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NEW 3D TECHNIQUES FOR RANKING AND PRIORITIZATION OF CHEMICAL INVENTORIES
Citation:
Mekenyan, O. G., P. K. Schmieder, AND S P. Bradbury. NEW 3D TECHNIQUES FOR RANKING AND PRIORITIZATION OF CHEMICAL INVENTORIES. Presented at SCOPE/UPAC International Symposium on Endocrine Active Substances, Yokohama, Japan, November 17-21, 2002.
Description:
New three-dimensional quantitative structure activity (3-D QSAR) techniques for prioritizing chemical inventories for endocrine activity will be presented. The Common Reactivity Pattern (COREPA) approach permits identification of common steric and/or electronic patterns associated with diverse chemicals that have similar biological activity. Compared to conventional 3-D QSAR techniques, the COREPA approach does not require structural alignments between compounds in a training set, or test set, and a lead compound. Instead, the conformational distributions of biologically-similar chemicals across specific molecular descriptors are compared. The COREPA approach also differs with traditional methods by incorporating conformational flexibility of the ligand. All energetically reasonable conformers of a chemical are considered in deriving conformational distributions and reactivity patterns. A COREPA model can be determined across single stereoelectronic parameters (i.e., the original formulation of COREPA) or across several relevant parameters to create a multi-dimensional
reactivity pattern (COREPA A-M). The modelling algorithm determines those parameters that best discriminate classes of biologically-dissimilar chemicals, which ultimately leads to a
decision tree for identification of ?active' compounds that maximizes prediction sensitivity.
Reactivity patterns for relative ratER binding affinity (RBA; 17 -estradiol = 100%). Were established in terms of global nucleophilicity, interatomic distances between nucleophilic sites, and local electron donor capability of the nucleophilic sites. These reactivity patterns were used to establish descriptor profiles for identifying and ranking compounds in different RBA ranges. Subsequently, an exploratory expert system was developed for use in ranking relative ER binding affinity potential for large chemical data sets. The system provides 3D screening of such inventories and includes a ?direct tweak' method and a genetic algorithm for rapid and more exhaustive investigations of conformational flexibility of query chemicals, respectively. The COREPA models and 3D screening-techniques were experimentally validated within the Endocrine Disruption Activity of Environmental Pollutants (EDAEP) project administrated by the European Union (EU). Seven high production volume chemicals (HPVCs), out of 907 compounds, were predicted to have relatively low ER binding affinity (RBA <1%), four were randomly selected for empirical evaluation by the ERE-CALUX and human Er -binding assays and found to elicit weak estrongenic activity.