New opportunities not only in chemistry

Comment by Paweł Borowiecki, PhD, from the Faculty of Chemistry:

The 2024 Nobel Prize in Chemistry was awarded to three scientists for their groundbreaking research on proteins. Prof. David Baker from the University of Washington was honored for designing new proteins using computational tools, while Demis Hassabis and John Jumper (co-founders of DeepMind Technologies, now Google DeepMind) were recognized for creating the AlphaFold2 artificial intelligence model, based on artificial neural networks, which predicts protein structures directly from their amino acid sequences.

It's worth emphasizing that the AlphaFold2 program allows for the prediction of a protein's three-dimensional structure with an accuracy of around 90%. In comparison, prototypes of such tools used between 2000 and 2017 had an accuracy that did not exceed 40%, making this a significant achievement. In simplified terms, using this software, one can generate a protein structure from a simple nucleotide sequence transcribed into an amino acid sequence without the need for crystallization, greatly simplifying and accelerating many tedious and time-consuming laboratory procedures.

The discoveries of this year’s Nobel laureates open new possibilities not only in chemistry but also in modern biotechnology and medicine. The scientific potential of these tools is currently being used in designing highly specific and selectively acting next-generation drugs, creating new enzymes with improved catalytic properties, vaccines, and many other functional materials. These discoveries may provide a new impetus in fighting various civilization diseases or even in recycling polymer waste.

How Do Proteins Work and How Does This Affect Our Lives

Comment by Prof. Tomasz Ciach, from the Faculty of Chemical and Process Engineering:

On Wednesday, October 9, the Royal Swedish Academy of Sciences announced the awarding of the Nobel Prize in Chemistry. The prize was given for two thematically connected achievements: "numerical protein design" and "numerical prediction of protein structures." The first part of the prize went to David Baker from the University of Washington, Seattle, USA. The second part was awarded to Demis Hassabis and John M. Jumper from DeepMind, a Google subsidiary specializing in artificial intelligence.

David Baker was born on October 6, 1952, in Seattle (USA). He is considered a pioneer in computational methods for designing and predicting the three-dimensional structures of proteins using artificial intelligence. Since creating the first protein unseen in nature in 2003, he has developed a range of new proteins with many potential applications. He has also founded several biotech companies. The role of his research in advancing medicine is best evidenced by the fact that in 2024, Time magazine recognized him as one of the 100 most influential people in health research.

Briton Demis Hassabis, born on July 27, 1976, began his career designing computer games with artificial intelligence. He is co-founder of the British-American DeepMind research laboratory (Google) and co-author of the AlphaFold algorithm. Hassabis is also an advisor to the British government on AI technology development.

John Michael Jumper was born in 1981 in Little Rock, USA. Together with Demis Hassabis, they developed the AlphaFold AI algorithm—a model that predicts the three-dimensional structure of proteins based on their amino acid sequences. In 2021, Nature magazine named him one of the top ten most significant people in science. John Jumper currently works at DeepMind in London.

In 2020, Demis Hassabis and John Jumper presented the AlphaFold2 AI model. Thanks to it, they were able to predict the three-dimensional structure of almost all known proteins. Since their breakthrough, AlphaFold2 has been used by more than two million researchers in 190 countries. The main authors of the AlphaFold algorithm were soon recognized as serious contenders for the Nobel Prize. A publication on the AlphaFold algorithm in Nature in 2020 has been cited over 13,000 times. Only about 500 out of roughly 61 million scientific publications have been cited more than 10,000 times, which speaks volumes about the importance of this achievement.

In general, the 2024 Nobel Prize in Chemistry was awarded for the use of artificial intelligence algorithms to predict protein structures and design amino acid sequences to achieve specific three-dimensional structures. Why is this research so important? Proteins are the fundamental building blocks of life as we know it on Earth. They not only form the mechanical structures of life, such as human skin, hair, and muscles, but they also serve as microscopic working machines—true nanorobots that put life in motion. Proteins provide energy to life and make it function at its most fundamental molecular level.

Although we have long known how to determine the sequence of amino acids in a linear structure and even synthesize amino acid chains, predicting how the three-dimensional structure would look has been very challenging and, for larger proteins, almost impossible. Understanding the three-dimensional structure helps us comprehend how a protein functions and how a chemical molecule, such as a drug, interacts with it. This knowledge allows for designing better drugs or targeting new proteins. Additionally, it helps combat antibiotic resistance in bacteria and discover new antibiotics. Designing new proteins opens possibilities not only for developing new drugs but also for creating new enzymes to break down plastic packaging or other waste produced by our civilization. It could lead to new methods of food production or clean energy, and in the future, it may even enhance life itself, improving plant efficiency or perhaps even our own biological structure.