The use of networks to aid the drug discovery process is a rather new but booming endeavor. A vast variety of different types of networks are being constructed and analyzed for various different tasks in drug discovery. The analysis may be at the level of establishing connectivity, topology, and graphs, or may go to a more quantitative level. We discuss here how computational systems biology approaches can aid the quantitative analysis of biochemical networks for drug-target prediction. We focus on networks and pathways in which the components are related by physical interactions or biochemical processes. We particularly discuss the potential of mathematical modeling to aid the analysis of proteins for druggability.
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