Drug Target Identification Based on Flux Balance Analysis of Metabolic Networks

Abstract Efficiently identifying drug targets with minimal side effects is a major challenge in new drug development. In this paper, we develop a method based on flux balance analysis (FBA) to identify drug targets in metabolic networks. The method, which is formulated into two linear programming models, first finds the steady flux of reactions and mass flow of metabolites in the pathologic state and determines the optimal flux and mass flow in the medication state such that the side effect caused by medication is minimized. Then drug targets can be identified by comparing the flux of reactions in both states and checking the reactions whose fluxes are changed. We give an illustrative example to show that the drug target identification problem can be solved effectively by our method.