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Bioinformatics Advance Access published online on April 26, 2007
Bioinformatics, doi:10.1093/bioinformatics/btm150
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© The Author (2007). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

A Network-Based Method for Target Selection in Metabolic Networks

R. Guimerà a,*, M. Sales-Pardo a and L. A. N. Amaral a

aNorthwestern Institute on Complex Systems (NICO) and Dept. Chemical and Biological Engineering, Northwestern University, Evanston, IL 60208, USA

*To whom correspondence should be addressed. Roger Guimera, E-mail: rguimera{at}northwestern.edu


  Abstract

Motivation: The lack of new antimicrobials, combined with increasing microbial resistance to old ones, poses a serious threat to public health. With hundreds of genomes sequenced, systems biology promises to help in solving this problem by uncovering new drug targets.

Results: Here, we propose an approach that is based on the mapping of the interactions between biochemical agents, such as proteins, and metabolites, onto complex networks. We report that nodes and links in complex biochemical networks can be grouped into a small number of classes, based on their role in connecting different functional modules. Specifically, for metabolic networks, in which nodes represent metabolites and links represent enzymes, we demonstrate that some enzyme classes are more likely to be essential, some are more likely to be species-specific, and some are likely to be both essential and specific. Our network-based enzyme classification scheme is thus a promising tool for the identification of drug targets.

Associate Editor: Dr. Jonathan Wren

Received on January 11, 2007; revised on April 5, 2007; accepted on April 13, 2007

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