The Nobel Prize in Chemistry for 2024 has been awarded to three scientists, David Baker, Demis Hassabis and John Jumper. Their work in protein structure prediction and computational protein design has not only answered questions in biology but has also opened the doors to advancements in medicine, biotechnology and more.
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Demis Hassabis, the British founder of Google DeepMind and John Jumper share half of the prize for developing AlphaFold. AlphaFold has transformed the field of biology by accurately predicting protein structures based solely on their amino acid sequences.
Before AlphaFold’s development, predicting a protein’s three-dimensional structure was a slow and difficult process that often took years of research.
In 2020, AlphaFold 2 was unveiled, delivering accuracy in predicting the structures of two-thirds of proteins with over 90% precision.
This breakthrough has enabled scientists to predict the structure of nearly all known proteins, a resource now accessible to more than 2 million people in 190 countries.
The other half of the prize was awarded to David Baker, an American biochemist from the University of Washington. Baker’s research goes beyond predicting existing protein structures, he has designed entirely new proteins that do not exist in nature.
His computational approach has yielded novel proteins with applications in medicine, vaccines, nanomaterials and tiny sensors. Baker’s innovations have made the way for the development of new vaccines including those targeting coronaviruses.
Since the early 2000s, Baker and his team have continually refined their techniques, producing proteins with increasingly complex and powerful functions.
Baker’s software, Rosetta, which helps design these proteins has been freely available.
David Baker, based at the University of Washington in Seattle, was awarded half of the Nobel Prize for his computational protein design work. He developed computational tools that allow for the design of new proteins with entirely novel structures and functions.
His research enables scientists to design proteins from scratch. Baker’s work is because it opens up possibilities for the creation of new proteins that do not exist in nature.
His team successfully designed synthetic proteins that can perform specific tasks including detecting and neutralizing viruses and diseases. This could lead to new treatments for a wide array of conditions including cancer and infectious diseases.
His computational methods have also enabled the creation of tiny sensors and nanomaterials.
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The other half of the prize was shared between Demis Hassabis and John Jumper, who developed AlphaFold2, an AI model that solves a 50-year-old problem in biology, accurately predicting the 3D structures of proteins based on their amino acid sequences.
Predicting the structure of proteins has been a goal for scientists because the structure of a protein determines its function. Understanding this helps in drug discovery, disease research and biotechnology.
AlphaFold2 managed to predict the structure of nearly all the 200 million proteins known to science, which has had an immediate impact on biological research.
This AI model has been used by over 2 million researchers globally helping in understanding complex biological processes like antibiotic resistance and the development of enzymes that can break down plastic.
AlphaFold2 is an advancement because it allows scientists to map out human proteins quickly, which was previously a painstaking and slow process involving experimental methods like X-ray crystallography or NMR spectroscopy.
The model’s impact on drug discovery has been profound. By helping scientists understand the structure of disease-related proteins, AlphaFold2 has accelerated the development of new therapeutics and biopharmaceuticals.
For decades, predicting the 3D structure of proteins from their amino acid sequences was considered one of the problems in biology. The complexity of protein folding with 20 different amino acids that can be arranged in countless ways making it extremely difficult to predict how they would fold into their final structure.
In 2020, Hassabis and Jumper achieved what many thought impossible, they cracked the code with AlphaFold2. This breakthrough allows researchers to move forward at speeds in understanding diseases and developing tailor-made drugs. It has even been used to model proteins involved in diseases such as COVID-19.
Scientists have pursued the goal of predicting how strings of amino acids fold into the three-dimensional shapes of proteins. These shapes are important because they determine how proteins interact with other molecules including drugs.
The 2024 Nobel Prize in Chemistry recognizes the realization of this dream, which has implications for medicine, biotechnology and fundamental biology.
Heiner Linke, the chair of the Nobel Committee for Chemistry described the work as fulfilling a scientific dream that opens up vast possibilities.
The combination of protein structure prediction and computational protein design creates a powerful toolkit for tackling diseases and engineering novel biological materials.
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