International researchers have developed a novel method for mapping protein interactions within the human body, offering a potential breakthrough in the understanding and treatment of rare diseases – conditions affecting an estimated 300 million people worldwide.Published this month in *Briefings in Bioinformatics*, the new methodology promises more accurate diagnostics and targeted therapies by visualizing the complex ‘social networks’ of proteins. The collaborative effort, involving scientists from Spain and the European project EURAS, focuses initial applications on a group of genetic disorders known as RASopathies, including Noonan and Costello syndromes.
A new tool developed by the SIBIUMA group is advancing understanding and treatment of rare diseases
Researchers have developed a new method for analyzing the complex interactions between proteins in the human body, potentially opening doors to improved diagnostics and therapies for rare diseases. The work, a collaboration between scientists at the University of Málaga, Spain’s IBIMA Platform BIONAND, the Biomedical Research Networking Centre for Rare Diseases (CIBERER), and the National Bioinformatics Institute (INB/ELIXIR-ES), represents a significant step forward in unraveling the complexities of these often-challenging conditions. Understanding these intricate protein interactions is crucial for developing effective treatments.
The study, published in the scientific journal ‘Briefings in Bioinformatics’, introduces a powerful methodology for mapping these protein relationships.
“Imagine the proteins in our body as people in a vast social network, and their interactions are the ‘friendships’,” explained James Richard Perkins, a researcher in the Department of Molecular Biology and Biochemistry and one of the study’s authors. “To understand which groups of proteins work together in biological functions or diseases, it’s crucial to identify their ‘communities.’ The challenge is that, just as a person can belong to multiple groups of friends, a protein can be involved in multiple biological processes simultaneously.”
Traditional methods often assigned each protein to a single community, oversimplifying the reality and losing valuable information, according to Perkins. To overcome this limitation, the researchers developed a strategy that reflects the way individuals participate in multiple social circles.
Key Aspects of the Advancement
The breakthrough centers on creating a new ‘biological map’ that accounts for the multiple ‘social circles’ of each protein. This innovative tool represents protein interaction networks in a simpler, more intuitive mathematical space. According to Perkins, the technology essentially transforms a complex road map into one where cities – representing proteins with similar functions – are grouped closer together. This approach facilitates the detection of hidden relationships and offers new possibilities for understanding how these molecules organize and collaborate in cellular processes.
To achieve this, the scientists significantly improved an algorithm known as Hierarchical Link Clustering (HLC), which is capable of identifying overlapping protein communities. This capability is essential because, “in real biology, just like in social life, the same element can be part of different groups.” “Just as a person can belong to several circles of friends, a protein can be involved in different biological functions, and this methodology allows us to capture precisely that complexity,” the researchers stated.
They also optimized the representation of known biological pathways by restricting the algorithm’s ‘random walks’ within these communities defined by HLC. “This drastically improved the accuracy of the digital map: now, proteins that participate in the same biological route tend to appear much closer to each other. This improvement in map navigation allows for a clearer and more efficient study of the interactions and functions of biological systems,” concluded the University of Málaga scientist.
Part of the SIBIUMA scientific team in the University Botanical Garden, in front of the Faculty of Sciences
Direct Impact on Rare Diseases: The Case of RASopathies
The methodology has been applied to a group of related rare diseases known as RASopathies. These conditions, caused by mutations in genes within a key pathway (RAS/MAPK), present a wide range of symptoms. Despite advances in genetics, the complete mechanisms driving these diseases and the connections between them remain unclear. This research offers a new avenue for exploring these complex relationships.
Using this new approach, the researchers were able to better represent the known pathways of RASopathies and identify new candidate genes potentially associated with these diseases, including syndromes like Noonan and Costello. The team’s involvement in the European project EURAS, which aims to study these diseases and develop specific therapies, informed their choice to focus on this group of conditions. The University of Málaga research group is participating in the EURAS investigation into these rare genetic disorders, as detailed on the EURAS project website.
What Does This Mean for the Future?
This advancement opens the door to “important biomedical applications.” By better understanding how genes interact and how biological pathways are organized, researchers can identify potential new therapeutic targets, which are essential for developing more precise and effective drugs. The findings could accelerate the development of targeted therapies for rare diseases.
The study also reveals an interesting molecular connection between RASopathies and certain types of cancer. This coincidence suggests that existing cancer treatments could potentially be repurposed to address these rare conditions, offering a concrete hope for many patients.
Furthermore, the authors have made the optimized tools used in this work available to the scientific community, fostering collaboration and the application of these methods in other biomedical contexts.
Collectively, this “achievement” – the result of cooperation between leading research institutions – represents a decisive step toward a deeper understanding of biological networks. And, more importantly, “offers a more promising future for the diagnosis and treatment of diseases that have until now posed enormous medical and scientific challenges.”
Study Reference:
Federico García-Criado, Pedro Seoane, Elena Rojano, Juan A G Ranea, James R Perkins, Advancing edge-based clustering and graph embedding for biological network analysis: a case study in RASopathies, Briefings in Bioinformatics, Volume 26, Issue 4, July 2025, bbaf320, https://doi.org/10.1093/bib/bbaf320
