The 2024 Nobel Prize in Chemistry points to a new protein-powered era of biological discovery

The 2024 Nobel Prize in Chemistry was recently awarded to David Baker, Demis Hassabis, and John Jumper for their work on protein design and structure prediction. This well-deserved prize highlights the key role proteins will play in the next era of biological discovery. It shows how the integration of biological knowledge, programing know-how, and hands-on validation can lead to astounding advances in basic and applied biology. Below we outline how next-generation proteomics platforms can synergize with the fruits of this Nobel-winning work by revealing the broadscale proteomic and proteoform-specific contexts in which protein structures exist. Combining understanding from the fields of structural biology and proteomics will add actionable depth to our understanding of life.

The 2024 Nobel Prize in Chemistry – High throughput protein design and structure prediction 

As outlined in the Nobel Committee for Chemistry’s scientific background for the award, accurate prediction of protein structure from primary amino acid sequence has been a goal for decades. The Baker lab approaches this problem from an applied biology perspective. They generally start their work knowing what structures they’d like to create and work within the rules of protein folding to find their way back to primary sequence. They have incorporated known principles guiding the formation of protein domains into their Rosetta software suite at a massive scale. Over years of development, the Baker Lab has designed and tested ever more complicated protein structures and even created proteins with entirely novel functions (E.g. Jiang et al. 2008).  

In their work at Google’s DeepMind, Hassabis and Jumper built upon decades of work generating protein crystal structures, correlating changes in genomic sequencing data across evolutionary trees, and optimizing machine learning algorithms to accurately predict protein structures from known sequences. Using their AlphaFold software, it is now possible to input the primary sequence of most proteins and get back largely accurate protein structure predictions. Seeing the power of AlphaFold, the Baker Lab has even incorporated some of its underlying methodologies into the latest Rosetta software – a testament to the fruitful cross-pollination that occurs in the protein modeling field. 

With technologies like these, researchers can design and predict protein structures in a high throughput way. High throughput is the key here as X-ray crystallography and other means of determining protein structure experimentally are notoriously difficult and time consuming.  

Combining high-throughput structural biology with broadscale proteomics 

The genomics era has revealed that, to understand biology, we need much more information about the active proteins in biological systems. Thus, the next era of biology will be one that focuses on the billions of proteins that determine cell and tissue function. High-throughput technologies like those developed by these 2024 Nobel Laureates may enable researchers to investigate protein structure-function relationships at the scale of the proteome.  

This is critical because proteins do not operate in isolation. Their functions are impacted by biological context and especially what other proteins they interact with. Having high-throughput means of modeling protein structures may enable researchers to combine broadscale proteomic data with structural data and develop hypotheses about how these proteins cooperate to achieve particular phenotypes. 

Indeed, combining broadscale proteomic and protein structural datasets will likely improve both fields. On the proteomics side, being able to link structural data to the proteome may help researchers discover how protein abundance differences change biology. On the protein structure side, combining proteomic and high-throughput structural models may enable researchers to point to situations where structures do not add up given proteomics-predicted interactions. Their models can then be altered to better reflect the data. This kind of iterative work will hopefully vastly advance our understanding of biology. 

A starting-point for incorporating proteoform data into structure function-relationships 

Researchers are beginning to appreciate that individual protein species come in many, many different forms due to processes such as genetic mutation, alternative splicing, phosphorylation, and more. The resulting patterns of modification create myriad “proteoforms” which may have distinct interactions, structures, and ultimately functions. As novel proteomics technologies show us how combinations of proteoforms change phenotypes, researchers can map the patterns of modification that define proteoforms onto structural models, hypothesize how modifications might change structure, and test these hypotheses. With incredible modeling capabilities and novel proteoform-aware technologies, the foundations are in place for researchers to discover the mechanisms through which proteoforms change biology. 

Designing new ways to alter biology 

As broadscale proteomic and proteoform data are incorporated into new models created by researchers designing proteins, we’ll have entirely new ways to alter biological systems. With more broadscale proteomic data, researchers may get better at predicting the ways proteins interact with one another to adopt new structures. Researchers can hopefully use this information to design protein complexes that accomplish more complex tasks than the proteins designed today. 

With proteoform-level detail, researchers may be able to predict the propensity for structures to be modified in situ and design proteins to be altered to achieve desired outcomes. Perhaps researchers will design proteins that only adopt active forms once phosphorylated at numerous sites. Perhaps they’ll finely tune the degradation of designed structures. Or perhaps still they’ll design proteins to alert researchers to unexpected or dangerous changes in biological systems resulting from the generation of proteoforms.  

All this and more is possible in the next era of biological research whose foundations are set by these Nobel Prizes. We cannot wait to see the benefits that accrue to all of life science research as a result.