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Stochastic Modeling and Simulations of Biological Transport

Biological transport is an essential phenomenon for the living systems. A mechanistic investigation of biological transport processes is highly important for the
characterization of physiological and cellular events, the design and functioning of
several biomedical devices and the development of new therapies. To investigate the
physical-chemical details of this phenomenon, concerted efforts of both experiments
and theory are necessary.
Motor proteins constitute a major portion of the active transport in the living cell.
However, the actual mechanism of how chemical energy is converted into their directed
motion has still remained obscure. Recent experiments on motor proteins have been
producing exciting results that have motivated theoretical studies. In order to provide
deep insight onto motor protein's mechanochemical coupling we have used stochastic
modeling based on discrete-state chemical kinetic model. Such models enable us
to (1) resolve the contradiction between experimental observations on heterodimeric
kinesins and highly popular hand-over-hand mechanism, (2) take into account the free energy landscape modification of individual motor domains due to interdomain
interaction, (3) recognize the effect of spatial fluctuations on biochemical properties
of molecular motors, and (4) calculate the dynamical properties such as velocities,
dispersions of complex biochemical pathways. We have also initiated the investigation
of the dynamics of coupled motor assemblies using stochastic modeling.
Furthermore, an extensive Monte Carlo lattice simulation based study on facilitated search process of DNA-binding proteins is presented. This simulation shows
that the accelerated search compared to pure Smoluchowski limit can be achieved
even in the case where the one-dimensional diffusion is order of magnitude slower
than the three-dimensional diffusion. We also show that facilitated search is not only
the manifestation of dimensionality reduction but correlation times play a crucial role
in the overall search times.
Finally, a more general field of stochastic processes, namely first-passage time
process is investigated. Explicit expressions of important properties, such as splitting
probailities and mean first-passage times, that are relevant to (but not limited to)
biological transport, are derived for several complex systems.

Identiferoai:union.ndltd.org:RICE/oai:scholarship.rice.edu:1911/27479
Date January 2010
CreatorsDas, Rahul Kumar
ContributorsKolomeisky, Anatoly B.
Source SetsRice University
LanguageEnglish
Detected LanguageEnglish
TypeThesis, Text
Format170 p., application/pdf

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