Proteins and nucleic acids can physically partition without the help of membranes. These assemblies behave like liquid droplets and provide a dynamic environment for biomolecular reactions requiring specific protein concentrations. Some of these proteins are also known to aggregate and cause neurodegenerative diseases. This raises the key question how the functional liquid droplets transform into the pathological solid aggregates. In this research, advanced computational methods will be used to view how the structures of these proteins differ in the liquid droplets and aggregates. The knowledge learned from this project will be essential in designing novel strategies that can disrupt pathological aggregates but do not disrupt functional droplets. The concepts of computational modeling will be introduced into both the undergraduate research and high school biophysics apprenticeship programs at Arizona State University (ASU), a university with a significant underrepresented student population in a location that is home to a large number of individuals from underrepresented groups in STEM. The PI will pay specific attention to promoting a variety of dissemination approaches through the ASU expert database to introduce the concepts of biophysics and to facilitate the dissemination of materials to a broad audience.
Intrinsically disordered proteins, proteins that lack a well-defined folded structure, have been shown to participate in both liquid-liquid phase separation (LLPS) and aggregation. The former is reversible, providing important intracellular functions, whereas the latter is often irreversible and disease-related. There has been increasing interest in showing how droplet formation could induce aggregation, but little is known regarding the structure properties capable of distinguishing these two assembly states. One major challenge is the lack of high-resolution modeling methods for integrating observations from multiple experimental techniques. In this work, the PIs will develop a novel computational modeling framework to integrate multiple technologies. Specifically, all-atom explicit-solvent simulations will be used to investigate the structure properties of disordered proteins in both dispersed and condensed phases and how these properties are influenced by their interaction partners. Coarse-grained models will further be used to investigate both the formation of liquid droplets and aggregates. The impact of droplet formation on its aggregation preference will be quantitatively assessed. The project will leverage computational tools to establish fundamental physics principles that govern the structural (dis)similarities between LLPS and aggregation.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
