Stochastic Modeling and Simulations of Biological Transport
Das, Rahul Kumar
Kolomeisky, Anatoly B.
Doctor of Philosophy thesis
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.
Motor proteins; Stochastic modeling; DNA binding proteins; Monte Carlo simulations