Doctor of Philosophy
Using Brownian molecular dynamics simulations as well as Random Forest Algorithms, the internal dynamics and biomechanical response of von Willebrand Factor (vWF) multimers subject to shear flows are examined. The coarse-grained multimer description employed here is based on a monomer model in which the A2 domain of vWF is explicitly represented by a non-linear elastic spring whose mechanical response was fit to experimental force/extension data from vWF monomers. This permits examination of the dynamic behavior of hydrodynamic forces acting on A2 domains as a function of shear rate and multimer length, as well as position of an A2 domain along the multimer contour. A machine learning tool is herein developed that is useful for predicting the instantaneous dynamical state of sub-monomer features within long linear polymer chains, as well as extracting the dominant macromolecular motions associated with sub-monomer behaviors of interest. This tool is employed to better understand and predict sub-monomer A2 domain unfolding dynamics occurring amidst the dominant large-scale macromolecular motions of the biopolymer vWF immersed in flow. Lastly, Brownian dynamics simulations are employed to help explain details of experimental observations for the extensional response behaviors exhibited by wall-bound vWF subject to shearing flows within a microfluidic device.
Morabito, Michael John, "Mathematical Modeling of Flow-Induced Biological Polymer Dynamics using Coarse-Grained Brownian Dynamics Simulations" (2019). Theses and Dissertations. 5726.