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A Computationally Based Identification Algorithm For Estrogen Receptor Ligands: Part 2. Evaluation Of A Herα Binding Affinity Model, Steven P. Bradbury, O. G. Mekenyan, V. Kamenska, P. K. Schmieder, G. T. Ankley
A Computationally Based Identification Algorithm For Estrogen Receptor Ligands: Part 2. Evaluation Of A Herα Binding Affinity Model, Steven P. Bradbury, O. G. Mekenyan, V. Kamenska, P. K. Schmieder, G. T. Ankley
Steven P. Bradbury
The objective of this study was to evaluate the capability of an expert system described in the previous paper (S. Bradbury et al., Toxicol. Sci. 58, 253–269) to identify the potential for chemicals to act as ligands of mammalian estrogen receptors (ERs). The basis of the expert system was a structure activity relationship (SAR) model, based on relative binding affinity (RBA) values for steroidal and nonsteroidal chemicals derived from human ERa (hERa) competitive binding assays. The expert system enables categorization of chemicals into (RBA ranges of < 0.1, 0.1 to 1, 1 to 10, 10 to 100, and >150% relative to 17b-estradiol. In the current analysis, the algorithm was evaluated with respect …
A Computationally Based Identification Algorithm For Estrogen Receptor Ligands: Part 1. Predicting Herα Binding Affinity, Steven P. Bradbury, V. Kamenska, P. Schmieder, G. Ankley, O. Mekenyan
A Computationally Based Identification Algorithm For Estrogen Receptor Ligands: Part 1. Predicting Herα Binding Affinity, Steven P. Bradbury, V. Kamenska, P. Schmieder, G. Ankley, O. Mekenyan
Steven P. Bradbury
The common reactivity pattern (COREPA) approach is a 3-dimensional, quantitative structure activity relationship (3-D QSAR) technique that permits identification and quantification of specific global and local stereoelectronic characteristics associated with a chemical’s biological activity. It goes beyond conventional 3-D QSAR approaches by incorporating dynamic chemical conformational flexibility in ligand-receptor interactions. The approach provides flexibility in screening chemical data sets in that it helps establish criteria for identifying false positives and false negatives, and is not dependent upon a predetermined and specified toxicophore or an alignment of conformers to a lead compound. The algorithm was recently used to screen chemical data …