Dalriada Drug Discovery and Topos Bio have announced a strategic research collaboration aimed at accelerating drug discovery for intrinsically disordered proteins (IDPs), a challenging class of therapeutic targets linked to multiple diseases.

Under the partnership, Topos Bio will leverage Dalriada’s advanced capabilities in protein mass spectrometry and chemoproteomics to strengthen experimental validation of its AI-driven drug discovery programmes. The collaboration seeks to bridge the gap between computational predictions and real-world biological validation, particularly for protein targets that lack stable structures and are difficult to study using conventional approaches.

Dalriada will deploy a suite of complementary mass spectrometry- and proteomics-based techniques to generate high-resolution insights into protein–small molecule interactions. These include target engagement profiling, intact mass and peptide mapping analyses, covalent binding kinetics and mechanism-of-action proteomics. The data generated will support site-level engagement analysis, selectivity profiling and pathway-level understanding, enabling more informed decision-making during drug development.

Commenting on the collaboration, Diana Kraskouskaya, CEO of Dalriada Drug Discovery, highlighted the importance of integrating experimental precision with computational insights, particularly for structurally complex targets like IDPs where traditional methods fall short.

Ryan Zarcone, Co-founder and CEO of Topos Bio, emphasised that high-quality experimental data is critical to refining AI-generated hypotheses, especially in the context of dynamic and flexible protein structures.

Intrinsically disordered proteins are estimated to make up around 30–40 percent of the human proteome and are associated with diseases such as neurodegeneration, cancer and metabolic disorders. Their lack of fixed structure makes them difficult to target using traditional structure-based drug discovery methods, underscoring the need for integrated approaches combining AI and advanced experimental biology.

The collaboration reflects a broader industry shift toward combining computational modelling with high-resolution experimental techniques to expand the scope of druggable targets and accelerate the development of therapies for complex diseases.