UMBC joins super team to take on the “undruggable” misfolded proteins implicated in diseases from Alzheimer’s to some cancers
UMBC is contributing to a multi-institution research project, funded by the Advanced Research Projects Agency for Health (ARPA-H) with up to $51.7 million, that aims to predict how disease-causing proteins misfold before irreversible damage occurs and use those predictions to develop novel diagnostics and treatments. The four-year effort is expected to lead to new ways of detecting, slowing, and treating neurodegenerative diseases and cancer, with an initial focus on Alzheimer’s disease and Ewing sarcoma.
Headshot courtesy of David Garcia
UMBC’s part of the project is led by David Garcia, assistant professor in the Department of Chemical, Biochemical, and Environmental Engineering, whose team will be performing high throughput lab experiments. The whole integrated research consortium, named SEEDS (Sequence-to-disease: Environment-aware Ensembles of Disordered proteins at Scale), brings together researchers from 10 academic institutions and seven industry partners, including the consortium co-leaders, the Buck Institute for Research on Aging and Georgetown University.
“What I find most exciting about this work is that it spans the gap from bench-scale experiments to mature hypotheses for treatments,” says Garcia. “It’s very rare to bring together such large teams, with disparate expertise, and I think that’s how you turn fundamental knowledge into effective treatments. As scientists, I think we’re motivated by solving the puzzle or fixing the problem, so it’s hard to feel more motivated than when you have the chance to both make a dent in understanding the rules of the natural world and turning that understanding into something that can help people.”
The problem of misfolded proteins
Protein misfolding and aggregation are associated with Alzheimer’s disease, amyotrophic lateral sclerosis (ALS), some cancers, and other chronic and degenerative conditions. Many of the proteins involved have long been considered “undruggable” because they lack the stable shapes and binding pockets that most drugs are designed to fit.
Today, researchers can capture snapshots of these proteins, often only after they have already clumped together, but they cannot reliably predict how they will behave as conditions inside the cell change, or when those changes start to become harmful.
To address these challenges, the SEEDS team brings together expertise in protein science, artificial intelligence, computational modeling, cancer, and neuroscience to create a platform that can mitigate disease due to misfolded proteins.
The proteins being studied are called intrinsically disordered proteins, or IDPs. Unlike many proteins that adopt relatively stable three-dimensional structures, IDPs form many different shapes. Conditions inside the cell, including acidity, molecular crowding, metals, metabolites, and chemical modifications, can influence which forms they take and how they behave. That flexibility allows IDPs to perform important functions in healthy cells, but it also makes them extraordinarily difficult to understand and target when something goes wrong.
The goal is to move from describing these proteins one at a time to predicting their behavior from sequence and surroundings alike, and to turn that prediction into ways to detect, and ultimately prevent, the shifts that lead to disease. Importantly, the team will pair computational predictions with experimental measurements, testing protein behavior under different conditions rather than relying on computer models alone.
Team SEEDS is part of ARPA-H’s BIOmolecular Grammar for protein Aggregation Modulation and Intervention (BIOGAMI) program. SEEDS is co-led by Georgetown’s Priyanka Joshi, Ph.D, and the Buck Institute’s Chuankai (Kai) Zhou, Ph.D. BIOGAMI focuses on the earliest stages of protein dysfunction, before proteins misfold or clump together and cause lasting damage to cells. The program uses the idea of a molecular “grammar.” If researchers can learn the rules that govern how flexible, disordered proteins behave, they may eventually be able to predict and influence what happens when that behavior begins to change. BIOGAMI is led by ARPA-H Program Manager Shannon Greene, Ph.D.
This research was funded, in part, by the Advanced Research Projects Agency for Health (ARPA-H). The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the U.S. Government.