DescriptionThis thesis answers questions about how the design of proteins maintains dynamic stability. It begins with an investigation into how a globular protein, β -Lactoglobulin A, accommodates a small molecule into its hydrophobic core. These experiments examine the events of ligand binding, reporting the pico- to nanosecond motions that stabilize the ligand. The small molecule, Coumarin 153 (C153), is a dye whose fluorescence energy is modulated by the surrounding protein. Relaxation of the protein about the dye manifests as a time-dependent red shift in observed fluorescence energy. This red shift is successfully separated from the fluorescence of two other C153 dye binding sites with an analysis tool we develop. Using a model fluorescence spectrum, the total fluorescence is decomposed into its three components. binding locations are assigned based on temperature-dependent fluorescence data which reveal site specific thermodynamic changes in the protein consistent with previous reports. The high temperature denature of β -Lactoglobulin is also manifested as a change in fluctuation activation energies, which are calculated according to Arrhenius theory. The second part of the thesis establishes the ma jor driving force for the destabilization of an intrinsically disordered protein, an event which initiates its aggregation to amyloid. α-synuclein (αSyn) is the major protein component of pathological Lewy bodies found in Parkinsonian neural tissue. The majority of in vitro experiments accelerate kinetics with sample agitation in the presence of air or polytetrafluoroethylene (PTFE). Our experiments use controlled amounts of PTFE to demonstrate the accel- eration is due to the stabilization of monomeric αSyn at the hydrophobic-hydrophilic (PTFE-water) interface. This result disproves the widely held assumption that amyloid kinetics are primarily accelerated by mass transfer and/or fibril fragmentation and calls for a reevaluation of αSyn amyloid publications. It is determined that only the initial dimerization reaction is surface dependent and a fit of data to an explicit kinetic model allows information of solution phase reactions to be separated from it. A model is developed about a free energy landscape and the resulting kinetic parameters are translated into ∆G and ∆G‡ values for prenuclation, nucleation, and fibrillization reactions.