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.
Copyright \copyright 2011 Elsevier Ltd. All rights reserved.
%0 Journal Article
%1 Chavali2012Metabolic
%A Chavali, Arvind K.
%A D'Auria, Kevin M.
%A Hewlett, Erik L.
%A Pearson, Richard D.
%A Papin, Jason A.
%D 2012
%J Trends in microbiology
%K drug-targets flux-analysis metabolic-networks
%N 3
%P 113--123
%R 10.1016/j.tim.2011.12.004
%T A metabolic network approach for the identification and prioritization of antimicrobial drug targets.
%U http://dx.doi.org/10.1016/j.tim.2011.12.004
%V 20
%X 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.
Copyright \copyright 2011 Elsevier Ltd. All rights reserved.
@article{Chavali2012Metabolic,
abstract = {
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.
Copyright {\copyright} 2011 Elsevier Ltd. All rights reserved.
},
added-at = {2018-12-02T16:09:07.000+0100},
author = {Chavali, Arvind K. and D'Auria, Kevin M. and Hewlett, Erik L. and Pearson, Richard D. and Papin, Jason A.},
biburl = {https://www.bibsonomy.org/bibtex/2f3ea31c9a96c728e62863b0a3c948c99/karthikraman},
citeulike-article-id = {10311944},
citeulike-linkout-0 = {http://dx.doi.org/10.1016/j.tim.2011.12.004},
citeulike-linkout-1 = {http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3299924/},
citeulike-linkout-2 = {http://view.ncbi.nlm.nih.gov/pubmed/22300758},
citeulike-linkout-3 = {http://www.hubmed.org/display.cgi?uids=22300758},
doi = {10.1016/j.tim.2011.12.004},
interhash = {8d33972fbfecc380d71063c3fc7b7fe4},
intrahash = {f3ea31c9a96c728e62863b0a3c948c99},
issn = {1878-4380},
journal = {Trends in microbiology},
keywords = {drug-targets flux-analysis metabolic-networks},
month = mar,
number = 3,
pages = {113--123},
pmcid = {PMC3299924},
pmid = {22300758},
posted-at = {2012-03-16 06:20:45},
priority = {2},
timestamp = {2018-12-02T16:09:07.000+0100},
title = {A metabolic network approach for the identification and prioritization of antimicrobial drug targets.},
url = {http://dx.doi.org/10.1016/j.tim.2011.12.004},
volume = 20,
year = 2012
}