Virtual and biomolecular screening converge on a selective agonist for GPR30.

Estrogen is a hormone critical in the development, normal physiology and pathophysiology of numerous human tissues. The effects of estrogen have traditionally been solely ascribed to estrogen receptor alpha (ERalpha) and more recently ERbeta, members of the soluble, nuclear ligand-activated family of transcription factors. We have recently shown that the seven-transmembrane G protein-coupled receptor GPR30 binds estrogen with high affinity and resides in the endoplasmic reticulum, where it activates multiple intracellular signaling pathways. To differentiate between the functions of ERalpha or ERbeta and GPR30, we used a combination of virtual and biomolecular screening to isolate compounds that selectively bind to GPR30. Here we describe the identification of the first GPR30-specific agonist, G-1 (1), capable of activating GPR30 in a complex environment of classical and new estrogen receptors. The development of compounds specific to estrogen receptor family members provides the opportunity to increase our understanding of these receptors and their contribution to estrogen biology.

Integration of virtual screening with high-throughput flow cytometry to identify novel small molecule formylpeptide receptor antagonists.

The formylpeptide receptor (FPR) family of G-protein-coupled receptors contributes to the localization and activation of tissue-damaging leukocytes at sites of chronic inflammation. We developed a FPR homology model and pharmacophore (based on the bovine rhodopsin crystal structure and known FPR ligands, respectively) for in silico screening of approximately 480,000 drug-like small molecules. A subset of 4324 compounds that matched the pharmacophore was then physically screened with the HyperCyt flow cytometry platform in high-throughput, no-wash assays that directly measure human FPR binding, with samples (each approximately 2500 cells in 2 microl) analyzed at 40/min. From 52 confirmed hits (1.2% hit rate), we identified 30 potential lead compounds (inhibition constant, Ki= 1-32 microM) representing nine distinct chemical families. Four compounds in one family were weak partial agonists. All others were antagonists. This virtual screening approach improved the physical screening hit rate by 12-fold (versus 0.1% hit-rate in a random compound collection), providing an efficient process for identifying small molecule antagonists.