G-protein coupled receptors (GPCRs) are the largest protein family of drug targets.Detailed mechanisms of binding are unknown for many important GPCR-ligand pairs due to the difficulties of GPCR recombinant expression, biochemistry, and crystallography. We describe our new method, ConDock, for predicting ligand binding sites in GPCRs using combined information from surface conservation and docking starting from crystal structures or homology models. We demonstrate the effectiveness of ConDock on well-characterized GPCRs such as the 2 adrenergic and A2A adenosine receptors. We also demonstrate that ConDock successfully predicts ligand binding sites from high-quality homology models. Finally, we apply ConDock to predict ligand binding sites on a structurally uncharacterized GPCR, GPER. GPER is the Gprotein coupled estrogen receptor, with four known ligands: estradiol, G1, G15, and tamoxifen.ConDock predicts that all four ligands bind to the same location on GPER, centered on L119, H307, and N310; this site is deeper in the receptor cleft than predicted by previous studies. We compare the sites predicted by ConDock and traditional methods that utilize information from surface geometry, surface conservation, and ligand chemical interactions. Incorporating sequence conservation information in ConDock overcomes errors introduced from physics-based scoring functions and homology modeling.

High concentrations of estrogenic compounds can overstimulate estrogen receptors and potentially lead to breast, ovarian, and cervical cancers. Recently, a G-protein coupled estrogen receptor (GPER/GPR30) was discovered that has no structural similarity to the wellcharacterized, classical estrogen receptor ERα. The crystal structure of GPER has not yet been determined, and the ligand binding sites have not yet been experimentally identified. The recent explosion of GPCR crystal structures now allow homology modeling with unprecedented reliability. We create, validate, and describe a homology model for GPER. We describe and apply ConDock, the first hybrid scoring function to use information from protein surface conservation and ligand docking, to predict binding sites on GPER for four ligands, estradiol, G1, G15, and tamoxifen. ConDock is a simple product function of sequence conservation and binding energy scores. ConDock predicts that all four ligands bind to the same location on GPER, centered on L119, H307, and N310; this site is deeper in the receptor cleft than are ligand binding sites predicted by previous studies. We compare the sites predicted by ConDock and traditional methods analyzing surface geometry, surface conservation, and ligand chemical interactions. Incorporating sequence conservation information in ConDock avoids errors resulting from physics-based scoring functions and modeling.

GPCRs (G-protein coupled receptors) are the largest family of drug targets and share a conserved structure. Binding sites are unknown for many important GPCR ligands due to the difficulties of GPCR recombinant expression, biochemistry, and crystallography. We describe our approach, ConDockSite, for predicting ligand binding sites in class A GPCRs using combined information from surface conservation and docking, starting from crystal structures or homology models. We demonstrate the effectiveness of ConDockSite on crystallized class A GPCRs such as the beta2 adrenergic and A2A adenosine receptors. We also demonstrate that ConDockSite successfully predicts ligand binding sites from high-quality homology models. Finally, we apply ConDockSite to predict the ligand binding sites on a structurally uncharacterized GPCR, GPER, the G-protein coupled estrogen receptor. Most of the sites predicted by ConDockSite match those found in other independent modeling studies. ConDockSite predicts that four ligands bind to a common location on GPER at a site deep in the receptor cleft. Incorporating sequence conservation information in ConDockSite overcomes errors introduced from physics-based scoring functions and homology modeling.