New ligands for everyone's favorite protein
A landmark event in structural biology and pharmacology occurred in 2007 when the structure of the ß2-adrenergic receptor was solved using xray crystallography by Brian Kobilka's and Raymond Stevens's groups at Stanford and Scripps respectively. The structure was co-crystallized with the inverse agonist carazolol. Until then the only GPCR structure available was that of rhodopsin and all homology models of GPCR were based on this structure. The availability of this new high resolution structure opened new avenues for structure-based GPCR ligand discovery.
The ß2 binding pocket is especially suited for drug design since it is tight, narrow and lined with mostly hydrophobic residues with polar residues well-separated. Two crucial residues, an Asp and a Ser bind to the ubiquitous charged amino nitrogen present in most catecholamines and the aromatic section of the molecule docks deep into the hydrophobic pocket. These particular features also make computational docking more facile; a mix of polar and non-polar features with bridging waters can make docking and scoring more challenging.
Since the ß2 structure has been published, attempts are being made to use it as a template to build homology models of other GPCRs. A couple of months back I described an interesting proof-of-principle paper by Stefano Costanzi that sought to investigate how well a homology model based on the ß2 would perform. In that study carazolol itself was used as a ligand for docking into the homology model. Comparison with the original crystal structure revealed that while the ligand docked more or less satisfactorily, an important deviation in its orientation could be explained by a counterintuitive orientation of a Phe residue in the binding site. The study indicated that the devil is in the details when one is considering homology models.
However, finding ligands for the ß2 itself is also an important and interesting endeavor. Virtual screening could help in such studies. To this end Brian Shoichet, Brian Kobilka and their group have used the DOCK program to virtually screen one million lead-like ligands from their ZINC database against the ß2. Out of the 1 million ranked poses, they chose and clustered the top 500 compounds (0.05% of the database) into 25 unique chemotypes, a choice also guided by visual inspection of the protein-ligand interactions and commercial availability. They then tested these 25 compounds against the ß2 and found 6 compounds with IC50s better than 4 µM. One of these compounds with an IC50 of 9 nM is perhaps the most potent inverse agonist of the ß2 known. The binding poses revealed substantial overlap of similar functional groups with the carazolol structure. Two compounds turned out to have novel chemotypes and bore very little similarity with known ß2 ligands. A negative test was also run where a known predicted binder was chemical modified so that it would not bind.
Interestingly all the compounds found were inverse agonists. The ZINC library is somewhat biased against aminergic ligands as is most of chemical space. The catecholamine scaffold is one of the favourite scaffolds in medicinal chemistry. However, subtle difference in protein structure can sometimes turn an inverse agonist into an agonist. In this case, small changes in the orientation of the crucial Ser residue near the mouth of the binding pocket. In a past study for instance, slightly changing the rotameric features of the Ser residue thus resulting in a different orientation of the hydroxyl was sufficient to retrieve agonists.
The study thus shows the value of virtual screening in the discovery of new ß2 ligands and indicates the effect of library bias and protein structure on such ligand discovery. Many factors can contribute to the success or failure of such a search; nature is a multi-armed demon.
Reference:
Kolb, P., Rosenbaum, D., Irwin, J., Fung, J., Kobilka, B., & Shoichet, B. (2009). Structure-based discovery of ß2-adrenergic receptor ligands Proceedings of the National Academy of Sciences DOI: 10.1073/pnas.0812657106
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