Understanding how proteins interact is essential to decoding cellular processes and communication. In a groundbreaking study, researchers at the Friedrich Miescher Institute (FMI) have explored how every possible mutation in a protein affects its ability to bind with its partners, shedding light on how mutations influence cellular functions and the evolution of proteins.
Proteins: The Cellular Workhorses
Proteins are essential molecules that perform a variety of tasks, from catalyzing chemical reactions to enabling communication between cells. To function correctly, proteins must bind with specific partner molecules. Errors in these interactions can disrupt cellular processes and contribute to diseases.
The sequence of amino acids in a protein determines its ability to bind to other molecules. Changes in this sequence - mutations - can alter how a protein interacts with its partners, potentially influencing its function and the health of the cell.
A Comprehensive Look at Protein Mutations
To understand how mutations affect protein interactions, researchers in Guillaume Diss’s lab at FMI studied a protein called JUN, which plays a vital role in DNA binding and cellular signaling. The team introduced mutations into every amino acid of JUN and tested how these changes influenced its interactions with 54 different partner proteins.
The study revealed two key effects of mutations on JUN. First, some mutations affected binding affinity, which refers to how strongly JUN binds to all its partner proteins. A higher binding affinity means the protein attaches more effectively to its partners, while a lower affinity means weaker interactions. Second, other mutations influenced specificity, or JUN’s ability to selectively bind to certain partners over others. This determines how precisely JUN can "choose" its partners. These two factors are interconnected: mutations that increase specificity for one partner often reduce binding affinity for others.
Implications for Evolution and Medicine
This study is the first to examine how all possible mutations in a protein influence interactions with an entire family of partners, offering new insights into how proteins adapt and evolve. By decoding these interaction rules, the research opens avenues for predicting how mutations might lead to diseases.
Such predictive models could play a critical role in personalized medicine. For instance, understanding how genetic variations affect protein interactions might help assess individual risks for conditions like Alzheimer’s disease or type 2 diabetes, paving the way for targeted treatments. Guillaume Diss noted that this work helps bridge the gap between the complex behavior of proteins and their roles in health and disease.
Original publication:
Alexandra M. Bendel, Andre J. Faure, Dominique Klein, Kenji Shimada, Romane Lyautey, Nicole Schiffelholz, Georg Kempf, Simone Cavadini, Ben Lehner, & Guillaume Diss The genetic architecture of protein interaction affinity and specificity Nature Communications (2024) Advance online publication
