Kinetic Analysis of Estrogen Receptor/Ligand Interactions

• Published in: Proceedings of the National Academy of Sciences - PNAS Vol. 99; no. 13; pp. 8562 - 8567
• Main Authors: Rich, Rebecca L., Hoth, Lise R., Geoghegan, Kieran F., Brown, Thomas A., LeMotte, Peter K., Simons, Samuel P., Hensley, Preston, Myszka, David G.
• Format: Journal Article
• Language: English
• Published: United States National Academy of Sciences 25.06.2002; National Acad Sciences
• Subjects: Agonists; Analysis; Antibodies; Antibodies, Monoclonal - metabolism; Benzhydryl Compounds; Biochemistry; Biological Sciences; Biosensing techniques; Bisphenols; Dehydroepiandrosterone - metabolism; Drug interactions; Estrogen Receptor alpha; Estrogen Receptor beta; Estrogens; Kinetics; Ligands; Phenols - metabolism; Protein isoforms; Receptors; Receptors, Estrogen - chemistry; Receptors, Estrogen - metabolism; Recombinant Proteins - chemistry; Recombinant Proteins - metabolism
• ISSN: 0027-8424; 1091-6490
• DOI: 10.1073/pnas.142288199

Surface plasmon resonance biosensor technology was used to directly measure the binding interactions of small molecules to the ligand-binding domain of human estrogen receptor. In a screening mode, specific ligands of the receptor were easily discerned from nonligands. In a high-resolution mode, the association and dissociation phase binding responses were shown to be reproducible and could be fit globally to a simple interaction model to extract reaction rate constants. On average, antagonist ligands (such as tamoxifen and nafoxidine) were observed to bind to the receptor with association rates that were 500-fold slower than agonists (such as estriol and β-estradiol). This finding is consistent with these antagonists binding to an altered conformation of the receptor. The biosensor assay also could identify subtle differences in how the same ligand interacted with two different isoforms of the receptor (α and β). The biosensor's ability to determine kinetic rate constants for small molecule/protein interactions provides unique opportunities to understand the mechanisms associated with complex formation as well as new information to drive the optimization of drug candidates.