Ligand-stabilized conformational states of human beta(2) adrenergic receptor: insight into G-protein-coupled receptor activation

Abstract

G-protein-coupled receptors (GPCRs) are known to exist in dynamic equilibrium between inactive- and several active-state conformations, even in the absence of a ligand. Recent experimental studies on the beta(2) adrenergic receptor (beta(2)AR) indicate that structurally different ligands with varying efficacies trigger distinct conformational changes and stabilize different receptor conformations. We have developed a computational method to study the ligand-induced rotational orientation changes in the transmembrane helices of GPCRs. This method involves a systematic spanning of the rotational orientation of the transmembrane helices (TMs) that are in the vicinity of the ligand for predicting the helical rotations that occur on ligand binding. The predicted ligand-stabilized receptor conformations are characterized by a simultaneous lowering of the ligand binding energy and a significant gain in interhelical and receptor-ligand hydrogen bonds. Using the beta(2)AR as a model, we show that the receptor conformational state depends on the structure and efficacy of the ligand for a given signaling pathway. We have studied the ligand-stabilized receptor conformations of five different ligands, a full agonist, norepinephrine; a partial agonist, salbutamol; a weak partial agonist, dopamine; a very weak agonist, catechol; and an inverse agonist, ICI-115881. The predicted ligand-stabilized receptor models correlate well with the experimentally observed conformational switches in beta(2)AR, namely, the breaking of the ionic lock between R131(3.50) at the intracellular end of TM3 (part of the DRY motif) and E268(6.30) on TM6, and the rotamer toggle switch on W286(6.48) on TM6. In agreement with trp-bimane quenching experiments, we found that norepinephrine and dopamine break the ionic lock and engage the rotamer toggle switch, whereas salbutamol, a noncatechol partial agonist only breaks the ionic lock, and the weak agonist catechol only engages the rotamer toggle switch. Norepinephrine and dopamine occupy the same binding region, between TM3, TM5, and TM6, whereas the binding site of salbutamol is shifted toward TM4. Catechol binds deeper into the protein cavity compared to the other ligands, making contact with TM5 and TM6. A part of the catechol binding site overlaps with those of dopamine and norepinephrine but not with that of salbutamol. Virtual ligand screening on 10,060 ligands on the norepinephrine-stabilized receptor conformation shows an enrichment of 38% compared to ligand unbound receptor conformation. These results show that ligand-induced conformational changes are important for developing functionally specific drugs that will stabilize a particular receptor conformation. These studies represent the first step toward a more universally applicable computational method for studying ligand efficacy and GPCR activation.

FIGURE 1

Structures of β₂AR ligands used in this study.

FIGURE 2

(a) Plot of change in ligand-binding energy for various rotation angles of helices 3, 5, and 6 with norepinephrine bound. (b) Plot of interhelical hydrogen bonds. (c) Ligand receptor hydrogen bonds.

FIGURE 3

Conformational switches in human β₂AR. (a) Ionic lock in apoprotein. (b) Breaking of ionic lock by norepinephrine. (c) W286^6.48 rotamer in the apoprotein conformation. The water mediated hydrogen bond between W286^6.48 and D79^2.50 is highlighted. (d) Toggling of the W286^6.48 rotamer by norepinephrine. (e) No change in the W286^6.48 rotamer for the salbutamol-bound conformation (not toggled).

FIGURE 4

Predicted binding site in the norepinephrine optimized β₂AR conformation. The residues within 5 Å of the ligand are shown in gray. The residues having strong interaction with the ligand are in green.

FIGURE 5

Predicted binding site in the dopamine optimized β₂AR conformation. The residues within 5 Å of the ligand are shown in gray. The residues having strong interaction with the ligand are in green.

FIGURE 6

Predicted binding site in the catechol optimized β₂AR conformation. The residues within 5 Å of the ligand are shown in gray. The residues having strong interaction with the ligand are in green.

FIGURE 7

Predicted binding site of salbutamol in the optimized β₂AR conformation. The residues within 5 Å of the ligand are shown in gray. The residues having strong interaction with the ligand are in green.

FIGURE 8

Predicted binding site of ICI-118551 in the optimized β₂AR conformation. The residues within 5 Å of the ligand are shown in gray. The residues having strong interaction with the ligand are in green.

FIGURE 9

Different steps in the receptor conformational change induced by norepinephrine. The shape of the binding cavity is represented by the blue surface. Note that in b, the shape of the binding cavity is shifted toward TM5, which makes TM3 and TM6 rotate.

FIGURE 10

Comparison among the binding sites of norepinephrine, dopamine, salbutamol, and catechol. (a) Superposition of all four binding sites. (b) Orientations of norepinephrine, salbutamol, and catechol.

FIGURE 11

Relative orientations of F282 and Y326 in the apoprotein and ligand-bound structures. (a) Apoprotein conformation. (b) Norepinephrine-stabilized state. (c) Salbutamol-stabilized state.

FIGURE 12

Location of F208 on TM5 in the binding pocket of norepinephrine, shown along with the WxP motif on TM6. Norepinephrine is shown in pink.

FIGURE 13

Binding energy landscapes (as a function of TM5 versus TM6 rotation) for two adrenergic ligands. (a) Inverse agonist ICI-118551. (b) Full agonist norepinephrine. The red regions represent unfavorable binding energies and the blue regions represent favorable binding energies. The various ligand-stabilized states are marked by dark circles. The white circles represent the possible inverse agonist stabilized states.

FIGURE 14

Distribution of adrenergic ligands in the sorted ligand list obtained from VLS. The distribution curves are shown after Gaussian smoothing and noise removal. The total number of ligands in the test database was 10,060. The optimum enrichment obtained corresponded to a 10% cutoff.