Moving Toward Genome-Scale Kinetic Models: The Mass Action Stoichiometric Simulation Approach

Abstract

Kinetic models are used to describe cellular metabolism. Traditional models are based on enzymatic information obtained from in vitro experiments. In vitro data is inaccurate for in vivo modeling and is difficult to scale to large metabolic networks. Due to the impeding availability of metabolomic and fluxomic data types, we present an alternative kinetic modeling approach. Mass action stoichiometric simulation (MASS) models are scalable kinetic models that detail in vivo metabolic transformations. MASS formulation is a “middle-out” approach involving the use of a genome-scale metabolic network as a scaffold to map fluxomic and metabolomic measurements. Multiple binding states of enzymes can be explicitly added to account for regulatory effects. There are practical challenges with data completeness and quality of MASS models, but they do represent scalable kinetic models that exhibit biological properties such as time scale decomposition and account for regulation.