Kim2010_VvuMBEL943_GSMR

  public model
Short description

This is a model of the genome scale reconstruction of the Vibrio vulnificus metabolic network, VvuMBEL943, described in the article:
Integrative genome-scale metabolic analysis of Vibrio vulnificus for drug targeting and discovery
Hyun Uk Kim, Soo Young Kim, Haeyoung Jeong, Tae Yong Kim, Jae Jong Kim, Hyon E Choy, Kyu Yang Yi, Joon Haeng Rhee, and Sang Yup Lee. Molecular Systems Biology 7:460 Jan 2011 doi: 10.1038/msb.2010.115

Abstract:
Although the genomes of many microbial pathogens have been studied to help identify effective drug targets and novel drugs, such efforts have not yet reached full fruition. In this study, we report a systems biological approach that efficiently utilizes genomic information for drug targeting and discovery, and apply this approach to the opportunistic pathogen Vibrio vulnificus CMCP6. First, we partially re-sequenced and fully re-annotated the V. vulnificus CMCP6 genome, and accordingly reconstructed its genome-scale metabolic network, VvuMBEL943. The validated network model was employed to systematically predict drug targets using the concept of metabolite essentiality, along with additional filtering criteria. Target genes encoding enzymes that interact with the five essential metabolites finally selected were experimentally validated. These five essential metabolites are critical to the survival of the cell, and hence were used to guide the cost-effective selection of chemical analogs, which were then screened for antimicrobial activity in a whole-cell assay. This approach is expected to help fill the existing gap between genomics and drug discovery.

This metabolic network model has been thoroughly validated by the authors. VvuMBEL943 is a stoichiometric model that contains the metabolic information of the microbial pathogen, Vibrio vulnificus CMCP6, at genome-scale. The SBML version was generated by Hyun Uk Kim using MetaFluxNet.

This model originates from BioModels Database: A Database of Annotated Published Models (http://www.ebi.ac.uk/biomodels/). It is copyright (c) 2005-2011 The BioModels.net Team.
To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

In summary, you are entitled to use this encoded model in absolutely any manner you deem suitable, verbatim, or with modification, alone or embedded it in a larger context, redistribute it, commercially or not, in a restricted way or not..

To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.

Format
SBML (L2V4)
Related Publication
  • Integrative genome-scale metabolic analysis of Vibrio vulnificus for drug targeting and discovery.
  • Kim HU, Kim SY, Jeong H, Kim TY, Kim JJ, Choy HE, Yi KY, Rhee JH, Lee SY
  • Molecular Systems Biology , 1/ 2011 , Volume 7 , pages: 460
  • Metabolic and Biomolecular Engineering National Research Laboratory, Department of Chemical and Biomolecular Engineering (BK21 program), Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea.
  • Although the genomes of many microbial pathogens have been studied to help identify effective drug targets and novel drugs, such efforts have not yet reached full fruition. In this study, we report a systems biological approach that efficiently utilizes genomic information for drug targeting and discovery, and apply this approach to the opportunistic pathogen Vibrio vulnificus CMCP6. First, we partially re-sequenced and fully re-annotated the V. vulnificus CMCP6 genome, and accordingly reconstructed its genome-scale metabolic network, VvuMBEL943. The validated network model was employed to systematically predict drug targets using the concept of metabolite essentiality, along with additional filtering criteria. Target genes encoding enzymes that interact with the five essential metabolites finally selected were experimentally validated. These five essential metabolites are critical to the survival of the cell, and hence were used to guide the cost-effective selection of chemical analogs, which were then screened for antimicrobial activity in a whole-cell assay. This approach is expected to help fill the existing gap between genomics and drug discovery.
Contributors
Hyun Uk Kim

Metadata information

is
BioModels Database MODEL1011300000
isDescribedBy
PubMed 21245845
isVersionOf
hasProperty
Mathematical Modelling Ontology Ordinary differential equation model
Curation status
Non-curated
Original model(s)
This submission version is the original model.
  • Model originally submitted by : Hyun Uk Kim
  • Submitted: 30-Nov-2010 15:46:29
  • Last Modified: 23-Jun-2011 14:13:11
Revisions
  • Version: 2 public model Download this version
    • Submitted on: 23-Jun-2011 14:13:11
    • Submitted by: Hyun Uk Kim
    • With comment: Current version of Kim2010_VvuMBEL943_GSMR
  • Version: 1 public model Download this version
    • Submitted on: 30-Nov-2010 15:46:29
    • Submitted by: Hyun Uk Kim
    • With comment: Original import of HyunUkKim2010_VvuMBEL943_MetabolicModeling