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Theory of partial agonist activity of steroid hormones

1 Mathematical Biology Section, NIDDK/LBM, National Institutes of Health, Bethesda, MD 20892-5621, USA;
2 Steroid Hormones Section, NIDDK/LERB, National Institutes of Health, Bethesda, MD 20892-1772, USA;
3 Computational Biology Program, New York University School of Medicine, New York, NY 10016, USA;
4 Science Department, Tuscarora High School, Loudoun County Public Schools, Leesburg, VA 20176, USA

Special Issues: Steroid hormone receptor regulation and function

The different amounts of residual partial agonist activity (PAA) of antisteroids under assorted conditions have long been useful in clinical applications but remain largely unexplained. Not only does a given antagonist often afford unequal induction for multiple genes in the same cell but also the activity of the same antisteroid with the same gene changes with variations in concentration of numerous cofactors. Using glucocorticoid receptors as a model system,we have recently succeeded in constructing from first principles a theory that accurately describes how cofactors can modulate the ability of agonist steroids to regulate both gene induction and gene repression. We now extend this framework to the actions of antisteroids in gene induction. The theory shows why changes in PAA cannot be explained simply by differences in ligand affinity for receptor and requires action at a second step or site in the overall sequence of reactions. The theory also provides a method for locating the position of this second site,relative to a concentration limited step (CLS),which is a previously identified step in glucocorticoid-regulated transactivation that always occurs at the same position in the overall sequence of events of gene induction. Finally,the theory predicts that classes of antagonist ligands may be grouped on the basis of their maximal PAA with excess added cofactor and that the members of each class differ by how they act at the same step in the overall gene induction process. Thus,this theory now makes it possible to predict how different cofactors modulate antisteroid PAA,which should be invaluable in developing more selective antagonists.
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