Metabolic channeling, long established in plant secondary metabolism, enables cells to effectively synthesize specific products without metabolic interference, diffusion limitations, or inhibition from intermediate steps. The formation of metabolic channels employs both static and dynamic interactions to spatially organize cooperating enzymes into efficient metabolic machines. The bacterial production of R-1,2 propanediol (R-1,2-PD) is an ideal target for the intential engineering of metabolic channels since this pathway includes both a bactericidal intermediate and an undesired side reaction from competing pathways. We expect engineered R-1,2-PD metabolic channels comprised of this 3-enzyme network will greatly improve the commercial production titers necessary to replace existing non-renewable methods for R-1,2-PD production with renewable technologies. Prior to the laboratory synthesis of de novo metabolic channels, we have simulated the R-1,2-PD reaction network through 3-D spatial stochastic algorithm, modeled after the Next Subvolume Method (NSM) proposed by Elf and Ehrenberg. Implementation of the NSM in Java on a 1.66 GHz Intel Core Duo processor running Mac OSX 10.4.6 simulates approximately 12 million reaction or diffusion events per hour for a system with 64,000 subvolumes, 16 species, and 21 reaction events. Our preliminary analysis shows that the compartmentalization of the proposed metabolic channel improves the kinetic properties with a 2-fold reduction of Km for the channeled enzymes (versus the unchanneled case) while still maintaining a high rate of R-1,2-PD production.