AI drug-discovery company Elix and the University of Vienna have formed a research partnership aimed at one of medicinal chemistry’s hardest problems: designing drugs against proteins that refuse to hold a fixed shape.
The Tokyo-based firm will pair its machine-learning platform with the Vienna lab of associate professor Julien Orts, which specializes in nuclear magnetic resonance (NMR) spectroscopy. The collaboration targets intrinsically disordered proteins (IDPs) and proteins involved in epigenetic signaling and cancer — classes long considered “undruggable” because they lack the stable pockets that most small-molecule drugs need.
What each side brings
Elix contributes Elix Discovery, an AI platform for predictive modeling and generating new molecular structures. Vienna contributes atomic-resolution structural biology: NMR spectroscopy, the INPHARMA method for validating how small molecules bind, and eNOE distance measurements the team says reach 0.1-ångström accuracy in resolving the range of shapes a flexible protein adopts.
Why disordered proteins are hard
Most structure-based drug design assumes a target holds still. Intrinsically disordered proteins constantly shift between conformations, so a single static snapshot is misleading. The idea here is to feed AI a richer, dynamic picture of those moving targets rather than one frozen frame.
“By combining our ability to resolve protein dynamics at atomic precision with Elix’s AI-driven generation, we can move beyond static structures,” Orts said. Elix’s chief executive framed the tie-up as a way to pursue the mission “on a global scale, uniting expertise in AI drug discovery.” Financial terms were not disclosed.