Abstract
Biological pathways information has accumulated along with Genomic sequence data. These metabolic pathways help us in understanding network robustness and complex reaction networks. They also provide a framework for improved understanding of microbial physiology and for antimicrobial drug discovery. This article is an attempt to understand the local and global properties of metabolic networks in P. aeruginosa and to identify potential drug targets through ‘load point’ and ‘choke point’ analyses. In this study, we identify 25 choke point enzymes in pathways unique to P. aeruginosa and 202 choke point enzymes in the common pathways between the pathogen and the host human. We also list top 10 choke point enzymes based on the load point values and number of shortest paths and propose them as putative targets. These data underscore the utility of systems analyses methods for understanding human metabolic network in drug discovery process and in-depth understanding of the mechanism of diseases.
Keywords: P. aeruginosa, choke points, load points, Pathway Hunter Tool (PHT)
Current Bioinformatics
Title: ‘Load Points’ and ‘Choke Points’ as Nodes for Prioritizing Drug Targets in Pseudomonas aeruginosa
Volume: 4 Issue: 1
Author(s): Deepak Perumal, Chu Sing Lim, Kishore R. Sakharkar and Meena K. Sakharkar
Affiliation:
Keywords: P. aeruginosa, choke points, load points, Pathway Hunter Tool (PHT)
Abstract: Biological pathways information has accumulated along with Genomic sequence data. These metabolic pathways help us in understanding network robustness and complex reaction networks. They also provide a framework for improved understanding of microbial physiology and for antimicrobial drug discovery. This article is an attempt to understand the local and global properties of metabolic networks in P. aeruginosa and to identify potential drug targets through ‘load point’ and ‘choke point’ analyses. In this study, we identify 25 choke point enzymes in pathways unique to P. aeruginosa and 202 choke point enzymes in the common pathways between the pathogen and the host human. We also list top 10 choke point enzymes based on the load point values and number of shortest paths and propose them as putative targets. These data underscore the utility of systems analyses methods for understanding human metabolic network in drug discovery process and in-depth understanding of the mechanism of diseases.
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Cite this article as:
Perumal Deepak, Lim Sing Chu, Sakharkar R. Kishore and Sakharkar K. Meena, ‘Load Points’ and ‘Choke Points’ as Nodes for Prioritizing Drug Targets in Pseudomonas aeruginosa, Current Bioinformatics 2009; 4 (1) . https://dx.doi.org/10.2174/157489309787158189
DOI https://dx.doi.org/10.2174/157489309787158189 |
Print ISSN 1574-8936 |
Publisher Name Bentham Science Publisher |
Online ISSN 2212-392X |
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