Topos Bio, an AI-powered biotechnology company, today introduced two new AI foundation models. The first is Topos-2, built to predict how intrinsically disordered proteins (IDPs), which are dynamic in nature, move and change shapes. The second is Topos-Bind, a first-of-its-kind model designed to predict how these dynamic proteins interact with potential drug molecules. Together, these models represent a significant advancement in AI-driven drug discovery, addressing a class of disease-causing proteins historically difficult to study and target.

Topos Bio’s mission is to build foundation models to drug historically “undruggable” targets, disease-causing proteins that resist traditional drug therapies and tools. These targets, comprising close to two-thirds of all proteins in humans, are major drivers of the most aggressive cancers and neurodegenerative diseases including Alzheimer’s, Parkinson’s, ALS, and Huntington’s. They represent a combined commercial opportunity of more than $200 billion a year, and until now, the industry has had no rational way to design drugs against them. That’s why only a handful of drugs have been produced that halt disease progression at all.

“The hardest problems in biology aren’t hidden because we’ve lacked computing power, they’re hidden because we’ve lacked the right data and models,” said Ryan Zarcone, CEO and co-founder of Topos Bio. “We’ve built Topos around a simple premise: if we can understand how these proteins move and interact, we can design medicines for diseases that have long remained beyond the reach of modern drug discovery, and ultimately change the trajectory of patients’ lives.”

Topos-2 builds on Topos-1, its predecessor which generates conformational ensembles for disordered proteins and regions. Topos-2 extends this capability to proteins that have both disordered and ordered regions, a closer match to how these proteins actually work in the body. On PeptoneBench, an external experimental benchmark measuring performance on these dynamic proteins, Topos-2 ranked first among over 10 evaluated models on agreement with experimental data, including NMR chemical shifts and SAXS. It outperformed other frontier models such as Microsoft Research’s BioEmu, Google DeepMind’s AlphaFold-2, and Boltz’s Boltz-2. Early testing put it nearly 4x closer to experimental ground-truth than the next-best model and showed that Topos-Bind was the only model able to predict how the shape of amyloid-beta, an Alzheimer’s target, changes in response to drugs.

Where Topos-2 models these dynamic proteins on their own, Topos-Bind predicts how they interact with drugs, giving deeper insight into new ways to target disease-linked proteins. No other existing model does this today. To train it, Topos Bio assembled the largest experimental datasets of small-molecule binding measurements against IDPs – at least two orders of magnitude larger than previously reported datasets – along with the largest physics-based corpus of IDR-ligand systems.

“Most AI protein models predict one best structure per sequence, but disordered proteins don’t have one shape, they exist as a shifting ensemble, so a single-structure model is answering the wrong question,” said Amir Khosrowshahi, CTO and co-founder of Topos Bio. “Topos Bio’s models generate a full ensemble of conformations a protein can actually adopt. From there, the models learn how a drug acts across that shifting landscape, not just where it binds in one snapshot, but how it changes the protein’s behavior.”

Topos-2 and Topos-Bind are currently being applied across Topos Bio’s internal discovery programs in neurodegeneration and oncology. That real-world application is already reshaping how the team thinks about the diseases they’re targeting.

“Many of the proteins most relevant to neurodegenerative disease are also among the hardest to study because they do not remain in one shape,” said Steven Finkbeiner, MD, PhD, Director of the Center for Systems and Therapeutics at Gladstone Institutes and a scientific collaborator with Topos Bio. “For years, the field has lacked sufficient experimental data to connect the motion of these proteins to their molecular interactions. Combining large-scale data generation with AI models designed for dynamic proteins could help address this gap and advance our understanding of disease biology and the search for new therapeutics.”

Topos Bio purposely chose to start with intrinsically disordered proteins, the extreme version of this problem, because solving it first forces the right approach from day one. That same framework is built to extend to the broader universe of dynamic, context-dependent drug targets that conventional discovery has never been able to reach.

About Topos Bio

Topos Bio is an AI-powered biotechnology company developing therapies for intrinsically disordered proteins (IDPs). Headquartered in San Francisco, the company’s platform integrates physics with generative AI to target disordered proteins across disease areas such as neurodegeneration and oncology. Topos Bio is backed by Boldstart, Threshold, Neo, and notable angel investors.

Media gallery

About The Author
Business Wire