Literature DB >> 22125297

Metabolic network modeling and simulation for drug targeting and discovery.

Hyun Uk Kim1, Seung Bum Sohn, Sang Yup Lee.   

Abstract

Systems biology has greatly contributed toward the analysis and understanding of biological systems under various genotypic and environmental conditions on a much larger scale than ever before. One of the applications of systems biology can be seen in unraveling and understanding complicated human diseases where the primary causes for a disease are often not clear. The in silico genome-scale metabolic network models can be employed for the analysis of diseases and for the discovery of novel drug targets suitable for treating the disease. Also, new antimicrobial targets can be discovered by analyzing, at the systems level, the genome-scale metabolic network of pathogenic microorganisms. Such applications are possible as these genome-scale metabolic network models contain extensive stoichiometric relationships among the metabolites constituting the organism's metabolism and information on the associated biophysical constraints. In this review, we highlight applications of genome-scale metabolic network modeling and simulations in predicting drug targets and designing potential strategies in combating pathogenic infection. Also, the use of metabolic network models in the systematic analysis of several human diseases is examined. Other computational and experimental approaches are discussed to complement the use of metabolic network models in the analysis of biological systems and to facilitate the drug discovery pipeline.
Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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Year:  2011        PMID: 22125297     DOI: 10.1002/biot.201100159

Source DB:  PubMed          Journal:  Biotechnol J        ISSN: 1860-6768            Impact factor:   4.677


  22 in total

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Review 4.  In silico methods for drug repurposing and pharmacology.

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5.  Framework and resource for more than 11,000 gene-transcript-protein-reaction associations in human metabolism.

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7.  RELATCH: relative optimality in metabolic networks explains robust metabolic and regulatory responses to perturbations.

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9.  A conceptual review on systems biology in health and diseases: from biological networks to modern therapeutics.

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10.  Predicting new molecular targets for rhein using network pharmacology.

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Journal:  BMC Syst Biol       Date:  2012-03-21
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