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This paper serves as a framework for designing advanced models for drugaction on metabolism. Drug treatment may affect metabolism by either enhancingor inhibiting metabolic reactions comprising a metabolic network. We introducethe concept of \textit{metabolic graphs}, a generalization of hypergraphshaving specialized features common to metabolic networks.Linear-in-flux-expression (briefly LIFE) is a methodology for analyzingmetabolic networks and simulating virtual patients. We extend LIFE dynamics tobe compatible with metabolic graphs, including the more complex interactions ofenhancer and inhibitor molecules that affect biochemical reactions. We discussresults considering network structure required for existence and uniqueness ofequilibria on metabolic graphs and show simulations of drug action on\textit{Mycobacterium tuberculosis} (briefly MTB)

Metabolic graphs, LIFE method and the modeling of drug action on Mycobacterium tuberculosis