Whereas drugs are intended to be selective, at least some bind to several physiologic targets, explaining both side effects and efficacy. As many drug-target combinations exist, it would be useful to explore possible interactions computationally. Here, we compared 3,665 FDA-approved and investigational drugs against hundreds of targets, defining each target by its ligands. Chemical similarities between drugs and ligand sets predicted thousands of unanticipated associations. Thirty were tested experimentally, including the antagonism of the β1 receptor by the transporter inhibitor Prozac, the inhibition of the 5-HT transporter by the ion channel drug Vadilex, and antagonism of the histamine H4 receptor by the enzyme inhibitor Rescriptor. Overall, 23 new drug-target associations were confirmed, five of which were potent (< 100 nM). The physiological relevance of one such, the drug DMT on serotonergic receptors, was confirmed in a knock-out mouse. The chemical similarity approach is systematic and comprehensive, and may suggest side-effects and new indications for many drugs.

The clinical efficacy and safety of a drug is determined by its activity profile across multiple proteins in the proteome. However, designing drugs with a specific multi-target profile is both complex and difficult. Therefore methods to rationally design drugs a priori against profiles of multiple proteins would have immense value in drug discovery. We describe a new approach for the automated design of ligands against profiles of multiple drug targets. The method is demonstrated by the evolution of an approved acetylcholinesterase inhibitor drug into brain penetrable ligands with either specific polypharmacology or exquisite selectivity profiles for G-protein coupled receptors. Overall, 800 ligand-target predictions of prospectively designed ligands were tested experimentally, of which 75% were confirmed correct. We also demonstrate target engagement in vivo. The approach can be a useful source of drug leads where multi-target profiles are required to achieve either selectivity over other drug targets or a desired polypharmacology.

Elucidating the key signal transduction pathways essential for both antipsychotic efficacy and side-effect profiles is essential for developing safer and more effective therapies. Recent work has highlighted noncanonical modes of dopamine D 2 receptor (D 2 R) signaling via β-arrestins as being important for the therapeutic actions of both antipsychotic and antimanic agents. We thus sought to create unique D 2 R agonists that display signaling bias via β-arrestinergic signaling. Through a robust diversity-oriented modification of the scaffold represented by aripiprazole (1), we discovered UNC9975 (2), UNC0006 (3), and UNC9994 (4) as unprecedented β-arrestin-biased D 2 R ligands. These compounds also represent unprecedented β-arrestin-biased ligands for a G i -coupled G proteincoupled receptor (GPCR). Significantly, UNC9975, UNC0006, and UNC9994 are simultaneously antagonists of G i -regulated cAMP production and partial agonists for D 2 R/β-arrestin-2 interactions. Importantly, UNC9975 displayed potent antipsychotic-like activity without inducing motoric side effects in inbred C57BL/6 mice in vivo. Genetic deletion of β-arrestin-2 simultaneously attenuated the antipsychotic actions of UNC9975 and transformed it into a typical antipsychotic drug with a high propensity to induce catalepsy. Similarly, the antipsychotic-like activity displayed by UNC9994, an extremely β-arrestin-biased D 2 R agonist, in wild-type mice was completely abolished in β-arrestin-2 knockout mice. Taken together, our results suggest that β-arrestin signaling and recruitment can be simultaneously a significant contributor to antipsychotic efficacy and protective against motoric side effects. These functionally selective, β-arrestin-biased D 2 R ligands represent valuable chemical probes for further investigations of D 2 R signaling in health and disease.functional selectivity | ligand bias G protein-coupled receptors (GPCRs) signal not only via canonical pathways involving heterotrimeric large G proteins, but also via noncanonical G protein-independent interactions with other signaling proteins including, most prominently, β-arrestins (1-4). The process by which GPCR ligands differentially modulate canonical and noncanonical signal transduction pathways is a phenomenon known as "functional selectivity" (5, 6). Such functionally selective ligands preferentially engage either canonical or noncanonical GPCR pathways (7,8). Clearly, the discovery of ligands with discrete functional selectivity profiles will be extremely useful for elucidating the key signal transduction pathways essential for both the therapeutic actions and the side effects of drugs (6). Understanding which signaling pathways contribute to antipsychotic efficacy and side effects, for instance, will in turn enable the design of better antipsychotic drug candidates and, ultimately, lead to safer and more effective therapies for patients. However, only a small number of functionally selective GPCR ligands have been reported to date (5-9). In addition to the paucity of such ligands,...

G-Protein coupled receptors (GPCRs) are intensely studied as drug targets and for their role in signaling. With the determination of the first crystal structures, interest in structure-based ligand discovery has increased. Unfortunately, most GPCRs lack experimental structures. The determination of the D3 receptor structure, and a community challenge to predict it, enabled a fully prospective comparison of ligand discovery from a modeled structure versus that of the subsequently released crystal structure. Over 3.3 million molecules were docked against a homology model, and 26 of the highest ranking were tested for binding. Six had affinities from 0.2 to 3.1μM. Subsequently, the crystal structure was released and the docking screen repeated. Of the 25 compounds selected, five had affinities from 0.3 to 3.0μM. One of the novel ligands from the homology model screen was optimized for affinity to 81nM. The feasibility of docking screens against modeled GPCRs more generally is considered.

We report the discovery, tissue distribution and pharmacological characterization of a novel receptor, which we have named H4. Like the three histamine receptors reported previously (H1, H2, and H3), the H4 receptor is a G protein-coupled receptor and is most closely related to the H3 receptor, sharing 58% identity in the transmembrane regions. The gene encoding the H4 receptor was discovered initially in a search of the GenBank databases as sequence fragments retrieved in a partially sequenced human genomic contig mapped to chromosome 18. These sequences were used to retrieve a partial cDNA clone and, in combination with genomic fragments, were used to determine the full-length open reading frame of 390 amino acids. Northern analysis revealed a 3.0-kb transcript in rat testis and intestine. Radioligand binding studies indicated that the H4 receptor has a unique pharmacology and binds [(3)H]histamine (K(d) = 44 nM) and [(3)H]pyrilamine (K(d) = 32 nM) and several psychoactive compounds (amitriptyline, chlorpromazine, cyproheptadine, mianserin) with moderate affinity (K(i) range of 33-750 nM). Additionally, histamine induced a rapid internalization of HA-tagged H4 receptors in transfected human embryonic kidney 293 cells.