Mapping Functional Group Requirements of Ligands at the Occluded Binding Pocket of β2-Adrenergic G-Protein Coupled Receptor using Site Identification by Ligand Competitive Saturation Simulations

Abstract

β2-adrenergic G-protein coupled receptor (B2AR) is an important therapeutic target for obstructive pulmonary diseases. The ligand binding pocket (LBP) in this and a number of other drug targets is deeply buried, offering significant challenges to computer-aided drug design approaches. Site Identification by Ligand Competitive Saturation (SILCS) is an in-situ fragment sampling method that maps the spatial distributions and approximate affinities of chemically diverse functional groups on a macromolecule through molecular dynamics (MD) simulations of the macromolecule in an aqueous solution of small molecules. Notable is the simultaneous inclusion of waters and protein flexibility such that the method accounts for ligand and binding site desolvation when mapping the affinity patterns of the different fragments (FragMaps). To probe an occluded LBP, a novel Grand-Canonical Monte-Carlo/MD (GCMC/MD) strategy is extended to the SILCS methodology. GCMC drives the small molecules and explicit solvent sampling of the occluded pocket, and the MD allows for the conformational sampling of the macromolecule in the presence of the small molecules, which is useful in identifying regions in the LBP that were inaccesible in the crystal conformation. Good agreement is obtained between the FragMaps and the positions of chemically similar functional groups of ligands observed in the crystal structures of B2AR. Ligand grid free energy (LGFE), an approximate estimation of binding affinity derived from FragMaps had good correlation with the experimentally measured binding affinity for diverse ligands. Clear differences were found in the FragMaps at the LBP across the activated and inactivated conformations of the B2AR. These differences were useful in determining the nature of a ligand that would preferentially bind to one of the two states and consequently guide drug design.