Risk assessment is used at every level of government as part of cost-benefit analysis. Since the cytochrome P450 enzymes play a central role in both detoxification and bioactiviation, predictive models for cytochrome P450 catalysis will be useful tools for evaluating the potential risks of environmental exposures. This proposal outlines steps towards the development of models that can translate laboratory data into computational models for the P450s. Both have been successful, but for the purposes of this application the focus is on the electronic component. The electronic component is dominant in those subsets of P450 catalyzed reactions which involve small, hydrophobic molecules that have few functional groups or polarizable sites. We have developed a model that can accurately predict (1) the LD-50 in mice of a structurally diverse set of nitriles, (2) the rates of in vitro metabolism of substituted toluenes and haloalkanes, and (3) the rates of in vivo metabolism of inhalation anesthetics (see Section C). This proposal outlines experiments that will allow us to expand our models for P450 mediated reactions to include a more diverse set of substrates.
The specific aims of this proposal are as follows:
Specific Aim 1. To determine the energy differences for; (1) hydrogen atom abstractions from the carbon atoms adjacent to different functional groups, and (2) addition to a series of aromatic compounds.
Specific Aim 2. To establish that tert-butoxy radical (t-ButO) is a good chemical model for the iron-oxene species of P450.
Specific Aim 3. To develop a computational model for the active oxygen species of P450 that will allow us to predict the rates of both hydrogen atom abstraction and aromatic addition. By completing the experiments described in Specific Aims 1 and 2, we will build a experimental database that can be compared with the computational results developed under Specific Aim 3. The experimental data can be used to correct for any deficiencies in the computational methods. The end product will be a carefully constructed model for the electronic component of P450 mediated reactions. The model will represent the next level of complexity in striving for a complete model of P450 mediated reactions and will enhance the scope of the model's utility as a risk assessment tool for molecules that are bioactivated by P450.
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