A computational model for biochemical pathways with applications to metabolic processes.

摘要

Statement of the problem. The development of computational models allows one to easily reveal and quantify certain behaviors of the biochemical network of interest. The existing models for chemical reactions based on the Michaelis-Menten approach are highly nonlinear and could cause computational instability for a network of reactions. The objectives of this thesis are (1) to develop a model for chemical reactions that is robust and stable for simulating biochemical pathways, (2) to design a customized software and graphic user interface (GUI) for easy implementation of model-based simulations, and (3) to apply the modeling and simulation system to a metabolic process namely glycolysis---the metabolism of glucose.;Methods. The modeling and simulation system was implemented in the C++ programming language using a cross-platform development tool, wxWidgets. A set of rate equations were used to describe the dynamics of a system with a compartment-like physical model. This allows for the reduction of such complexities that can restrict the model's overall stability. A novel approach to modeling the driving force of chemical reactions that comprise biochemical pathways has been established. This method models the kinetics of the reaction by relating the mechanisms of the reaction to a common physical model. Using this approach, the differential equations or state equations that characterize the dynamics of the chemical reactions were established. Numerical methods were then used to solve these equations via a 2nd order Runge-Kutta method. After establishing the modeling methodology for its validity, a GUI was designed and developed for data entry, parameter storage and retrieval, model simulation, display of the concentration time-series curves, and for linking reactions to form a pathway.;Results. The modeling and simulation system was successfully implemented. The computational part of the customized C++ program was validated against the results from MatLab. Selected steps from the 10-step glycolysis process were simulated and produced results consistent with those reported in literature. The model's reliability was tested by reversing the reaction's driving potential. The model was robust with respect to the initial conditions, inconsistent and/or incomplete data for assigning the model parameters. It has been concluded that this modeling approach gives logical and consistent results. For future work, the software developed in this thesis will be used to study the complete pathway of glycolysis and other biochemical pathways.