A reaction network model for CYP2E1-mediated metabolism of toxicant mixtures

In this paper, we describe a modeling approach to predict the interlinked pathways and kinetics resulting from CYP2E1-mediated metabolism of both pure species and chemical mixtures. This approach is based on the concept of chemical reaction networks, an idea that has formed the basis for simulation tools that have shown good predictive capabilities in the petroleum industry, but also an idea that has heretofore seen minimal application in the biomedical research arena. Although the initial target for developing this reaction network approach was cytochrome P450 2E1 (CYP2E1) and its over 200 substrates, this technology has been used for other families of CYP enzymes and their substrates in our laboratory. Utilizing this approach, we have produced a modular 'predictive metabolomics' simulation framework comprising interdependent software components that perform such tasks as testing of substrate binding feasibility, performing virtual chemistry, formulating reaction-rate equations, computing reaction kinetics and predicting time-dependent species concentrations. As an illustrative example, we outline the application of this framework to the prediction of the reaction networks resulting from the Phase I metabolism of two compounds of important toxicological interest. The potential of this modeling technology is immense in providing a computer simulation platform for complex-chemical mixtures and complex-biological systems. It is possible that this technology will play an important role in formulating a 'Virtual Human'.