A metabolic network approach for the identification and prioritization of antimicrobial drug targets.
For many infectious diseases, novel treatment options are needed in order to address problems with cost, toxicity and resistance to current drugs. Systems biology tools can be used to gain valuable insight into pathogenic processes and aid in expediting drug discovery. In the past decade, constraint-based modeling of genome-scale metabolic networks has become widely used. Focusing on pathogen metabolic networks, we review in silico strategies used to identify effective drug targets and highlight recent successes as well as limitations associated with such computational analyses. We further discuss how accounting for the host environment and even targeting the host may offer new therapeutic options. These systems-level approaches are beginning to provide novel avenues for drug targeting against infectious agents.
Department of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908, USA.
Arvind K
AK
Chavali
Kevin M
KM
D'Auria
Erik L
EL
Hewlett
Richard D
RD
Pearson
Jason A
JA
Papin
D000818:Animals; D000900:Anti-Bacterial Agents / Q000737:chemistry / Q000494:pharmacology*; D001419:Bacteria / Q000187:drug effects / Q000235:genetics / Q000378:metabolism*; D001424:Bacterial Infections / Q000188:drug therapy / Q000235:genetics / Q000378:metabolism* / Q000382:microbiology; D055808:Drug Discovery / Q000379:methods*; D006801:Humans; D053858:Metabolic Networks and Pathways; D049490:Systems Biology / Q000379:methods*
D000900:Anti-Bacterial Agents