  This paper serves as a framework for designing advanced models for drug
action on metabolism. Drug treatment may affect metabolism by either enhancing
or inhibiting metabolic reactions comprising a metabolic network. We introduce
the concept of \textit{metabolic graphs}, a generalization of hypergraphs
having specialized features common to metabolic networks.
Linear-in-flux-expression (briefly LIFE) is a methodology for analyzing
metabolic networks and simulating virtual patients. We extend LIFE dynamics to
be compatible with metabolic graphs, including the more complex interactions of
enhancer and inhibitor molecules that affect biochemical reactions. We discuss
results considering network structure required for existence and uniqueness of
equilibria on metabolic graphs and show simulations of drug action on
\textit{Mycobacterium tuberculosis} (briefly MTB)
