Anticancer drug discovery through genome-scale metabolic modeling
Altered metabolism has long been recognized as a defining property of cancer physiology, but is experiencing renewed interest as the importance of such alterations are becoming fully realized. Once regarded merely as a side effect of a damaging mutation or a general increase in proliferation rate, metabolic network rewiring is now viewed as an intentional process to optimize tumor growth and maintenance, and can even drive cancer transformation. This has motivated the search for anticancer targets among enzymes in the metabolic network of cancer cells. Genome-scale metabolic models (GEMs) provide the necessary framework to systematically interrogate this network, and many recent studies have successfully employed GEMs to predict anticancer drug targets in the metabolic networks of various cancer types.
Genome-scale metabolic model
Integrative omics analysis
Flux balance analysis