Consists of two linear programming models: one is to find the
Consists of two linear programming models: one is to find the optimal fluxes of reactions and the mass flows of metabolites in the pathologic state, and the other is to determine the fluxes and mass flows in the medication state with the minimal side effect caused by the medication. Then drug AZD4547MedChemExpress AZD4547 targets are identified by comparing the fluxes of reactions in both states and checking the reactions whose fluxes are changed. An illustrative example is given to show that the drug target identification problem can be solved effectively by our method. We also apply our method to a hyperuricemiarelated purine metabolic pathway. Known drug targets for hyperuricemia are correctly identified by our twostage FBA method, and the side effects of these targets are also taken into account. A number of other promising drug targets are found to be both effective and safe.complex cellular processes. Metabolic networks connect biochemical reactions via substrate and product substances called metabolites. In a metabolic network, enzymes catalyze reactions which take substrates and produce metabolites. Such processes constitute the whole metabolism system of a living organism. However, the malfunctions of some enzymes may lead to production of excessive concentration or mass flow of certain compounds in a sophisticated metabolic system, and thereby may result in diseases [28]. Such compounds are generally considered as disease-causing compounds because they are directly relevant to the diseases. The remaining compounds in the metabolic system are all considered as non-disease-causing compounds. On the other hand, those enzymes are considered as drug targets, if manipulating them by drugs the concentration or mass flow of disease-causing compounds can be adjusted to a healthy range. Hence, the drug target identification problem is to identify such an enzyme set that can be manipulated by drugs to adjust the mass flow of all disease-causing compounds to a healthy range, and meanwhile reduce the gap between the mass flow of non-disease-causing compounds after PubMed ID:http://www.ncbi.nlm.nih.gov/pubmed/25432023 medication and their healthy range as much as possible. The sum of gaps between the mass flow of all non-disease-causing compounds and their healthy state range is defined as the side effects (of the drug targets).Metabolic network representationMethods Metabolism, which comprises the complete set of biochemical reactions in a living cell, is one of the mostA metabolic network is generally a biochemical network, in which chemical compounds and metabolites are represented by nodes and reactions catalyzed by one or several certain enzymes are denoted by directed edges. In order to make drug target identification easily understood, we use another graphical representation of metabolic networks [29], in which a metabolic network is built up of substrates that are connected to one another not through single links, but through physical entities denoting reactions (enzymes). A metabolic network in this type of representation is a directed bipartite graph and has two types of nodes. One type represents chemical reactions and the other metabolites. A directed edge from a reaction to a metabolite means that the metabolite is a product of the reaction. A directed edge from a metabolite to a reaction represents that the metabolite is a reactant of the reaction. A reversible reaction is considered as two separate reactions corresponding to forward and backward reactions. This representation allows us conveniently to expres.
