| Literature DB >> 23744946 |
Roger L Chang1, Kathleen Andrews, Donghyuk Kim, Zhanwen Li, Adam Godzik, Bernhard O Palsson.
Abstract
Genome-scale network reconstruction has enabled predictive modeling of metabolism for many systems. Traditionally, protein structural information has not been represented in such reconstructions. Expansion of a genome-scale model of Escherichia coli metabolism by including experimental and predicted protein structures enabled the analysis of protein thermostability in a network context. This analysis allowed the prediction of protein activities that limit network function at superoptimal temperatures and mechanistic interpretations of mutations found in strains adapted to heat. Predicted growth-limiting factors for thermotolerance were validated through nutrient supplementation experiments and defined metabolic sensitivities to heat stress, providing evidence that metabolic enzyme thermostability is rate-limiting at superoptimal temperatures. Inclusion of structural information expanded the content and predictive capability of genome-scale metabolic networks that enable structural systems biology of metabolism.Entities:
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Year: 2013 PMID: 23744946 PMCID: PMC3777776 DOI: 10.1126/science.1234012
Source DB: PubMed Journal: Science ISSN: 0036-8075 Impact factor: 47.728