A metabolic network approach for the identification and prioritization of antimicrobial drug targets

被引:75
作者
Chavali, Arvind K. [1 ]
D'Auria, Kevin M. [1 ]
Hewlett, Erik L. [2 ]
Pearson, Richard D. [2 ,3 ]
Papin, Jason A. [1 ]
机构
[1] Univ Virginia, Dept Biomed Engn, Charlottesville, VA 22908 USA
[2] Univ Virginia, Div Infect Dis & Int Hlth, Dept Med, Charlottesville, VA 22908 USA
[3] Univ Virginia, Dept Pathol, Charlottesville, VA 22908 USA
基金
美国国家科学基金会; 美国国家卫生研究院;
关键词
FLUX-BALANCE ANALYSIS; GENOME-SCALE RECONSTRUCTION; HAEMOPHILUS-INFLUENZAE RD; ESCHERICHIA-COLI; MYCOBACTERIUM-TUBERCULOSIS; PSEUDOMONAS-AERUGINOSA; SALMONELLA-TYPHIMURIUM; MODEL; HOST; CAPABILITIES;
D O I
10.1016/j.tim.2011.12.004
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
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.
引用
收藏
页码:113 / 123
页数:11
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