Premium
Developing a detailed model of Hexokinase using wREFERASS to implement the King‐Altman method
Author(s) -
Christmas Kevin M
Publication year - 2019
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.2019.33.1_supplement.633.5
Subject(s) - kinetic energy , chemistry , reaction rate constant , hexokinase , dissociation (chemistry) , parameterized complexity , dissociation constant , thermodynamics , enzyme , computational chemistry , kinetics , computer science , physics , organic chemistry , biochemistry , quantum mechanics , algorithm , receptor , glycolysis
A full kinetic model for enzymatic facilitation of substrate to product should account and provide equations for the binding for all reactants, the multiple enzyme‐reactant states, the inherent ordered or random binding mechanisms for substrates, ions, or protons that modulate the kinetic activity. Kinetic models of this quality are uncommon because the simpler Michaelis‐Menten (MM) representations have been considered adequate. MM approximations are for steady state conditions; they are inaccurate during transients; they cannot accommodate circumstances in which the concentration of reactants are close to the affinity or dissociation constant of the enzyme. The ease in implementing MM has simplified the general understanding of enzymes, biology, and stunted the exploration for better quantitative methods of higher accuracy in enzymology. Here we report the of an enzymatic tool wREFERASS (Garcia‐Sevilla et al., 2010) to develop a complex kinetic model of skeletal muscle hexokinase (EC 2.7.1.1) using the King‐Altman notation: all terms consist of rate constants and reactant concentrations. The wREFERASS tool derives detailed mathematical expressions based on an input file that describes explicitly the kinetic pathways. The expressions provide unitary balance, conserves mass, and require defining and parameterizing the dissociation constants for each binding step. Rate constants and dissociation constants were parameterized using enzymatic data obtained from Lueck and Fromm (1973) on rat skeletal muscle hexokinase II. The kinetic model accounts for all reactants described from the input file and has physical units for all biological elements. The kinetic behavior far surpasses any MM representation due to the consideration of the multiple enzyme states. It accounts for time delay due to binding, shifts in conformational states and product release. After parameterizing each dissociation and rate constant it becomes clear that there is a preferred kinetic pathway for phosphorylation of glucose even though the binding mechanism is referred to as ‘random ordered’. Even with some parameter uncertainty by using detailed kinetic models we can develop targeted hypotheses on the less secure parameters. This approach is also attractive because every element of the pathway is explicit, results in little to no simplification of terms, and allows parameters to better reflect the biology. These models reintroduce time delays that exist in biology and metabolism and increases the accuracy of their predictions. Considerable work goes into developing a kinetic model that is not limited by MM assumptions. This model is archived at www.Physiome.org/Models/providing source code and a model that can be run over the web or downloaded. Support or Funding Information Supported by NIH grant: U01‐HL122199 This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .