There seems to be a notable shift in the way the Nobel Prize committee members award recipients this year. Rather than having a narrow focus on the specific area of study for each award, a broader perspective seems to be occurring. The recently announced Nobel Prize in Physics highlighted this trend by recognizing two pioneers in artificial intelligence. While physics was integrally involved in their work, their achievements were not isolated to physics alone. Now, the same trend has occurred in relation to the 2024 Nobel Prize in Chemistry. Three researchers have been co-awarded the Nobel Prize for AI innovation in protein design, and while their work certainly involves chemistry, it pertains directly to generative AI.
The 2024 Nobel Prize in Chemistry was given to three protein researchers–specifically, Dennis Hassabis, John Jumper, and David Baker. Hassabis and Jumper were able to leverage AI to predict protein structures. Baker, on the other hand, used AI innovation in protein design to create completely new proteins. In all cases, however, each recipient not only has a strong university research background but private sector experience as well. Given this, it’s evident that the Nobel Prize committee looked beyond the academic world in their considerations. As public-private collaborations increase, and as AI’s impact becomes more pervasive, so too are the candidates for Nobel Prize awards.
Solving the Protein Folding Problem
In chemistry, it’s well known that protein structures play a significant role in physiological functioning. Depending on how a protein compound folds and contorts greatly affects how it works. Therefore, being able to predict proteins’ structures offers many important insights into disease, medication treatments, and more. Scientists for decades have been trying to predict this, and the progress has been notably slow. But Hassabis and Jumper used an AI innovation in protein design to speed up the process. In essence, AI applications were able to predict protein structures in the more than 200 proteins known to exist in all organisms. What would have taken many years was accomplished within hours as a result. This is why they share the 2024 Nobel Prize in Chemistry this year.
Hassabis has both a computer science degree and neuroscience background from Cambridge. But his claim to fame is the launching of DeepMind in 2010 as an AI startup that Google subsequently acquired for $650 million. Jumper also has an extensive academic background but in theoretical chemistry. Notably, however, Jumper joined Hassabis at DeepMind in 2017 where they created their AlphaFold 2 Model. This model was introduced in 2020 showing that the “protein folding problem” had been effectively solved. Since that time, biochemists have used their AI innovation in protein design to develop drugs and other compounds. Based on the future impact of their work, it’s understandable why they were selected for the 2024 Nobel Prize in Chemistry.
AI Innovation in Protein Design
Defining existing protein structures are notably important in both chemistry and medicine. But at the same time, developing new proteins with unique properties also has great potential in these fields. This is why the 2024 Nobel Prize in Chemistry was also awarded to Baker this year. Interestingly, Baker is known to have designed a new protein unlike any known ones as far back as 2003. This is well before artificial intelligence was available. But since that time, Baker has gone on to use AI innovation in protein design to develop many others. Not only has his discoveries been utilized for drug and vaccine development but for new nanomaterials and sensors. His work was also integral in the development of the COVID antiviral nasal spray as well as new Celiac disease drugs.
Like his co-recipients of the 2024 Nobel Prize in Chemistry, Baker has a strong academic research background. This includes extensive study and research in biochemistry at Harvard, UC Berkeley, and the University of Washington. But just as important is Baker’s endeavors in the private sector. Just as Hassabis and Jumper pursued their research at Google, Baker launched private enterprises as well. In fact, he has cofounded over 20 different biotech companies over the course of his career. Leveraging his computational AI innovation in protein design, Baker has impacted numerous fields. Certainly, his contributions in chemistry are now well recognized. But his achievements will continue to have widespread benefits in many fields for decades to come.
Better and Stronger Through Collaboration
Two major takeaways can be appreciated from the 2024 Nobel Prize in Chemistry choices this year. First, it would seem research and discoveries in chemistry are expanding beyond primary chemistry experiments. Instead, the field has expanded into new directions as is evident by the AI innovation in protein design and protein research. Experts acknowledge that there is an increasing reliance on computational research for chemistry explorations. Hassabis, Jumper, and Baker each highlight these new directions for the field of chemistry. It would thus seem the Nobel Prize committee has accepted this view in making this year’s decisions. This is not the first time researchers outside primary chemistry have won. However, a broader perspective of chemistry achievements is likely in years to come.
The second major takeaway is the increasing collaboration between academic and private sector endeavors. Google has invested in research in a variety of areas with DeepMind being a great example of their efforts. Likewise, the biotech firms cofounded by Baker showcases the need to bridge gaps between science and business efforts. While AI innovation in protein design is the main theme this year, so is the recognition of private industry contributions. Like Bell Laboratories did decades earlier, other private firms especially in AI are leading the way. With the 2024 Nobel Prize in Chemistry going to combined academicians and private researchers, this message is clear. Leveraging private support to optimize research discoveries in AI and elsewhere will serve science well in years to come.
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