Date of Award

May 2024

Degree Type

Dissertation

Degree Name

Doctor of Philosophy

Department

Physics

First Advisor

Ionel Popa

Abstract

Proteins play a fundamental role in virtually every aspect of our daily lives, from essential bodily functions such as oxygen transport and muscle movement to our sensory perceptions. Beyond their biological functions, proteins are also integral to the development of biocompatible materials. These materials are crafted by leveraging chemical reactions to link specific amino acids, forming intricate protein lattice networks. Despite advancements in understanding the strength of individual protein building blocks through single molecule measurements, predicting the mechanical properties of these biomaterials remains challenging due to the inherent randomness in molecular orientation within the network. To address this complexity, it is crucial to grasp how nanoscale mechanics influence macroscopic characteristics, enabling the design of predictable and adjustable biomaterials. My research endeavors to bridge the vast scale disparity of six orders of magnitude, employing a diverse array of experimental and computational methods. Specifically, I utilized Single Molecule Magnetic Tweezers to gauge the mechanical properties of protein L along the N-C pulling trajectory. Complementing this approach, Steered Molecular Dynamics Simulations (SMDS) were employed to simulate off-axis pulling geometries inaccessible experimentally. The SMDS outcomes provided insights into the relative stability of different pulling geometries and facilitated the creation of free energy landscapes, modeling protein unfolding via coarse-grained Brownian dynamics simulations. Furthermore, I developed a network formation model to simulate biomaterials composed of folded protein domains using Brownian dynamics simulations. By analyzing these simulated networks, I calculated the average force experienced by each domain when subjected to external stress, simulating real-world scenarios. These simulated networks were then subjected to applied stress using a global force vector, allowing the network to adapt and protein domains to unfold. After a simulated duration, the resulting extensions of the biomaterials were compared to experimental data, confirming the model's ability to predict realistic behavior. This multidisciplinary approach offers valuable insights into the mechanics of biomaterials, facilitating the design of more effective and predictable materials for various applications.

Available for download on Friday, May 22, 2026

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