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A research consortium co-led by the Buck Institute and Georgetown University has received an ARPA-H award of up to $51.7 million for a four-year effort to predict when flexible proteins begin shifting toward disease-associated states. The project will combine computational models with laboratory experiments, initially studying proteins relevant to Alzheimer’s disease and Ewing sarcoma; it has not yet produced a diagnostic or treatment.
A consortium co-led by the Buck Institute for Research on Aging and Georgetown University has received an award of up to $51.7 million from ARPA-H for a four-year effort to predict how flexible proteins change before they cause disease-associated damage. The project, initially focused on Alzheimer’s disease and Ewing sarcoma, aims to turn those predictions into potential ways to detect and eventually influence harmful protein changes; it has not yet produced a diagnostic or treatment.
The research effort, called SEEDS—Sequence-to-disease: Environment-aware Ensembles of Disordered proteins at Scale—will study proteins known as intrinsically disordered proteins (IDPs). Unlike proteins that settle into a relatively stable three-dimensional structure, IDPs can take on many shapes. The team will examine how their behavior changes with conditions inside cells, including acidity, molecular crowding, metals, metabolites and chemical modifications.
The consortium is co-led by Priyanka Joshi, an assistant professor at Georgetown University School of Medicine, and Chuankai (Kai) Zhou, an assistant professor at the Buck Institute. It brings together researchers from nine academic institutions and seven industry partners, combining expertise in protein science, artificial intelligence, computational modeling, cancer and neuroscience. The source report says the effort links Georgetown’s INTREPID and the Buck Institute’s SHIFT teams.
SEEDS plans to pair physics-guided AI and computational predictions with experiments that measure protein behavior under different conditions. The aim is to develop models that connect a protein’s sequence and cellular surroundings to the range of shapes and behaviors it may adopt, then test and refine those predictions in the laboratory. The source report describes this as a research goal, not a validated method already available for clinical use.
Why Early Protein Changes Matter
Protein misfolding and aggregation are associated with Alzheimer’s disease, amyotrophic lateral sclerosis (ALS), some cancers and other chronic or degenerative conditions. The project focuses on changes that could occur before proteins clump together or cause lasting cellular damage. If researchers can identify reliable warning signs at that stage, the work could eventually inform earlier detection or approaches to altering harmful protein behavior.
That possibility addresses a challenge in conventional drug development. Many proteins implicated in these conditions are described as “undruggable” because they do not hold a stable shape with the binding pockets that many drugs are designed to target. A better account of how these proteins behave across different environments could help researchers identify new points for intervention. But the award funds an investigation into that possibility; it does not establish that a new drug target, diagnostic test or treatment will result.
The approach also matters because it seeks to go beyond snapshots of proteins. Researchers can capture images or measurements of some proteins, often after they have already clumped, but the source report says their behavior as cellular conditions change is difficult to predict reliably. SEEDS will test whether combining large-scale modeling with targeted experiments can make those changing states more understandable.
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The Challenge of Flexible Proteins
Many protein-modeling advances have drawn on large collections of known structures. The source report notes that AI tools such as AlphaFold have transformed protein science by learning from decades of accumulated structural data. Researchers have much less structural information for intrinsically disordered proteins, according to Zhou, making their behavior harder to model using approaches built around stable structures.
SEEDS is part of ARPA-H’s BIOmolecular Grammar for protein Aggregation Modulation and Intervention (BIOGAMI) program, led by ARPA-H Program Manager Shannon Greene. BIOGAMI focuses on early stages of protein dysfunction, before misfolding or aggregation causes lasting cellular damage. Its “molecular grammar” concept refers to finding rules that link protein sequences and surrounding conditions to protein behavior.
For SEEDS, that means studying many proteins and environments while also examining selected cases closely enough to test how context changes what a protein does. The project’s combination of computational work and experiments is intended to address gaps in the available data and check whether model predictions match observed behavior.
“We aim to uncover the principles that determine when these proteins remain in healthy functional ensembles and when they begin to shift toward disease-associated states.”
— Chuankai (Kai) Zhou, assistant professor at the Buck Institute
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What the Award Cannot Yet Show
The award supports a four-year research effort, and the source report does not describe a completed model, diagnostic test or treatment. It remains unclear which specific proteins will yield the most predictive results, how accurately the team will be able to forecast harmful changes, or whether predictions can be translated into practical interventions.
The report also does not specify how much of the award will be paid initially, the schedule for funding, or intermediate project milestones. The announced amount is up to $51.7 million, not a statement that the full sum has already been disbursed. While Alzheimer’s disease and Ewing sarcoma are named as initial areas of focus, detailed study targets and timelines are not provided.
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Testing Models Against Experiments
During the project’s four-year period, the team is expected to generate data on disordered proteins across different conditions, build computational predictions from those data and compare the predictions with laboratory measurements. The key next evidence will be whether the models can reliably anticipate changes in protein behavior beyond the cases used to develop them.
Researchers will also need to establish whether any predicted early warning signs can be detected in disease-relevant settings and whether protein behavior can be redirected safely and effectively. Those are longer-term questions, not outcomes confirmed by the award announcement. Further information about specific targets, milestones and experimental findings is not included in the source report.
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Key Questions
What is the SEEDS project?
SEEDS is a four-year consortium co-led by the Buck Institute and Georgetown University. It will study how intrinsically disordered proteins behave across different cellular conditions, using computational predictions and experiments.
How much funding did the project receive?
ARPA-H awarded the effort up to $51.7 million. The source report does not give a payment schedule or say that the full amount has already been disbursed.
Which diseases are the initial focus?
The project’s initial focus is Alzheimer’s disease and Ewing sarcoma. The report does not list the specific proteins or research milestones for those areas.
Does this mean a new treatment or test is available?
No. The award funds research intended to improve predictions of harmful protein changes and potentially inform future diagnostics or treatments. No new test or treatment is reported as resulting from the project so far.
Why are these proteins difficult to study?
Intrinsically disordered proteins can take on many shapes, and their behavior can shift with conditions inside cells. The source report says researchers have less structural information about them than about proteins with stable shapes, making their behavior harder to predict.
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