ß-Arrestin recruitment and G protein signaling by the atypical human chemokine decoy receptor CCX-CKR.

Chemokine receptors form a large subfamily of G protein-coupled receptors that predominantly activate heterotrimeric Gi proteins and are involved in immune cell migration. CCX-CKR is an atypical chemokine receptor with high affinity for CCL19, CCL21, and CCL25 chemokines, but is not known to activate intracellular signaling pathways. However, CCX-CKR acts as decoy receptor and efficiently internalizes these chemokines, thereby preventing their interaction with other chemokine receptors, like CCR7 and CCR9. Internalization of fluorescently labeled CCL19 correlated with ß-arrestin2-GFP translocation. Moreover, recruitment of ß-arrestins to CCX-CKR in response to CCL19, CCL21, and CCL25 was demonstrated using enzyme-fragment complementation and bioluminescence resonance energy transfer methods. To unravel why CCX-CKR is unable to activate Gi signaling, CCX-CKR chimeras were constructed by substituting its intracellular loops with the corresponding CCR7 or CCR9 domains. The signaling properties of chimeric CCX-CKR receptors were characterized using a cAMP-responsive element (CRE)-driven reporter gene assay. Unexpectedly, wild type CCX-CKR and a subset of the chimeras induced an increase in CRE activity in response to CCL19, CCL21, and CCL25 in the presence of the Gi inhibitor pertussis toxin. CCX-CKR signaling to CRE required an intact DRY motif. These data suggest that inactive Gi proteins impair CCX-CKR signaling most likely by hindering the interaction of this receptor with pertussis toxin-insensitive G proteins that transduce signaling to CRE. On the other hand, recruitment of the putative signaling scaffold ß-arrestin to CCX-CKR in response to chemokines might allow activation of yet to be identified signal transduction pathways.

Virtual fragment screening: discovery of histamine H3 receptor ligands using ligand-based and protein-based molecular fingerprints.

Virtual fragment screening (VFS) is a promising new method that uses computer models to identify small, fragment-like biologically active molecules as useful starting points for fragment-based drug discovery (FBDD). Training sets of true active and inactive fragment-like molecules to construct and validate target customized VFS methods are however lacking. We have for the first time explored the possibilities and challenges of VFS using molecular fingerprints derived from a unique set of fragment affinity data for the histamine H(3) receptor (H(3)R), a pharmaceutically relevant G protein-coupled receptor (GPCR). Optimized FLAP (Fingerprints of Ligands and Proteins) models containing essential molecular interaction fields that discriminate known H(3)R binders from inactive molecules were successfully used for the identification of new H(3)R ligands. Prospective virtual screening of 156,090 molecules yielded a high hit rate of 62% (18 of the 29 tested) experimentally confirmed novel fragment-like H(3)R ligands that offer new potential starting points for the design of H(3)R targeting drugs. The first construction and application of customized FLAP models for the discovery of fragment-like biologically active molecules demonstrates that VFS is an efficient way to explore protein-fragment interaction space in silico.

Small and colorful stones make beautiful mosaics: fragment-based chemogenomics.

Smaller stones with a wide variety of colors make a higher resolution mosaic. In much the same way, smaller chemical entities that are structurally diverse are better able to interrogate protein binding sites. This feature article describes the construction of a diverse fragment library and an analysis of the screening of six representative protein targets belonging to three diverse target classes (G protein-coupled receptors ADRB2, H1R, H3R, and H4R, the ligand-gated ion channel 5-HT3R, and the kinase PKA) using chemogenomics approaches. The integration of experimentally determined bioaffinity profiles across related and unrelated protein targets and chemogenomics analysis of fragment binding and protein structure allow the identification of: (i) unexpected similarities and differences in ligand binding properties, and (ii) subtle ligand affinity and selectivity cliffs. With a wealth of fragment screening data being generated in industry and academia, such approaches will contribute to a more detailed structural understanding of ligand-protein interactions.

Crystal structure-based virtual screening for fragment-like ligands of the human histamine H(1) receptor.

The recent crystal structure determinations of druggable class A G protein-coupled receptors (GPCRs) have opened up excellent opportunities in structure-based ligand discovery for this pharmaceutically important protein family. We have developed and validated a customized structure-based virtual fragment screening protocol against the recently determined human histamine H(1) receptor (H(1)R) crystal structure. The method combines molecular docking simulations with a protein-ligand interaction fingerprint (IFP) scoring method. The optimized in silico screening approach was successfully applied to identify a chemically diverse set of novel fragment-like (≤22 heavy atoms) H(1)R ligands with an exceptionally high hit rate of 73%. Of the 26 tested fragments, 19 compounds had affinities ranging from 10 µM to 6 nM. The current study shows the potential of in silico screening against GPCR crystal structures to explore novel, fragment-like GPCR ligand space.