A recently published letter from scientists at Boehringer Ingelheim nicely summarizes recent advances in our understanding of G protein-coupled receptor (GPCR) structure and function. X-ray structures of the inactive forms of bovine rhodopsin (2000), β2 adrenergic receptor (2007 – with antibody and as a T4-lysozyme fusion), A2a adenosine receptor (2008), CXCR4 chemokine receptor (2010), and dopamine D3 receptor (2010) have all been published and despite low sequence homology all of these were shown to have transmembrane (TM) regions with high levels of 3D structural similarity. The main structural differences in proximity to the ligand binding sites were noted in extracellular loop regions and modeling these motifs (as well as the ligand binding mode) has proved to be challenging. With no reliable template available for homology modeling of the active states, the recent publication of the crystal structure of long acting agonist, BI-167107 (in yellow below), to β2 in what appears to be an activated form, is of particular note. Surprisingly, the ligand binding site in this structure is very similar to that modeled for a related agonist bound to an inactive form (in green below).
The authors postulate the following on the basis of these findings:
- Inactive structures of GPCRs are sufficiently good templates for activated state models (also see recent structures of β1 and β2 with agonists bound in the inactive state).
- The molecular switching between inactive and active receptor forms appears to be controlled by significant residue movements (and disruption of a hydrophobic network) one turn beyond the so-called “toggle switch” (W286 in β2). This information could enable better modeling of ligand-induced activation.
- The high similarity of binding sites in inactive and active receptors may make in silico discrimination between agonists and antagonists extremely difficult, if not impossible.
However, they emphasize the importance of obtaining additional structural data for activated GPCR complexes in order to establish the generality of these early observations and to elucidate the best methods for incorporating these findings into computational approaches to predicting ligand activity. It’ll be interesting to see how this area develops as additional structures become available.