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Critical perspective on the consequences of the limited availability of kinetic data in metabolic dynamic modelling

Authors :
Rafael S. Costa
Isabel Rocha
Eugénio C. Ferreira
Daniel Machado
Universidade do Minho
Source :
Repositório Científico de Acesso Aberto de Portugal, Repositório Científico de Acesso Aberto de Portugal (RCAAP), instacron:RCAAP
Publication Year :
2011

Abstract

Detailed kinetic models at the network reaction level are usually constructed using enzymatic mechanistic rate equations and the associated kinetic parameters. However, during the cellular life cycle thousands of different reactions occur, which makes it very difficult to build a detailed large-scale ldnetic model. In this work, we provide a critical overview of specific limitations found during the reconstruction of the central carbon metabolism dynamic model from E. coli (based on kinetic data available). In addition, we provide clues that will hopefully allow the systems biology community to more accurately construct metabolic dynamic models in the future. The difficulties faced during the construction of dynamic models are due not only to the lack of kinetic information but also to the fact that some data are still not curated. We hope that in the future, with the standardization of the in vitro enzyme protocols the approximation of in vitro conditions to the in vivo ones, it will be possible to integrate the available kinetic data into a complete large scale model. We also expect that collaborative projects between modellers and biologists will provide valuable kinetic data and permit the exchange of important information to solve most of these issues.<br />Rafael S. Costa would like to thank Fundacao para a Ciencia e Tecnologia for providing the grant SFRH/BD/25506/2005. The authors also acknowledge the MIT-Portugal project 'Bridging Systems and Synthetic Biology for the development of improved microbial cell factories' MIT-Pt/BS-BB/0082/2008.

Details

ISSN :
17518849
Volume :
5
Issue :
3
Database :
OpenAIRE
Journal :
IET systems biology
Accession number :
edsair.doi.dedup.....f50207b03aa31282b212bc6387694957