Multiscale analysis and visualization of biophysical structure and biochemical function with computational microscopy
- Author(s): Hirakis, Sophia P
- Advisor(s): Amaro, Rommie E
- McCammon, J Andrew
- et al.
The evasive source and cause of a disease is oftentimes smaller than you think. Imagine, though, chasing something that you can't actually see. Fortunately for the modern-day biomedical scientist, computational tools harnessing the power of physics using the language of mathematics are able to see the invisible. Computational microscopy is a tool developed to visualize the energetic behavior of biological systems. With progressive advancements in computer graphics and the development of mathematical theories to explain biological behavior, computational microscopy has become a useful tool used by many kinds scientists over the greater half of the last century to understand the energetic underpinnings of a system's behavior. Unlike most "microscopes," it allows us to visualize extremely small entities like atoms, molecules, proteins, and cells. More importantly, it allows us to spatiotemporally transcend scales to understand the dynamics of our systems. Like a biophysically detailed time-lapse, we are able to see through time, to understand chemical "butterfly effects" that transcend the time and space scale at which they operate. In this thesis, the computational microscope is applied to multiple systems to visualize and analyze the physicochemical mechanisms that underlie biological function. Specifically, the thesis is centered on the structure of proteins and subcellular mechanisms driving cardiac function and dysfunction. In the first chapter, we address the concept of multiscale biological simulations, integrating information from atomistic scales toward cellular models of Protein Kinase A. The second chapter demonstrates the ways that atomistic simulations can be applied to the study of the structural interactions in protein-protein complexes vital to the infectious mechanisms of Group-A Streptococcus. In the third chapter, two scales of biological simulation are used in tandem to understand the structure and the kinetic behavior of Protein Kinase A RIalpha. The final chapter incorporates the kinetic understanding of relevant species in a realistic subcellular geometry to investigate signaling mechanisms that underlie calcium activation in healthy and diseased hearts. Particular attention is paid to the way that structural alterations on the atomistic, molecular, and membranous level alter the behavior of biological systems. Holistically, this thesis is centered on the use of computational tools and the development of realistic models that can reproduce experimental findings and predict the behavior of systems, driving the creation of new hypotheses.