Steady-state kinetic properties of sorbitol dehydrogenase from chicken liver

We describe a believed-novel procedure for translating metabolite profiles (metabolome) into the set of metabolic fluxes (fluxome) from which they originated. Methodologically, computational modeling is integrated with an analytical platform comprising linear optimization, continuation and dynamic analyses, and metabolic control. The procedure was tested with metabolite profiles obtained from ex vivo mice Langendorff-heart preparations perfused with glucose. The metabolic profiles were analyzed using a detailed kinetic model of the glucose catabolic pathways including glycolysis, pentose phosphate (PP), glycogenolysis, and polyols to translate the glucose metabolome of the heart into the fluxome. After optimization, the ability of the model to simulate the initial metabolite profile was confirmed, and metabolic fluxes as well as the structure of control and regulation of the glucose catabolic network could be calculated. We show that the step catalyzed by phosphofructokinase together with ATP demand and glycogenolysis exert the highest control on the glycolytic flux. The negative flux control exerted by phosphofructokinase on the PP and polyol pathways revealed that the extent of glycolytic flux directly affects flux redirection through these pathways, i.e., the higher the glycolytic flux the lower the PP and polyols. This believed-novel methodological approach represents a step forward that may help in designing therapeutic strategies targeted to diagnose, prevent, and treat metabolic diseases.

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From Metabolomics to Fluxomics: A Computational Procedure to Translate Metabolite Profiles into Metabolic Fluxes

Cortassa

Caceres

Bell

et al. 2015

Biophysical Journal

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Effects of some anti-neoplastic drugs on sheep liver sorbitol dehydrogenase

Alım

Beydemır

2012

Archives of Physiology and Biochemistry

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Stress is an important factor for many diseases in living metabolisms. The mini pathway named as polyol is a critical junction for stress factors. This pathway has two enzymes: aldose reductase (AR) and sorbitol dehydrogenase (SDH). It is linked with some diseases such as diabetes mellitus and some cancer types. In particular, SDH is very sensitive and unstable in in vitro conditions. In this study, SDH was purified by using simple and rapid chromatographic methods such as DEAE-Sephadex and CM-Sephadex C-50 columns. Subunit and active form molecular weights were found as 39.8 kDa and 150 kDa, respectively. The in vitro effects of some antineoplastic drugs were investigated. IC(50) values were 0.025, 0.081, 0.291, 1.62, 4.86, 6.54 mM for dacarbazine, methotrexate, epirubicin hydrochloride, calcium folinate, gemcitabine hydrochloride, oxaliplatin, respectively. From these results, dacarbazine was lowest IC(50) value and it is the strongest inhibitor for liver SDH enzyme activity compared to the other drugs.

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Steady-state kinetic properties of sorbitol dehydrogenase from chicken liver

Cited by 2 publications

References 22 publications

From Metabolomics to Fluxomics: A Computational Procedure to Translate Metabolite Profiles into Metabolic Fluxes

From Metabolomics to Fluxomics: A Computational Procedure to Translate Metabolite Profiles into Metabolic Fluxes

Effects of some anti-neoplastic drugs on sheep liver sorbitol dehydrogenase

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