Proteins form the fundamental building blocks of living organisms, making their study one of the primary focuses of biochemistry. Protein research encompasses understanding their composition, determining their spatial structures, predicting their properties, and even designing novel proteins with specific functionalities.
The 2024 Nobel Prize in Chemistry recognized groundbreaking achievements in this field. American biochemist and computational biologist David Baker received the award for his work on computer-aided protein design. Meanwhile, British neuroscientist Demis Hassabis and his colleague John M. Jumper were honored for their contributions to predicting protein structures. Together, these laureates have revolutionized how we approach protein research using advanced computational tools.
Proteins, also known as polypeptides, are complex organic molecules composed of amino acid chains linked by peptide bonds. The sequence of these amino acids is dictated by the genetic code. Out of hundreds of known amino acids, only 21 are utilized in living organisms, eight of which are essential. Humans and many other animals cannot synthesize these essential amino acids—such as valine, leucine, and tryptophan—and must obtain them through dietary protein, posing challenges for strict vegetarians and vegans.
Proteins perform a wide array of functions in the human body. Hemoglobin transports oxygen in the blood, antibodies support the immune system, rhodopsin enables vision, and enzymes catalyze essential biochemical reactions. Moreover, all bodily tissues are primarily composed of proteins. These molecules achieve their functions by folding into specific three-dimensional structures, a process governed by their amino acid sequences. Despite the theoretical complexity of folding—where a 100-amino-acid protein could adopt potential configurations—proteins fold reliably into precise shapes. Biochemists have long sought to predict these structures based solely on amino acid sequences, a challenge now addressed by the Nobel laureates.
Demis Hassabis and John M. Jumper, working at Google DeepMind, developed the AlphaFold2 artificial intelligence model in 2020. By leveraging deep learning techniques, similar to those in the AlphaGo neural network that mastered the game of Go, AlphaFold2 identified patterns in extensive datasets to predict the spatial structures of proteins. This model has since enabled scientists worldwide to determine the structures of numerous proteins, transforming the field of biochemistry.
Meanwhile, David Baker's team created Rosetta, a computer program that predicts protein folding by analyzing vast datasets. This process, which involved using a distributed network of approximately 70,000 computers, also enabled the design of entirely new proteins. In 2003, Baker's team successfully created a synthetic protein with 93 amino acids, whose structure and amino acid sequence were unlike anything found in nature. X-ray diffraction analysis confirmed the accuracy of their predictions, marking a major milestone in protein engineering.
The Nobel Committee awarded half of the prize's 11 million Swedish kronor (just over $1 million) to Baker, with the remaining half shared between Hassabis and Jumper, reflecting the unique significance of their contributions. Interestingly, the 2024 Nobel Prize in Physics was also awarded for advancements in artificial intelligence, highlighting its growing impact across scientific disciplines.
But what does this mean for everyday life? These breakthroughs will enhance our understanding of how proteins function in the human body, aid in developing new drugs, and lead to the creation of enzymes capable of breaking down plastic waste. Looking ahead, such innovations could help us address some of humanity's most pressing challenges—or perhaps even create entirely new forms of life.
