John M. Jumper

American computer scientist
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External Websites
Quick Facts
Born:
1985, Little Rock, Arkansas, U.S. (age 39)
Awards And Honors:
Nobel Prize (2024)
Subjects Of Study:
protein

John M. Jumper (born 1985, Little Rock, Arkansas, U.S.) is an American computer scientist who was awarded the 2024 Nobel Prize in Chemistry for his work using artificial intelligence (AI) to find the three-dimensional structure of proteins. He shared half the prize with his colleague, English computer scientist Demis Hassabis, and the other half of the prize was awarded to American biochemist David Baker.

Early life and career

Jumper spent his childhood and teenage years in Little Rock, Arkansas. He majored in mathematics and physics at Vanderbilt University and graduated with a bachelor’s degree in 2007. He went on to complete a master’s degree in physics at the University of Cambridge in 2008.

Jumper spent the next three years at D.E. Shaw Research, a computational laboratory in New York City, where he developed simulations to examine the dynamics of proteins and other molecules. Starting in 2011 Jumper shifted his study of computational biology to the University of Chicago, where he applied machine learning to explore the physics of protein folding. He graduated from the University of Chicago with a master’s degree (2012) and a Ph.D. (2017) in chemistry. He then joined Google’s DeepMind, an AI development company, in 2017 as a research scientist working on AlphaFold, which predicts the three-dimensional structure of proteins using machine-learning algorithms.

Solving protein folding

Proteins are large molecules that are directly involved in the chemical processes essential for life and are built up from 20 amino acids that can be combined in many different ways. The function of a protein is determined by its three-dimensional structure, which can be quite complex based on how the string of amino acids is folded.

How a protein is folded is determined by its amino acid sequence. However, even a small protein of only 100 amino acids can have 1047 possible three-dimensional structures. Predicting a protein’s structure from its amino acid sequence became a key problem in molecular biology.

In 1994 biologists John Moult and Krzysztof Fidelis founded the Critical Assessment of protein Structure Prediction (CASP) challenge to test methods for predicting protein structures. Every two years, contestants were given the amino acid sequences for proteins whose structure had been determined but not published and were challenged to predict the protein structures.

Progress was slow. By the mid-2010s the best models in the CASP challenge were about 40 percent accurate. DeepMind entered its protein structure program AlphaFold in CASP13 in 2018 and delivered an astonishing accuracy of about 60 percent, far ahead of any competitors. However, improvement beyond that was difficult, but by then Jumper had joined DeepMind and used his experience with protein simulation to help develop AlphaFold2.

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AlphaFold2 was trained on databases of amino acid sequences and protein structures and used a neural network called a transformer to find a likely protein structure. At CASP14 in 2020 AlphaFold2 reached an accuracy of 90 percent, which is comparable with experimental results. The problem of finding a protein structure given an amino acid sequence had been solved.

Jumper, DeepMind CEO Hassabis, and their collaborators used AlphaFold2 to calculate the structure of almost all of the more than 50,000 human proteins in 2021. They then went even further and calculated the structures of almost all of the 200 million known proteins, which come from about 1 million different species, or as Hassabis called it, “the entire protein universe.” By predicting how proteins organize themselves, researchers can develop more effective drugs that target specific proteins whose structures contribute to diseases. Since 2023 Jumper has been the director of Google DeepMind.

Jumper is also the recipient of the Wiley Prize in Biomedical Sciences (2022) and the BBVA Foundation Frontiers of Knowledge Award in Biology and Biomedicine (2023, shared with Hassabis and Baker). Jumper also received the VinFuture Prize (2022), the Canada Gairdner International Award (2023), and the Albert Lasker Basic Medical Research Award (2023, shared with Hassabis).

Erik Gregersen John P. Rafferty