The hunt for new antibiotics can be aided by computational tools that identify indispensible components of a pathogen's physiology.
Olaf Wiest at the University of Notre Dame in Indiana, Zoltán Oltvai of the University of Pittsburg in Pennsylvania and their colleagues analysed the metabolic networks of Escherichia coli and Staphylococcus aureus and identified 13 enzymes that catalyse essential reactions in both these bacteria. The researchers then ran molecular simulations to find 41 compounds with potential to inhibit these enzymes. Finally, they confirmed that some of those compounds reduced enzyme activity and killed the bacteria in vitro.
The study, the authors say, shows how genomic and metabolic information can enhance drug discovery, including the development of tailored therapies for specific bacterial strains.
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Drug discovery: Virtual antibiotic screen. Nature 463, 139 (2010). https://doi.org/10.1038/463139d