ORF74 recruits β-arrestin1 and β-arrestin2 in response to human chemokines.

<p>HEK293T cells co-expressing ORF74-Rluc8 and β-arrestin1-eYFP (A, C) or β-arrestin2-eYFP (B, D) were stimulated with increasing concentrations of CXCL1 (open squares), CXCL8 (filled squares) or CXCL10 (open circles) (A, B) or co-stimulated with CXCL1 and CXCL10 (C, D). β-arrestin recruitment to the receptor was measured as an increase in BRET ratio (BRETr). Data are shown as fold over basal and represent the mean of pooled data from at least three independent experiments each performed in triplicate. Error bars indicate SEM values. Significant differences between vehicle and chemokine-stimulation were determined by one-way ANOVA followed by a Bonferroni test (**** p ≤ 0.0001). NS = not significant.</p

ORF74 trafficking is β-arrestin-dependent.

<p>HEK293T cells were transiently transfected with ORF74-Rluc8 and Venus-K-Ras (plasma membrane marker) (A, C) or Venus-Rab5a (early endosome marker) (B, D) in combination with control (Contr) or β-arrestin1/2 (βarr1/2) siRNA. (A, B) Downregulation of β-arrestin1/2 levels was determined by immunoblotting. STAT3 levels were determined as loading control. (C, D) Cells were stimulated with CXCL1 for indicated time and BRET was measured. Data are shown as the mean of pooled data from three independent experiments each performed in triplicate. Data is presented as fold over vehicle-stimulated cells (dotted line) and error bars indicate SEM values. Statistical differences between the area under the curve of cells treated with control or β-arrestin1/2 siRNA (baseline = 1) were determined by a Student t test (** p ≤ 0.01).</p

Characterization and β-arrestin recruitment to ORF74-ST/A.

<p>(A) Schematic representation of the C-tail of ORF74, starting at the conserved VPxxY-motif in TM7. Serine and threonine residues mutated to alanine in ORF74-ST/A are shown in bold brown. The location of TM7 (delineated) and helix 8 (marked red) are based on the CCR5 crystal structure (PDB-code 4MBS) [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0124486#pone.0124486.ref035" target="_blank">35</a>]. (B-F) HEK293T cells were transiently transfected with WT-ORF74 (WT) (B-E) or ORF74-ST/A (ST/A) (B-F) or empty vector DNA (mock-transfected) (B, E). (B) Relative receptor expression at the cell surface was determined by ELISA. Binding of ¹²⁵I-CXCL10 (C) or ¹²⁵I-CXCL8 (D) to intact HEK293T cells was measured in the presence of increasing concentrations unlabeled homologous chemokines. Constitutive (E) or chemokine-induced (F) activation of PLC was determined by measuring InsP accumulation. (G) HEK293T cells expressing ORF74-Rluc8 (WT) or ORF74-ST/A-Rluc8 (ST/A) in combination with β-arrestin1-eYFP (βarr1) or β-arrestin2-eYFP (βarr2) were vehicle-stimulated (white bars) or stimulated with 300 nM CXCL1 (black bars) before measurement of BRET. Data are presented as fold over mock-transfected cells (dotted line) (B, E), percentage of specific binding (C, D) or fold over basal (F, G). All data are represented as the mean of pooled data from at least three independent experiments each performed in triplicate and error bars indicate SEM values. Statistical differences of cell surface expression (B) or constitutive PLC activation (E) between WT-ORF74 and ORF74-ST/A or between vehicle- and corresponding CXCL1-treated cells (G) were determined by a Student t test (**** p ≤ 0.0001, ** p ≤ 0.01, * p ≤ 0.05). NS = not significant.</p

Serines and threonines at the distal end of the C-tail are essential for β-arrestin recruitment.

<p>(A) Schematic representation of the C-tail of ORF74, starting at the conserved VPxxY-motif in TM7. Serine and threonine residues mutated to alanine are shown in bold brown and clustered to indicate the different ORF74-ST/A mutants (ST/A1, ST/A2 and ST/A3). The location of TM7 (delineated) and helix 8 (marked red) are based on the CCR5 crystal structure (PDB-code 4MBS) [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0124486#pone.0124486.ref035" target="_blank">35</a>]. (B) HEK293T cells were transiently transfected with ORF74-Rluc8 (WT), ORF74-ST/A1-Rluc8 (ST/A1), ORF74-ST/A2-Rluc8 (ST/A2) or ORF74-ST/A3-Rluc8 (ST/A3) or empty vector DNA (mock-transfected) and receptor cell surface expression was determined by ELISA. (C-F) HEK293T cells expressing ORF74-Rluc8 (WT) or one of the Rluc8-tagged ORF74-ST/A mutants in combination with β-arrestin1-eYFP (C, E) or β-arrestin2-eYFP (D, F) were treated with increasing concentrations CXCL1 (C, D) or were vehicle-stimulated (white bars) or stimulated with 300 nM CXCL1 (black bars) (E, F) before measurement of BRET. Data are shown as the mean of pooled data from three independent experiments each performed in triplicate. Data is presented as fold over mock-transfected cells (dotted line) (B) or fold over basal (C-F) and error bars indicate SEM values. Statistical differences between ORF74 WT and mutant cell surface expression (B) or difference between vehicle- and corresponding CXCL1-treated cells (E, F) were determined by one-way ANOVA followed by a Bonferroni test (B) or a Student t test (E, F), respectively (**** p ≤ 0.0001, ** p ≤ 0.01). NS = not significant.</p

ORF74 internalizes and traffics via early, recycling and late endosomes.

