Title page for ETD etd-05162011-105041

Type of Document Dissertation
Author Wu, Zhanghan
Author's Email Address zwu07@vt.edu
URN etd-05162011-105041
Title Understanding molecular and cellular processes using statistical physics
Degree PhD
Department Genetics, Bioinformatics, and Computational Biology
Advisory Committee
Advisor Name Title
Xing, Jianhua Committee Chair
Cao, Yang Committee Member
Cimini, Daniela Committee Member
Walker, Richard A. Committee Member
  • Microtubule Dynamics
  • Mathematical Modeling
  • Enzyme Conformational Changes
  • Single Molecular Fluctuations
Date of Defense 2011-05-04
Availability unrestricted
Using statistical physics principles to solve problems in biology is one of the most promising directions due to the complexity and non-equilibrium fluctuations in biological systems. In this work, we try to describe the dynamics at both cellular and molecular levels. Microtubule dynamics and dynamic disorder of enzyme proteins are two of the examples we investigated. The dynamics of microtubules and the mechanical properties of these polymers are essential for many key cellular processes. However, critical discrepancies between experimental observations and existing models need to be resolved before further progress towards a complete model can be made. We carried out computational studies to compare the mechanical properties of two alternative models, one corresponding to the existing, conventional model, and the other considering an additional type of tubulin lateral interaction described in a cryo-EM structure of a proposed trapped intermediate in the microtubule assembly process. Our work indicates that a class of sheet structures is transiently trapped as an intermediate during the assembly process in physiological conditions. In the second part of the work, we analyzed enzyme slow conformational changes in the context of regulatory networks. A single enzymatic reaction with slow conformational changes can serve as a basic functional motif with properties normally discussed with larger networks in the field of systems biology. The work on slow enzyme dynamics fills the missing gap between studies on intramolecular and network dynamics. We also showed that enzyme fluctuations could be amplified into fluctuations in phosphorylation networks. This can be used as a novel biochemical “reporter” for measuring single enzyme conformational fluctuation rates.
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