Understanding the binding of the same ligand to GPCRs of different families.

G protein-coupled receptors (GPCRs) are the largest class of cell-surface receptor proteins with important functions in signal transduction and often serve as therapeutic drug targets. With the rapidly growing public data on three dimensional (3D) structures of GPCRs and GPCR-ligand interactions, computational prediction of GPCR ligand binding becomes a convincing option to high throughput screening and other experimental approaches during the beginning phases of ligand discovery. Such predictions are cost-efficient and can be important aides for planning wet lab experiments to help elucidate signaling pathways and expedite drug discovery. There are existing computational tools for GPCR ligand binding prediction using various sequence and structural derived features. However, these methods have been typically tested on specific families of GPCRs and none has focused on features that characterize binding of a single ligand to multiple GPCR families. In this work, we set out to uncover and understand the binding of the same ligand to multiple GPCRs of different families. As expected only a few GPCRs share a conserved sequence motif. We observed local 3D structural similarities and local sequence similarities. We also observed that the GPCRs within the same family share similar binding pockets for the ligand. Molecular docking revealed that a ligand can bind to GPCRs of different families with different poses but similar conformations. Finally, the ligands bind to similar pockets with similar electrostatic and solvation properties and share similar residues. These findings can be exploited to improve protein function inference, drug repurposing and drug toxicity prediction, and accelerate the development of new drugs.