made up of hundreds or thousands of smaller units called amino acids, which are attached to one another in long chains.
- There are 20 different types of amino acids that can be combined to make a protein.
- The sequence of amino acids determines each protein’s unique 3-dimensional structure and its specific function.
- Amino acids are coded by combinations of three DNA building blocks (nucleotides), determined by the sequence of genes.
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Significance of Protein Structure
- Having a protein structure provides a greater level of understanding of how a protein works, which can allow us to create hypotheses about how to affect it, control it, or modify it.
- For example, knowing a protein’s structure could allow you to design site-directed mutations with the intent of changing function.
October 10, 2024
