Impact/Purpose:
For many mechanisms of toxicity the key differential process is the interaction between the ultimate toxicant and a macromolecular target (receptor-ligand, enzyme-substrate, DNA-genotoxicant, etc.). Modeling this process on a molecular level provides an approach for prioritizing chemical information needs. This interaction initiates a cascade of events leading to the ultimate (adverse) outcome. Computational molecular models of the interaction of a molecule (potential toxicant or its metabolites) with the relevant target, provides insight into the
capacity of a chemical to initiate the relevant cascade. A number of recent scientific and technical advances facilitate this approach. First, many of the relevant targets have been identified experimentally. The molecular structure of some of these targets has been determined and additional information of this type is likely to become available in the future. Second, molecular modeling software for the simulation and analysis of interactions of this type has become more sophisticated in a number of relevant ways and make it possible to more realistically simulate the processes of toxicity. These advances have resulted
from both basic computational investigations of the structure and dynamics of macromolecules in biological systems and the requirements of the pharmaceutical industry for the discovery of
new therapeutic agents. Third, computational hardware and visualization techniques have steadily improved. Increased processing speed and memory have made it possible to include large segments of macromolecules in classical simulations and even in quantum mechanical calculations. We are applying molecular modeling methods, fueled by these current scientific and technological advances, to investigating chemicals for their capacity to cause toxicity through specific modes of action and using a target-toxicant paradigm.
Initially, this approach is being applied to the study of environmental endocrine disruption. Crystal structures exist in the literature for many receptors in the endocrine system. By removal of the ligand computationally these crystal structures are used to create virtual
biomolecular targets for endocrine disruption. The best fit to the target for each of a series of potential ligands can then be determined by computational methods. The properties of this fit may then be used as part of a scheme to predict the potential of an environmental agent to cause endocrine disruption.
Project Information:
Progress
:There is increasing concern about the potential of environmental chemicals to produce adverse health effects through interaction with the endocrine system. One general mechanism for disruption of the endocrine system involves competition for steroid hormone binding sites by xenobiotic chemicals that may fully or partially mimic natural hormones. Crystal structures of the estrogen and androgen receptors have been used to create macromolecular targets. Multiple crystal structures available for the estrogen receptor have been used to demonstrate the importance of including receptor flexibility in determining the best fit and therefore the chemicals likely have the most effect. Studies on including flexibility are in progress. In other preliminary studies, methods existing methods are being employed. Using a data base containing estrogens, androgens and chemicals that bind to other nuclear, it was found that the results for a single receptor, considered individually, did not correctly order the ligands according to the ability to bind to that receptor. However, when the data for a series of receptors is considered simultaneously and the results analyzed to determine which receptor a chemical interacts with most favorably, all chemicals are classified correctly.
An additional Agency concern, that may be approached with the target-toxicant paradigm and molecular modeling, is the cumulative risk of some specific pesticides on the enzyme acetylcholinesterase (AChE). There is some data that indicates that AChE has two binding sites, the catalytic site and an allosteric site that affects the specificity and efficacy of the enzyme. In experiments involving just a single toxicant it is not possible to identify the site of interaction but we have shown that for mixtures of AChE active chemicals the cumulative toxicity depends on the relative interaction of each chemical with each site. A computational scheme is being developed for the cumulative toxicity of mixtures that takes advantage of the two site model.
Approach
:For many mechanisms of toxicity the key differential process is the interaction between the ultimate toxicant and a macromolecular target (receptor-ligand, enzyme-substrate, DNA-genotoxicant, etc.). Modeling this process on a molecular level provides an approach for prioritizing chemical information needs. This interaction initiates a cascade of events leading to the ultimate (adverse) outcome. Computational molecular models of the interaction of a molecule (potential toxicant or its metabolites) with the relevant target, provides insight into the capacity of a chemical to initiate the relevant cascade.
A number of recent scientific and technical advances facilitate this approach. First, many of the relevant targets have been identified experimentally. The molecular structure of some of these targets has been determined and additional information of this type is likely to become available in the future. Second, molecular modeling software for the simulation and analysis of interactions of this type has become more sophisticated in a number of relevant ways and make it possible to more realistically simulate the processes of toxicity. These advances have resulted from both basic computational investigations of the structure and dynamics of macromolecules in biological systems and the requirements of the pharmaceutical industry for the discovery of new therapeutic agents. Third, computational hardware and visualization techniques have steadily improved. Increased processing speed and memory have made it possible to include large segments of macromolecules in classical simulations and even in quantum mechanical calculations. We are applying molecular modeling methods, fueled by these current scientific and technological advances, to investigating chemicals for their capacity to cause toxicity through specific modes of action and using a target-toxicant paradigm.
Initially, this approach is being applied to the study of environmental endocrine disruption. Crystal structures exist in the literature for many receptors in the endocrine system. By removal of the ligand computationally these crystal structures are used to create virtual biomolecular targets for endocrine disruption. The best fit to the target for each of a series of potential ligands can then be determined by computational methods. The properties of this fit may then be used as part of a scheme to predict the potential of an environmental agent to cause endocrine disruption.
The ultimate goal of this research is to develop a library of biomolecular targets for chemical toxicity and methods appropriate for the prediction of the ability of a chemical to interact with these targets. These targets may then by used as part of a chemical prescreen.
Relevance
:This research addresses the Agency need for predictive models for hazard identification, both the sub areas of QSAR and other computational approaches and High Throughput Screening.
Project IDs:
ID Code
:IIC-2
Project type
:Partner Specific