earticle

영어

Microbial pathogens are constantly developing resistance to antibiotics, giving impetus for the development of efficient methods for drug targeting and discovery. Genome-scale biological network is expected to play a significant role, as it has succeeded in capturing the physiological
characteristics of various organisms. We herein employed two systematic approaches. One of them is constraints-based flux analysis, an optimizationbased simulation technique that calculates metabolic fluxes (1). Another important work is chokepoint analysis, which is network-topology-based method that selects enzymes or metabolites as a target that has a single
ingoing and/or outgoing reaction (2). We combined these methods to generate novel drug targets in several emerging drug-resistant pathogens, including Escherichia coli, Helicobacter pylori, Mycobacterium tuberculosis and Staphylococcus aureus. This study demonstrates that drug targeting using in silico approaches enables a rational design of experiments applicable to biomedical science. [This work was supported by the Korean Systems Biology Research Project (M10309020000–03B5002–00000) of the Ministry of Education, Science and Technology. Further supports by the LG Chem Chair Professorship, Microsoft, and IBM SUR program are appreciated.]