Protein, protein, protein!

As part of this, research groups are studying the biological processes involved and in particular how proteins, which are found in blood or expressed by cells, orchestrate interactions that must be coordinated in a fine-tuned manner to work properly, as when they are found to be dysregulated, they may trigger or drive the development of severe diseases. Computational tools have become essential to help researchers gain in-depth mechanistic insights, and artificial intelligence (AI) has made a significant impact on how protein structures are predicted and designed.  

We are very likely only at the beginning of a scientific era that will yield a range of new protein-based technologies and strategies that almost certainly will make a major difference to how we target and treat diseases in the future.

This year’s Nobel Prize in Chemistry went to David Baker, University of Washington, Seattle, WA, USA; Howard Hughes Medical Institute, USA, and Demis Hassabis and John Jumper, Google’s DeepMind. The Nobel Prize was awarded for their groundbreaking work on computational protein design and protein structure prediction. This includes the innovative development of numerous algorithms, tools and techniques that have been combined with AI to revolutionize how proteins can be predicted and built to mediate distinct biological functions. This enormous scientific effort has resulted in software tools, such as RoseTTAfold and Alphafold, that have been made available to the entire research community to speed up further development and biological research. Such computational tools are now being used to study all classes of proteins, ranging from small peptides to large and complex proteins, such as enzymes and antibodies. Importantly, they are also used to construct new versions of the proteins with tailored binding and transport properties, and also to design functional proteins that nature has never seen before. As such, we are very likely only at the beginning of a scientific era that will yield a range of new protein-based technologies and strategies that almost certainly will make a major difference to how we target and treat diseases in the future.

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The Nobel Prize in Chemistry: The amazing structures of proteins

The Royal Swedish Academy of Sciences has decided to award the Nobel Prize in Chemistry 2024 to David Baker “for computational protein design” and Demis Hassabis and John M. Jumper “for protein structure prediction”.

However, to be able to have such an impact, these technological and computational advancements and designed proteins must be put into practical use. It is therefore inspiring to see how the Institute for Protein Design, led by the Nobel laureate David Baker, is actively training and empowering its students and researchers to turn their scientific discoveries into commercial assets, and fostering a culture for spin-out company creation.

Earlier this year, co-director Prof Johanna Olweus received a large Cancer Grand Challenges grant funded by Cancer Research UK and NIH together with the global team “MATCHMAKERS”, which also includes Nobel Laureate David Baker.

In Norway, we have several research groups working on protein engineering, both as soluble molecules and in a cellular context. For instance, at the Centre of Excellence, Precision Immunotherapy Alliance (PRIMA), funded by the Research Council of Norway, where seven PIs have joined forces to develop new precision immunotherapy strategies, there is extensive use of computational tools to gain new knowledge that can guide development. Earlier this year, co-director Prof Johanna Olweus received a large Cancer Grand Challenges grant funded by Cancer Research UK and NIH together with the global team “MATCHMAKERS”, which also includes Nobel Laureate David Baker. Another PI of PRIMA, Jan Terje Andersen, is working with one of the spin-out companies for the Baker lab. Recently, PRIMA also recruited two associated group leaders, Professor Geir Kjetil Sandve and Associate Professor Victor Greiff, both of whom have a key focus on developing machine learning approaches, software platforms, and computational and experimental tools.

The combination of the strengths of different tools allows us to tailor-design protein structures for a multitude of purposes in medicine. However, proteins also have a vast area of application outside of drug design and personalized health. Within the broader area of life science, including utilization of bioresources, a deeper understanding of proteins is expected to pave the way for new insights that will ensure optimal properties and new solutions for food and feed. This year’s winners stated that they will be almost as excited as they are this year, once the Nobel Prize goes to someone using the powers of the computational tools they have developed, to create new groundbreaking discoveries.

Who knows what the future of life science inventions will bring us? Our prediction is that you wouldn’t be completely wrong if you guess that part of the solution may be protein, protein, protein.