Monday, November 5, 2007 - 2:20 PM

Target Site Search Strategy Of Gene Regulatory Proteins

Andrew Spakowitz and Mario Diaz de la Rosa. Chemical Engineering, Stanford University, Stauffer III - Room 113, 381 North South Mall, Stanford, CA 94305

Gene expression is orchestrated by a host of regulatory proteins that coordinate the transcription of DNA to RNA. The regulatory proteins function by locating specific binding sequences of DNA and binding to these sequences to form the transcription initiation complex. In many instances, these regulatory proteins only have several hundred copies that must efficiently locate target sequences on the genome-length DNA strand in order to dynamically control protein levels in the cell. Our goal in this research is to use a combination of analytical theory and computational modeling to gain a fundamental understanding of the physical processes that underlie the stochastic search of a regulatory protein for its target site.

The non-specific binding of regulatory proteins to random sequences of DNA is believed to permit the protein to slide along the DNA in a stochastic manner. Periodically, a thermal kick or an interaction with another bound protein will disengage the regulatory protein from the DNA surface, leading to three-dimensional diffusion. Eventually, the protein will reattach to the DNA at some new location that is dictated by both the diffusivity of the protein and the DNA configuration. Cycling through these random events constitutes a search strategy for the target site. We build a reaction-diffusion theory of this search process in order to predict the optimal strategy for target site localization. The statistical behavior of the DNA strand acts as a necessary input into the theory, and we consider several governing behaviors for the DNA strand. We first model DNA using the wormlike chain model, which is most relevant for a free DNA strand in a cell free experiment. We then proceed to address how supercoiling in plasmid DNA impacts the search strategy using Brownian dynamics simulation of the twisted polymer ring. We explore the impact of DNA configuration on target site localization in order to predict how protein expression will vary under different experimental conditions.