Path-integral and Coarse-graining Strategies for Complex Molecular Phenomena

Molecular simulation provides a powerful tool for connecting molecular-level processes to physical observables. However, the facility to make those connections relies upon the application and development of theoretical methods that permit appropriate descriptions of the systems or processes to be studied. In this thesis, we utilize molecular simulation to study and predict two phenomena with very different theoretical challenges, beginning with (1) lithium-ion transport behavior in polymers and following with (2) equilibrium isotope effects with relevance to position-specific and clumped isotope studies. In the case of ion transport in polymers, there is motivation to use molecular simulation to provide guidance in polymer electrolyte design, but the length and timescales relevant for ion diffusion in polymers preclude the use of direct molecular dynamics simulation to compute ion diffusivities in more than a handful of candidate systems. In the case of equilibrium isotope effects, the thermodynamic driving forces for isotopic fractionation are often fundamentally quantum mechanical in nature, and the high precision of experimental instruments demands correspondingly accurate theoretical approaches. Herein, we describe respectively coarse-graining and path-integral strategies to address outstanding questions in these two subject areas.

Design and analysis of nucleic acid reaction pathways

Nucleic acids are a useful substrate for engineering at the molecular level. Designing the detailed energetics and kinetics of interactions between nucleic acid strands remains a challenge. Building on previous algorithms to characterize the ensemble of dilute solutions of nucleic acids, we present a design algorithm that allows optimization of structural features and binding energetics of a test tube of interacting nucleic acid strands. We extend this formulation to handle multiple thermodynamic states and combinatorial constraints to allow optimization of pathways of interacting nucleic acids. In both design strategies, low-cost estimates to thermodynamic properties are calculated using hierarchical ensemble decomposition and test tube ensemble focusing. These algorithms are tested on randomized test sets and on example pathways drawn from the molecular programming literature. To analyze the kinetic properties of designed sequences, we describe algorithms to identify dominant species and kinetic rates using coarse-graining at the scale of a small box containing several strands or a large box containing a dilute solution of strands.