The regulation of gene expression is a complex process fundamental to how a cell develops and interacts with its environment. One class of proteins involved in the regulation of genes are transcription factors (TFs), which recognize and bind to short sequences of DNA (TF binding sites - TFBS). Well-established bioinformatics methods predict the location of these target sequences using motif models. These models exhibit poor specificity (i.e. high false positive rates) and the predictions correlate poorly with laboratory chromatin immunoprecipitation (ChIP) data. We projected that the incorporation of biophysical aspects such as (but not limited to): 1) a model for how TFs search through nuclear and genomic space for a specific binding site, 2) non-specific interactions with other proteins, and 3) a binding energy probabilistic model for DNA interaction events, would improve predictions. A prototype simulator has been developed, and the scores from the simulator will be used to generate predictions of gene regulatory regions, which will then be compared to protein-DNA interaction data from published ChIP experiments.