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30 September 2025

In a new study, researchers from Karolinska Institutet (KI) showed that a specific gene influences how cells move, and that it can therefore cause various rheumatic diseases. Two researchers from ҳ contributed to this discovery through modeling that predicted the gene’s impact on cells, and now the researchers hope this could lead to new treatments.

Photographer: Olov Planthaber

Researchers from Karolinska Institutet and Linköping University collaborated in a study mapping the gene DIORA1 (FAM167A). The gene is associated with autoimmune rheumatic diseases, but until now it has been unknown why.

“We have long known that DIORA1 is linked to autoimmune diseases, without understanding its function. Now we show that the gene regulates the cell’s ability to move by interacting with a group of proteins known as MRCK kinases,” says Marie Wahren-Herlenius, Professor at the Department of Medicine Solna, Karolinska Institutet and corresponding author of the article.

Kinases are proteins important for the body’s skeleton, and researchers at KI have shown that the DIORAA1 gene binds to MRCK kinases and affects their activity. This leads to changes in the structure and movement of the affected cell. But before they could experimentally prove the gene’s function, they received help from Björn Wallner and Maria Sunnerhagen, researchers at the Department of Physics, Chemistry and Biology, Linköping University.

Interdisciplinary Collaboration

Marie Wahren-Herlenius turned to Björn Wallner, at the Division of Bioinformatics at LiU, when investigating how DIORA1 interacted with MRCK kinases. Björn is a world leading researcher in protein structure modeling and has further developed the Nobel Prize-winning AI tool AlphaFold. His work has made the method even more accurate in predicting both the three-dimensional structure of proteins and how they interact with each other, based on the amino acid sequence.

“They had indications of an interaction but didn't know exactly how it could look at the molecular level. This was challenging partly because MRCK is a very large protein, and partly because DIORA1 is flexible and only adopts its structure when interacting with a partner such as MRCK. So we really had to push the limits, but we greatly benefited from having access to Sweden’s largest supercomputer here in Linköping.”

Maria Sunnerhagen
Maria Sunnerhagen
DIORA1 is an intrinsically disordered protein, which makes its interactions difficult to characterize with classical experimental methods that have been optimized for interactions between well-ordered proteins. Maria Sunnerhagen, Professor of Structural Biology, conducts research on disordered proteins and how their complexes can be experimentally characterized.

“In this interdisciplinary team, by combining our different expertise and experiences in a new way, we have succeeded in describing how a disordered protein regulates another dynamic process: how cells move,” says Maria Sunnerhagen.

Through advanced modeling, Björn was able to predict how the protein could interact at the molecular level, which the team at Karolinska Institutet then verified experimentally.

“This demonstrates the power of combining AI-based structure prediction with experimental biomedical research,” says Björn Wallner.

Using a method called proximity proteomics, where they identified which proteins are located close to DIORA1 in the cell, the KI team was able to confirm the interaction with MRCK kinases and map out exactly how the proteins connect. By reducing the expression of DIORA1 in human cells with the help of CRISPR technology, the researchers observed changes in gene activity and protein modifications related to cell movement, as well as an increased ability of the cells to invade their surroundings.

“Understanding how genes such as DIORA1 function at the cellular level is important for revealing the mechanisms behind rheumatic diseases and can contribute to the development of new treatments in the future,” says Marie Wahren-Herlenius.

This article is partly based on a news item from .

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