Event

PhD Dissertation - Suhas Gotla

Monday, March 31, 2025
1:00 p.m.
AJC3104
Rachel Chang
301 405 8268
rachel53@umd.edu

Title: Polysaccharides in Amyloid Aggregation and Hydrogel Mechanics: Insights from Molecular Modeling

Committee members:

Dr. Silvina Matysiak, Chair

Dr. Christopher Jewell

Dr. Gregg Duncan

Dr. Sara Molinari

Dr. Jefferey Klauda, Dean's Representative

Abstract:

Polysaccharides are linear polymeric carbohydrates with wide-ranging functions in biological contexts and constantly emerging applications at the intersection of biomedical and materials sciences. They often participate in soft matter systems—multi-component systems with a propensity for self-assembly—ranging from simple household agar gels to complex biofluids like mucus. In this thesis, we examined overlapping yet independent cases of polysaccharide-related self-assembly with relevance to materials design for engineering applications and disease-related amyloid aggregation. A common theme among them is the inherent dynamics and polymorphism of self-assembled structures, which pose challenges to complete characterizations with experimental techniques. We addressed the knowledge gaps in the experimental literature with molecular dynamics (MD), a method of physics-based simulations of molecular motions. The conventional MD approach, also known as ``atomistic" MD, where each atom of a molecule is explicitly modeled, is accurate but inefficient at sampling the timescales necessary for large dynamical changes like self-assembly. To overcome this limitation, we opted for a simplified MD scheme known as ``coarse-graining", where degrees of freedom of atomistic molecules are reduced by approximating their chemical properties. With this approach to molecular modeling, four case studies of polysaccharide-based soft matter systems were performed, and mechanistic insights were reported.

The first case study considered a pH-responsive hydrogel system composed of the polysaccharide chitosan, and an anionic surfactant. Experiments showed that the hydrogels had contrasting mechanical properties at the two pH extremes. Our simulations, which spanned atomistic, coarse-grained, and non-equilibrium MD, provided insight into the structural origins of these pH-dependent mechanical properties. Next, we showed that chitosan hydrogels inhibited the toxic aggregation of Alzheimer's disease-related amyloid-β by sequestering monomeric peptides throughout the hydrogel network. The inhibitory effect was minimal in dilute chitosan conditions where hydrogels did not form. The last two case studies focused on the influence of glycosaminoglycans, a class of polysaccharide that make up parts of the extracellular matrix (ECM), on amyloid aggregation. One was aimed at understanding how glycosaminoglycans enhanced amyloid aggregation far from the cell surface, the other at the role of glycosaminoglycans near the cell surface. In this way, we investigated two distinct microenvironments within the ECM, the biological milieu of many toxic amyloids. Concurrently, we investigated the aggregation of two different peptides, developed coarse-grained force fields for two different glycosaminoglycans, and collectively contributed to a transferable toolkit of force fields for the modeling of sub-cellular environments. We developed thermodynamic and kinetic mechanisms for the ability of glycosaminoglycans to enhance amyloid aggregation in both contexts. Highlights include demonstrations of how the bending of glycsoaminglycans mediated peptide aggregation. In addition to contributing basic scientific knowledge, these insights may inspire strategies for amyloid inhibition, rational hydrogel design, or other applications.