Metabolically re-modeling the drug pipeline

•The goal of computational systems biology is to develop predictive models of cells.•Genome-scale metabolic models (GSMMs) can infer whole cell metabolic states.•GSMMs can help identify drugs that either kill or alter metabolism of target cells.•GSMMs can predict drug toxicity and selectivity in both pathogens and human cells.

Costs for drug development have soared, exposing a clear need for new R&D strategies. Systems biology has meanwhile emerged as an attractive vehicle for integrating omics data and other post-genomic technologies into the drug pipeline. One of the emerging areas of computational systems biology is constraint-based modeling (CBM), which uses genome-scale metabolic models (GSMMs) as platforms for integrating and interpreting diverse omics datasets. Here we review current uses of GSMMs in drug discovery, focusing on prediction of novel drug targets and promising lead compounds. We then expand our discussion to prediction of toxicity and selectivity of potential drug targets. We discuss successes as well as limitations of GSMMs in these areas. Finally, we suggest new ways in which GSMMs may contribute to drug discovery, offering our vision of how GSMMs may re-model the drug pipeline in years to come.