Understanding structure and dynamics of peptides using simulations and experiments

Thesis (Ph. D.)--University of Rochester. Department of Chemical Engineering, 2020.
Explaining and predicting experimental results are the goals of molecular simulations. Molecular simulations that reproduce experimental results give a molecular explanation of phenomena that are fundamentally inaccessible to experiments. Such important phenomena include fast time-dependent processes, like the binding of a ligand to an active site of an enzyme or protein misfolding. These processes are hard to measure experimentally and even if they are time-independent they may be challenging to observe experimentally. These molecular processes are nevertheless important and have wide applications from drug design to discovering novel materials with specific properties. Simulations excel at elucidating these phenomena. Simulations allow one to see the nanoscale details that lead to bulk properties and macroscopic observables. Understanding molecule mechanisms from simulations' perspective can lead to innovations by providing insight, giving guidance to design of materials that are nonfouling, antimicrobial, etc. Because the goal is understanding an experiment, utilizing the experimental results to improve the accuracy of simulations is an obvious advantage. Experiment Directed Simulations (EDS) is a method of minimally biasing a simulation such that the simulation matches experimental results. This research focuses on implementing EDS on biomolecules, such as tripeptides and amyloid peptides, to analyze the structure and dynamics of these systems.