Computer modeling of muscle phosphofructokinase kinetics

Waser, Mark R.; Garfinkel, Lillian; Kohn, Michael C.; Garfinkel, David

doi:10.1016/0022-5193(83)90030-9

Cited by 14 publications

(5 citation statements)

References 19 publications

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“…, Ning et al, 1969;Kosow & Rose, 1970), but they both are widely scattered and were obtained under circumstances leading to doubt concerning their validity. However, its effect as an inhibitor of hexokinase is weak compared with the corresponding effect on phosphofructokinase (Waser et al, 1983). The chelates of a number of metal ions with ATP are inhibitory, and may be involved in disease conditions (e.g.…”

Section: Inhibitorsmentioning

confidence: 99%

Kinetic properties of hexokinase as assembled with a microcomputer data base

Garfinkel

Matsiras

et al. 1987

Biochemical Journal

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We have constructed a relational data base containing the kinetic properties of the isoenzymes of hexokinase using the Knowledgeman data-base program on an IBM PC microcomputer. The natural subunit of this data base is the refereed publication, 165 of which were included. Reported values for the Mr (approx. 97,000) are in good agreement, but this agreement becomes progressively worse as one examines the Km values for glucose and ATP and the Ki for glucose 6-phosphate, where the reported values are spread over three orders of magnitude. Some quantities are very thinly or unreliably determined. Experimental conditions, especially free Mg2+ concentration, are rarely close to physiological. Reasons for the spread or uncertainty of numbers, and the distinctions that can be made between isoenzymes despite this spread, are discussed.

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Section: Inhibitorsmentioning

confidence: 99%

Kinetic properties of hexokinase as assembled with a microcomputer data base

Garfinkel

Matsiras

et al. 1987

Biochemical Journal

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“…The PFK-1 model was substituted by the pseudorandom order, statistical inhibition model originally developed by Waser et al (57) and adapted by Connett (10). In this section, the adaptations of this model are described.…”

Section: Methodsmentioning

confidence: 99%

“…Hereto, the kinetic model of PFK activity in a previously reported mathematical model of the glycolytic pathway (Vinnakota KC, Rusk J, Palmer L, Shankland E, Kushmerick MJ. J Physiol 588: 1961-1983) was adapted to contain a calcium-calmodulin binding sensitivity. The two main results were introduction of regulation of PFK-1 activity by binding of a calcium-calmodulin complex in combination with activation by increased concentrations of AMP and ADP was essential to qualitatively and quantitatively explain the experimental observations.…”

mentioning

confidence: 99%

Combined in vivo and in silico investigations of activation of glycolysis in contracting skeletal muscle

Schmitz

Groenendaal

Wessels

et al. 2013

American Journal of Physiology-Cell Physiology

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The hypothesis was tested that the variation of in vivo glycolytic flux with contraction frequency in skeletal muscle can be qualitatively and quantitatively explained by calciumcalmodulin activation of phosphofructokinase (PFK-1). Ischemic rat tibialis anterior muscle was electrically stimulated at frequencies between 0 and 80 Hz to covary the ATP turnover rate and calcium concentration in the tissue. Estimates of in vivo glycolytic rates and cellular free energetic states were derived from dynamic changes in intramuscular pH and phosphocreatine content, respectively, determined by phosphorus magnetic resonance spectroscopy ( 31 P-MRS). Computational modeling was applied to relate these empirical observations to understanding of the biochemistry of muscle glycolysis. Hereto, the kinetic model of PFK activity in a previously reported mathematical model of the glycolytic pathway (Vinnakota KC, Rusk J, Palmer L, Shankland E, Kushmerick MJ. J Physiol 588: 1961-1983) was adapted to contain a calcium-calmodulin binding sensitivity. The two main results were introduction of regulation of PFK-1 activity by binding of a calcium-calmodulin complex in combination with activation by increased concentrations of AMP and ADP was essential to qualitatively and quantitatively explain the experimental observations. Secondly, the model predicted that shutdown of glycolytic ATP production flux in muscle postexercise may lag behind deactivation of PFK-1 (timescales: 5-10 s vs. 100 -200 ms, respectively) as a result of accumulation of glycolytic intermediates downstream of PFK during contractions. glycolysis; skeletal muscle; calcium regulation; 31 P-MRS; computational modeling; systems biology GLYCOLYSIS PLAYS A CENTRAL role in catabolism and anabolism for all cell types (20; 44). Identification of regulatory mechanisms has been important to many areas of biomedical research, ranging from basic understanding of the biochemistry of carbohydrate utilization to applications in biotechnology (48) and drug development for cancer therapies (39). In mammalian cells, skeletal muscle has been a key experimental model to study the regulation of glycolysis and glycogenolysis. It can increase the glycogenolytic ATP production flux by two orders of magnitude during rest to work transitions on a timescale of seconds (56). This exceptionally broad and dynamic operational range of glyco(genol)ytic flux puts a high duty cycle upon the control mechanism(s) of this pathway.Several approaches have been used to elucidate the underlying regulatory mechanisms including physical isolation and in vitro kinetic characterization of individual enzymes from skeletal muscle providing a wealth of information on the individual components of this pathway (3). The application of noninvasive, nondestructive investigative techniques such as in vivo nuclear magnetic resonance spectroscopy (MRS) have since allowed studying the behavior of the intact pathway in muscle (8). For example, it has been demonstrated that glycolytic flux rapidly shuts down in the absence of mu...

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“…These models often require the solution of systems of differential equations (Bierbicher, Eigen and Gardiner, 1983;Franco and Canela, 1984;Kohn and Garfinkel, 1983a;Kohn and Garfinkel, 1983b;Waser et al, 1983). However, in most metabolic pathways, either we are unaware of all the steps involved or we lack rate constants for each step.…”

Section: Simulation Methodsmentioning

confidence: 99%

Knowledge-based simulation of DNA metabolism: prediction of enzyme action

1991

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We have developed a knowledge-based simulation of DNA metabolism that accurately predicts the actions of enzymes on DNA under a large number of environmental conditions. Previous simulations of enzyme systems rely predominantly on mathematical models. We use a frame-based representation to model enzymes, substrates, and conditions. Interactions between these objects are expressed using production rules and an underlying truth maintenance system. The system performs rapid inference and can explain its reasoning. A graphical interface provides access to all elements of the simulation, including object representations and explanation graphs. Predicting enzyme action is the first step in the development of a large knowledge base to envision the metabolic pathways of DNA replication and repair.

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Computer modeling of muscle phosphofructokinase kinetics

Cited by 14 publications

References 19 publications

Kinetic properties of hexokinase as assembled with a microcomputer data base

Kinetic properties of hexokinase as assembled with a microcomputer data base

Combined in vivo and in silico investigations of activation of glycolysis in contracting skeletal muscle

Knowledge-based simulation of DNA metabolism: prediction of enzyme action

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