Simulation of cellular biochemical system kinetics

Abstract

The goal of realistically and reliably simulating the biochemical processes underlying cellular function is achievable through a systematic approach that makes use of the broadest possible amount of in vitro and in vivo data, and is consistent with all applicable physical chemical theories. Progress will be facilitated by establishing: (1) a concrete self-consistent theoretical foundation for systems simulation; (2) extensive and accurate databases of thermodynamic properties of biochemical reactions; (3) parameterized and validated models of enzyme and transporter catalytic mechanisms that are consistent with physical chemical theoretical foundation; and (4) software tools for integrating all these concepts, data, and models into a cohesive representation of cellular biochemical systems. Ongoing initiatives are laying the groundwork for the broad-based community cooperation that will be necessary to pursue these elements of a strategic infrastructure for systems simulation on a large scale.

Figure B1.1

Phosphate metabolite levels in the heart in vivo. A: Measured ratio of [CrP]/[ATP] plotted as a function MVO₂. Measured ratio of [P_i]/[CrP] plotted as a function MVO₂. Data are adapted from: 엯, Zhang et al. [47]; ◁, Zhang et al. [48]; ◇, Gong et al. [49]; △, Ochiai et al. [50]; ▽, Gong et al. [51]; ◻, Bache et al. [52]. (Shaded data points indicate situation when P_i is below limit of detection.)

Figure B1.2

Feedback control of oxidative phosphorylation in the heart. The rate of mitochondrial synthesis is physiologically activated by products of ATP hydrolysis, of which P_i is the most important controller, as illustrated in A. Panels B and C shows comparison of predictions of Equation (B.5) with data obtained from ³¹P-magnetic resonance spectroscopy (³¹P-MRS). Data in B and C are adapted from [47-52]. Shaded data points indicate situation when P_i is below limit of detection. Model predictions use W_max = 5.14 · W^R. The factor α (set to 1.12) in panel B accounts for the fact that that ATP signal measured from ³¹P-MRS arises from cytosolic plus mitochondrial ATP, while CrP is confined to the cytosol.

Figure B2.1

Dependence of the apparent Michaelis-Menten constant for isocitrate for NAD-dependent isocitrate dehydrogenase on free Mg²⁺ concentration. Values assumed for dissociation constants are K_H1 = 2.29 μM, K_H2 = 46.8 μM, and K_Mg = 1.91 mM; [H⁺] = 10⁻⁷ M.

Figure 1

Strategic approach to biochemical systems modeling and analysis. Models are constructed based on three major data sets: biochemical thermodynamics, kinetics of enzymes in vitro, and systems-level data, such as from intact organelles, cells, tissues, and/or organs. Thermodynamic data are used to construct databases of thermodynamic properties; enzyme kinetic data and thermodynamic property data are used to develop models of individual enzyme and transporter mechanisms. Individual enzyme and transporter models are integrated together to build systems-level models that are parameterized and validated using systems-level data.