An approach to identify drug targets that select against antibiotic resistance
Type of Award: Catalyst
Award Period: September 2011 - August 2013
Amount Awarded: $ 199,972.00
PI(s): Adilson Motter, PhD, Northwestern University; Sean Crosson, PhD, UChicago;
Abstract: Diseases caused by microbial infection are the second leading cause of death worldwide (WHO World Health Report, 2004). Perhaps the greatest current challenge in the treatment of such infections is the development of new classes of antibiotics. Between 1935 and 1968, 14 classes of antibiotics were developed -- representing novel mechanisms of action. Since 1970 only 5 new classes have been introduced into the clinic, two of which are limited to topical use (Alanis 2005). In all cases, bacterial resistance to these drugs arose a few years after their introduction (Walsh 2003). There are, therefore, two major problems to consider in the development of new antibiotic drugs:
1) the identification of novel targets, and
2) the development of approaches that will limit the evolution of resistance in bacteria.
Using the tools of metabolic network modeling (Motter) and bacterial genetics (Crosson), we will identify new drug targets that are less likely to develop resistance and refine approaches to select against resistance for existing antibiotics.