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Virginia Tech

Understanding molecular and cellular processes using statistical physics

Abstract

dc:description.abstract

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.

Degree

thesis:*
Name thesis:degree_name
Ph. D.
Level thesis:degree_level
doctoral
Discipline thesis:degree_discipline
Genetics, Bioinformatics, and Computational Biology
Department dc:contributor.department
Genetics, Bioinformatics, and Computational Biology
Grantor dc:publisher
Virginia Tech
Year dc:date.issued
2011

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Wu, Zhanghan
Chair dc:contributor.committeechair
  • Xing, Jianhua
Committee members dc:contributor.committeemember
  • Cao, Yang
  • Cimini, Daniela
  • Walker, Richard A.

Subjects

dc:subject × 4

Rights

dc:rights
Statement dc:rights
  • In Copyright

Identifiers

dc:identifier.*
Dc Identifier Other
etd-05162011-105041
OAI identifier oai:identifier
oai:vtechworks.lib.vt.edu:10919/27745

Chain of custody

source
Harvested from
Virginia Tech
Base URL
vtechworks.lib.vt.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Wu, Zhanghan. Understanding molecular and cellular processes using statistical physics. doctoral thesis, Virginia Tech, 2011. http://hdl.handle.net/10919/27745