Citation:

JONES, W. J., R. C. KOLANCZYK, O. MEKENYAN, A. PROTZEL, AND P. K. SCHMIEDER. SIMULATING METABOLISM TO ENHANCE EFFECTS MODELING. Presented at BOSC SP2 Review, Research Triangle Park, NC, February 07 - 09, 2007.

Impact/Purpose:

This task is divided into four major research areas: (1) Development of computational tools and databases for screening-level modeling of the environmental fate of organic chemicals; (2) Metabolism of xenobiotics: Enhancing the development of a metabolic simulator; (3) Metabonomics: The use of advanced analytical tools to identify toxicity pathways; and (4) Software infrastructure to support development and application of transformation/metabolic simulators.

For many chemicals, multiple transformation/metabolic pathways can exist. Consequently, transformation/metabolic simulators must utilize transformation rate data for prioritization of competing pathways. The prioritization process thus requires the integration of reliable rate data. When this data is absent, it is necessary to generate a database with metabolic and transformation rate constants based on: (1) experimentally measured values, including those requiring the use of advanced analytical techniques for measuring metabolic rate constants in vivo and in vitro; (2) rate constants derived from SPARC and mechanistic-based QSAR models; and (3) data mined from the literature and Program Office CBI. A long-term goal of this project is to build this database. This information will be used to enhance the predictive capabilities of the transformation/metabolic simulators. As indicated previously, exposure genomics, which provide early signs of chemical exposure based on changes in gene expression, will be used to guide chemical fate and metabolism studies. The incorporation of exposure genomics into fate studies will provide information concerning (1) the minimal concentrations at which biological events occur; and (2) the identification of biologically relevant chemicals(s) in mixtures.

The capability of categorizing chemicals and their metabolites based on toxicity pathway is imperative to the success of the CompTox Research Program. Metabonomics, which is the multi-parametric measurement of metabolites in living systems due to physiological stimuli and/or genetic modification, provides such a capability. The application of metabonomics to toxicity testing involves the elucidation of changes in metabolic patterns associated with chemical toxicity based on the measurement of component profiles in biofluids, and enables the generation of spectral profiles for a wide range of endogenous metabolites. Metabolic profiles can provide a measure of the real outcome of potential changes as the result of xenobiotic exposure.

Description:

A major uncertainty that has long been recognized in evaluating chemical toxicity is accounting for metabolic activation of chemicals resulting in increased toxicity. The proposed research will develop a capability for forecasting the metabolism of xenobiotic chemicals of EPA interest and to allow prediction of the most likely chemical metabolites to be formed. The information is interfaced with toxic effect models allowing prediction of parent chemical toxic potential and of chemical metabolites of equal or greater toxicity than the parent chemical. These predictions will enable reasonable decisions to be made as to whether or not empirical studies are required to further refine a risk assessment, and will allow OPPTS to move toward a new assessment paradigm that targets specific effects data needs, for specific chemicals and exposures, that are essential to assess and manage risks appropriately.

Record Details: