CAREER: Bridging time and length scales of intrinsically disordered protein conformations and assemblies using advanced computational methods

About This Grant

This research seeks to understand how proteins interact and self-assemble, bridging scales from the random motion of individual molecules to the formation of large multi-protein assemblies. The project will focus on intrinsically disordered proteins (IDPs), a class of biological molecules that lack a single, fixed three-dimensional structure. Instead, these molecules can interconvert between distinct, transient forms that play important roles in cellular processes such as molecular recognition, signaling, and regulation. The dynamic and flexible nature of IDPs makes them prone to aggregation into ordered amyloid fibrils or to liquid-liquid phase separation into protein-rich droplets important for normal cellular function. Understanding the biophysical principles that lead to these distinct molecular assemblies will provide insights into cellular processes, the progression of neurodegenerative diseases, and the design of bio-inspired materials with unique properties. Beyond these scientific outcomes, this project will enhance undergraduate education by integrating computational methods into the biochemistry curriculum. Students will gain hands-on experience in advanced computational techniques such as molecular dynamics simulations, machine learning, and mathematical modeling. The project includes the development of an online biophysical chemistry textbook integrated with real-world examples, programming-focused curriculum modules, and a computational workshop to train undergraduate research students. Students engaged in this project will gain competitive skills for future careers in science, technology, and medicine. The project will investigate the biophysical principles that connect and lead to distinct aggregation and assembly pathways and will uncover specific factors like protein sequence, solution conditions, and chemical modifications that influence the rich behavior of IDPs. The goals are to characterize the complete conformational landscape of IDPs during fibrilization, to elucidate the factors leading to phase separation of IDPs across multiple length scales, to characterize the formation of correlated segments in proteins that possess a sizeable intrinsically disordered region (IDR), and to develop a model for controlling liquid-liquid phase separation through post-translational modifications. Molecular dynamics simulations, enhanced sampling methods, and machine learning will be integrated with experimental distance distributions to map the complex conformational landscapes of IDPs and model their transition to pathological aggregates or functional assemblies. Coarse-grained and polymer physics models will be developed to study how posttranslational modifications like phosphorylation modulate the phase behavior of low-complexity IDPs. The project seeks to provide a multiscale framework for understanding IDP assembly and to establish principles for predicting biologically relevant conditions for phase separation, aggregation, and segmental dynamics that govern cellular processes. This project is funded by the Molecular Biophysics Cluster in the Division of Molecular and Cellular Biosciences. 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.