Small-Molecule Binders of Prokineticin Receptors Figure 1. Snake plot of hPKR1. The secondary structure is according to hPKR1 protein annotation in the UniProtKB database (entry Q8TCW9). Positions in the hPKR1 sequence differing from hPKR2 (entry Q8NFJ6) are shaded black. Conserved positions between the two subtypes are shaded white. A nine-residue hPKR1-unique insert in the N terminus is shaded gray with dashed lines. The seven transmembrane domains are denoted by roman numerals. Extracellular and intracellular sides of the membrane are labeled, as well as the N terminus (NH2) and C terminus (COOH) ends of the protein. doi:10.1371/journal.pone.0027990.g001 neous systems revealed that they bind and are activated by nanomolar concentrations of both recombinant PKs, though PK2 was shown to have a slightly higher affinity for both receptors than was PK1 [12]. Hence, in different tissues, specific signaling outcomes following receptor activation may be mediated by different ligand-receptor combinations, in accordance with the expression profile of both ligands and receptors in that tissue [13]. Activation of PKRs leads to diverse signaling outcomes, including mobilization of calcium, stimulation of phosphoinositide turnover, and activation of the p44/p42 MAPK cascade in overexpressed cells, as well as in endothelial cells naturally expressing PKRs [5,7,8,14,15] leading to the divergent functions of PKs. Differen- tial signaling capabilities of the PKRs is achieved by coupling to several different G proteins, as previously demonstrated [11]. The PKR system is involved in different pathological conditions such as heart failure, abdominal aortic aneurysm, colorectal cancer, neuroblastoma, polycystic ovary syndrome, and Kallman syndrome [16]. While Kallman syndrome is clearly linked to mutations in the PKR2 gene, it is not currently established whether the other diverse biological functions and pathological conditions are the result of a delicate balance of both PKR subtypes or depend solely on one of them. Recently, small-molecule, non-peptidic PKR antagonists have been identified through a high-throughput screening procedure [17,18,19,20]. These guanidine triazinedione-based compounds competitively inhibit calcium mobilization following PKR activa- tion by PKs in transfected cells, in the nanomolar range [17]. However, no selectivity for one of the subtypes has been observed [17]. A better understanding of the PK system can generate pharmacological tools that will affect diverse areas such as development, immune response, and endocrine function. There- fore, the molecular details underlying PK receptor interactions, both with their cognate ligands and small-molecule modulators, and with downstream signaling partners, as well as the molecular basis of differential signaling, are of great fundamental and applied interest. Structural information has been instrumental in delineating interactions and the rational development of specific inhibitors [21]. However, for many years only the X-ray structure of bovine Rhodopsin has been available [22] as the sole representative structure of the large superfamily of seven-transmembrane (7TM) domain GPCRs. In recent years crystallographic data on GPCRs has significantly grown and now includes, for example, structures of the b1 and b2- adrenergic receptors, in both active and inactive states, the agonist- and antagonist-bound A2A adenosine receptor, and the CXCR4 chemokine receptor bound to small-molecule and peptide antagonists. The new structures were reviewed in [23,24] and ligand-receptor interactions were summarized in [25]. Nevertheless, the vast number of GPCR family members still requires using computational 3D models of GPCRs for studying these receptors and for drug discovery. Different strategies for GPCR homology modeling have been developed in recent years (reviewed in [26]), and these models have been successfully used for virtual ligand screening (VLS) procedures, to identify novel GPCR binders [21]. Successful in-silico screening approaches, applied to GPCR drug discovery, include both structure-based and ligand-based tech- niques and their combinations. Molecular ligand docking is the most widely used computational structure-based approach, employed to predict whether small-molecule ligands from a PLoS ONE | www.plosone.org 2 November 2011 | Volume 6 | Issue 11 | e27990