Amino Acid Metabolism and Fluxes

By the mid1960s, the pioneering work of Umbarger and Gerhart and Pardee had shown us that carbon flow through a biosynthetic pathway was controlled by allosteric inhibition of the first enzyme of the pathway by its end product; and, studies of the lac operon by Jacob and Monod had established that genes were controlled by an operator-repressor mechanism. During the intervening forty-plus years, knowledge and technologies have continued to explode in unanticipated ways. Today, we understand in great detail the molecular mechanisms of the many levels of metabolic and genetic regulation that control carbon flow through the amino acid biosynthetic pathways. Traditional experimental approaches are not sufficient for the integration and reconstruction of complex biological systems using data mostly generated by high-throughput experiments. Only with computational methods and adequate modeling tools will we be able to reconstruct and query these large and complicated systems. Due to complicated enzyme reaction mechanisms and the frequent lack of rate constant measurements needed for solving differential equations, most investigators have turned their attention to the development of abstract, top-down modeling tools. For example, Palsson and colleagues have used metabolic flux balance analysis (FBA) methods to simulate steady-state metabolite flux through E. coli pathways representing hundreds of enzyme steps. Recently, Yang et al. have developed a bottom-up, enzyme mechanism modeling language, kMech (kinetic mechanism), for the mathematical simulation of metabolic pathways.