Investigating the organization and mechanics of cell structure using Monte Carlo methods

Understanding cellular structure and the associated mechanics at a molecular level is critical in numerous diseases including cancer and heart disease. Central to this is the organization of the internal cell structure (the cytoskeleton), which responds to mechanical forces as an actively adapting smart material. Understanding overall cell behavior from knowledge of low-level molecular components and their interactions is critical to being able to accurately dissect complex cellular behavior. This goal cannot be achieved without better capturing the distinctive pattern of spatial constraints on biochemistry in the cellular environment, factors largely lacking in prevailing modeling approaches and the in vitro experiments generally used to parameterize them. Such constraints are likely to be particularly relevant to quantitative modeling of molecular assembly systems, which are implicated in a broad range of critical cell functions.; The unique merit of this research lies primarily in its integration of information across disciplinary boundaries. It brings together the biology of molecular assembly systems and the development of simulation tools to explore these systems. The work presented here establishes a computational methodology and associated computer models that are better suited to characterizing molecular behavior in the cellular environment.; Specifically, it develops a computational model of molecular assembly systems in space and dimension-constrained environments using lattice based Monte Carlo methods. The model is tested on the well-characterized system of in vitro actin assembly system. The model matches classic methods in domains where classic methods should be valid and diverges in domains where classic models are not applicable.; Lastly, an off lattice Monte Carlo model is proposed to investigate the relationship between mechanics and the organization of these molecular assembly systems; the long term intent being to develop and validate a computational infrastructure suitable for understanding and testing how structure and mechanics affect cellular biochemistry.