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A Nobel Past, Present, and Future: The Central Role of Protein Design in Human and Planetary Impact

Proteins are the workhorses of life, executing virtually every biological function on Earth. The human body alone is composed of about 100,000 unique proteins that enable us to think, see, move, and feel—facilitating every human experience. Yet, the proteins we know are just a minuscule fraction of what’s theoretically possible. There are an estimated 10500 unique proteins that could exist—a number so astronomical it dwarfs the number of stars in the observable universe, which is about 1024.


Each of these potential proteins possesses unique properties, some subtly different from others, and some with entirely novel functionalities. Unlike exploring distant stars, we don’t need rocket ships to discover these proteins. Advances in computational biology, chemistry, and biotechnology have empowered us to design and characterize any of these proteins in a matter of weeks and at a cost of around $100. This leads us to the pivotal challenge: How can we search through this vast protein universe to find those that meet our specific needs?


This is where the groundbreaking work of Dr. David Baker – one of this year’s Nobel Laureate in Chemistry – and collaborative scientific communities like RosettaCommons comes into play. RosettaCommons, founded by Dr. David Baker, is a consortium of research laboratories that develop software tools to that allow us to search through this vast protein universe. Their collective efforts have revolutionized our ability to navigate this vast protein universe. By developing sophisticated algorithms and tools, they’ve essentially created a”Google Search” for proteins, enabling us to find proteins with specific properties amid an astronomical search space.



These efforts didn’t just begin recently; the ability to search this vast protein space has been foundational to the modern bioeconomy since the early 1970s. During that time, our capacity to engineer biology began to flourish—with Nobel-recognized contributions from scientists like Paul Berg, Walter Gilbert, and Frederick Sanger. Since then, we’ve been building a bioeconomy now valued at around $4 trillion globally. Designed proteins such as insulin, antibodies, cellulases, amylases, and neutral proteases have become ubiquitous in medicine, materials science, and the food industry. These proteins are instrumental in producing pharmaceuticals, enhancing laundry detergents, and improving the shelf life and quality of bread, cheese, and wine.


The tools and techniques for protein design have evolved dramatically from their foundation in the 1970s. In the 1980s, computational modeling of proteins opened new avenues for understanding protein structure and function, leading to Nobel Prizes for Martin Karplus, Michael Levitt, and Arieh Warshel. The 1990s saw the advent of directed evolution, a method to rapidly evolve proteins with desired properties—a breakthrough that earned Frances Arnold, George Smith, and Gregory Winter the Nobel Prize.


Building on these foundations, the scientific community has pushed the boundaries even further. By integrating computational modeling with advancements in artificial intelligence and machine learning, Dr. David Baker and researchers within RosettaCommons and beyond have developed methods to design entirely new proteins in silico. This approach allows scientists to predict and engineer proteins with specific functions, without being limited to those found innature. It’s like having a search engine that can not only find existing pages but also create new ones tailored to your exact needs.


This capability has immense implications. It accelerates the development of new therapeutics, enzymes for industrial processes, and materials with novel properties. For example, it has led to the creation of treatments for conditions like celiac disease, innovative vaccines, and enzymes that can perform previously impossible chemical reactions. Such advancements highlight the transformative potential of computational protein design in addressing some of humanity’s most pressing challenges.


Companies like Digestiva and Vinzymes are at the forefront of applying these cutting-edge tools. By leveraging computational protein design methods they have discovered novel enzymes that can revolutionize the food industry—Digestiva by amplifying the nutritional value of proteins, and Vinzymes by unlocking the potential of phenolics. These innovations address longstanding challenges, offering solutions that benefit both human health and the environment.


While we’re witnessing remarkable progress, this is just the beginning. The success rate of designing functional proteins is still around 1%, even with optimal search parameters. However, the field is advancing rapidly, attracting attention from tech giants like Meta, TikTok, Salesforce, Google, and NVIDIA, who are entering the realm of biology with their computational expertise.


As we stand on the cusp of a new era in biotechnology, the possibilities are virtually limitless. The integration of computational tools with biological science is unlocking solutions to problems once thought insurmountable. By continuing to develop and refine these technologies, we can create high-efficacy, low-cost, precision solutions that promote human health and environmental sustainability.



Dr. Justin Siegel is a Professor at the University of California, Davis, specializing in Genomics, Chemistry, Biochemistry, and Molecular Medicine. A former member of the Rosetta Commons community (2005–2011), he pioneered the development of enzyme design tools and continues his work in computational protein design. He also serves as the Ciocca Visiting Professor in Entrepreneurship at the UC Davis Graduate School of Management.

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