<p>HEK293T cells were transiently transfected with ORF74-Rluc8 (WT) (A-D) or ORF74-ST/A2-Rluc8 (ST/A2) (E-H) in combination with Venus-K-Ras (plasma membrane marker) (A, E), Venus-Rab5a (early endosome marker) (B, F), Venus-Rab7a (late endosome/lysosome marker) (C, G) or Venus-Rab11 (recycling endosome marker) (D, H) and stimulated with CXCL1, CXCL8 or CXCL10 for indicated time and BRET was measured. Data are shown as the mean of pooled data from three independent experiments each performed in triplicate. Data is presented as fold over vehicle-stimulated cells (dotted line) and error bars indicate SEM values. Statistical differences between the area under the curve of vehicle- and corresponding CXCL1-, CXCL8- or CXCL10-treated cells (baseline = 1) were determined by one-way ANOVA followed by a Bonferroni test (**** p ≤ 0.0001, *** p≤ 0.001, ** p ≤ 0.01, * p ≤ 0.05). NS = not significant.</p

Characterization and β-arrestin recruitment to ORF74-R^3.50A.

<p>(A, B) HEK293T cells were transiently transfected with WT-ORF74 (WT), ORF74-R^3.50A (R^3.50A) or empty vector DNA (mock-transfected). Relative receptor expression at the cell surface was determined by ELISA (A) and constitutive activation of PLC was determined by measuring InsP accumulation (B). Data are presented as fold over mock-transfected cells (dotted line). (C, D) HEK293T cells expressing ORF74-Rluc8 (WT) (filled circles) or ORF74-R^3.50A-Rluc8 (R^3.50A) (open squares) in combination with β-arrestin1-eYFP (C) or β-arrestin2-eYFP (D) were stimulated with increasing concentrations of CXCL1. Data are shown as fold over basal. All data are represented as the mean of pooled data from at least three independent experiments each performed in triplicate and error bars indicate SEM values. Statistical differences of cell surface expression (A) or constitutive PLC activation (B) between WT-ORF74 and ORF74-R^3.50A were determined by a Student t test (**** p ≤ 0.0001, *** p ≤ 0.001).</p

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 <i>and</i> 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 <i>molecular fingerprints</i> derived from a unique set of fragment affinity data for the histamine H₃ receptor (H₃R), a pharmaceutically relevant G protein-coupled receptor (GPCR). Optimized FLAP (Fingerprints of Ligands and Proteins) models containing essential molecular interaction fields that discriminate known H₃R binders from inactive molecules were successfully used for the identification of new H₃R 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 H₃R ligands that offer new potential starting points for the design of H₃R 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 <i>in silico</i>

Discovery of Novel <i>Trypanosoma brucei</i> Phosphodiesterase B1 Inhibitors by Virtual Screening against the Unliganded TbrPDEB1 Crystal Structure

<i>Trypanosoma brucei</i> cyclic nucleotide phosphodiesterase B1 (TbrPDEB1) and TbrPDEB2 have recently been validated as new therapeutic targets for human African trypanosomiasis by both genetic and pharmacological means. In this study we report the crystal structure of the catalytic domain of the unliganded TbrPDEB1 and its use for the in silico screening for new TbrPDEB1 inhibitors with novel scaffolds. The TbrPDEB1 crystal structure shows the characteristic folds of human PDE enzymes but also contains the parasite-specific P-pocket found in the structures of <i>Leishmania major</i> PDEB1 and <i>Trypanosoma cruzi</i> PDEC. The unliganded TbrPDEB1 X-ray structure was subjected to a structure-based in silico screening approach that combines molecular docking simulations with a protein–ligand interaction fingerprint (IFP) scoring method. This approach identified six novel TbrPDEB1 inhibitors with IC₅₀ values of 10–80 μM, which may be further optimized as potential selective TbrPDEB inhibitors

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 <i>and</i> 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 <i>molecular fingerprints</i> derived from a unique set of fragment affinity data for the histamine H₃ receptor (H₃R), a pharmaceutically relevant G protein-coupled receptor (GPCR). Optimized FLAP (Fingerprints of Ligands and Proteins) models containing essential molecular interaction fields that discriminate known H₃R binders from inactive molecules were successfully used for the identification of new H₃R 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 H₃R ligands that offer new potential starting points for the design of H₃R 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 <i>in silico</i>

Crystal Structure-Based Virtual Screening for Fragment-like Ligands of the Human Histamine H₁ 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 H₁ receptor (H₁R) 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) H₁R 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