International Union of Basic and Clinical Pharmacology. LXXXVIII. G protein-coupled receptor list: recommendations for new pairings with cognate ligands.

In 2005, the International Union of Basic and Clinical Pharmacology Committee on Receptor Nomenclature and Drug Classification (NC-IUPHAR) published a catalog of all of the human gene sequences known or predicted to encode G protein-coupled receptors (GPCRs), excluding sensory receptors. This review updates the list of orphan GPCRs and describes the criteria used by NC-IUPHAR to recommend the pairing of an orphan receptor with its cognate ligand(s). The following recommendations are made for new receptor names based on 11 pairings for class A GPCRs: hydroxycarboxylic acid receptors [HCA1 (GPR81) with lactate, HCA2 (GPR109A) with 3-hydroxybutyric acid, HCA3 (GPR109B) with 3-hydroxyoctanoic acid]; lysophosphatidic acid receptors [LPA4 (GPR23), LPA5 (GPR92), LPA6 (P2Y5)]; free fatty acid receptors [FFA4 (GPR120) with omega-3 fatty acids]; chemerin receptor (CMKLR1; ChemR23) with chemerin; CXCR7 (CMKOR1) with chemokines CXCL12 (SDF-1) and CXCL11 (ITAC); succinate receptor (SUCNR1) with succinate; and oxoglutarate receptor [OXGR1 with 2-oxoglutarate]. Pairings are highlighted for an additional 30 receptors in class A where further input is needed from the scientific community to validate these findings. Fifty-seven human class A receptors (excluding pseudogenes) are still considered orphans; information has been provided where there is a significant phenotype in genetically modified animals. In class B, six pairings have been reported by a single publication, with 28 (excluding pseudogenes) still classified as orphans. Seven orphan receptors remain in class C, with one pairing described by a single paper. The objective is to stimulate research into confirming pairings of orphan receptors where there is currently limited information and to identify cognate ligands for the remaining GPCRs. Further information can be found on the IUPHAR Database website (http://www.iuphar-db.org).

IUPHAR-DB: updated database content and new features.

The International Union of Basic and Clinical Pharmacology (IUPHAR) database, IUPHAR-DB (http://www.iuphar-db.org) is an open access, online database providing detailed, expert-driven annotation of the primary literature on human and rodent receptors and other drug targets, together with the substances that act on them. The present release includes information on the products of 646 genes from four major protein classes (G protein-coupled receptors, nuclear hormone receptors, voltage- and ligand-gated ion channels) and ∼3180 bioactive molecules (endogenous ligands, licensed drugs and key pharmacological tools) that interact with them. We have described previously the classification and curation of data for small molecule ligands in the database; in this update we have annotated 366 endogenous peptide ligands with their amino acid sequences, post-translational modifications, links to precursor genes, species differences and relationships with other molecules in the database (e.g. those derived from the same precursor). We have also matched targets with their endogenous ligands (peptides and small molecules), with particular attention paid to identifying bioactive peptide ligands generated by post-translational modification of precursor proteins. Other improvements to the database include enhanced information on the clinical relevance of targets and ligands in the database, more extensive links to other databases and a pilot project for the curation of enzymes as drug targets.

How to use the IUPHAR receptor database to navigate pharmacological data.

Today's data-intensive, interdisciplinary research challenges scientists to keep up to date with key experimental techniques and tools reported in the literature. The International Union of Basic and Clinical Pharmacology Database (IUPHAR-DB) goes some way to addressing this need by providing expert-curated information sourced from primary literature and displayed in a user-friendly manner online. The database provides a channel for the IUPHAR Nomenclature Committee (NC-IUPHAR) to provide recommendations on the nomenclature of receptors and ion channels, to document their properties and the ligands that are useful for receptor characterization. Here we describe IUPHAR-DB's main features and provide examples of techniques for navigating and exploring the information. The database is freely available online at http://www.iuphar-db.org/.

Design, synthesis and biological evaluation of novel inhibitors of Trypanosoma brucei pteridine reductase 1.

Genetic studies indicate that the enzyme pteridine reductase 1 (PTR1) is essential for the survival of the protozoan parasite Trypanosoma brucei. Herein, we describe the development and optimisation of a novel series of PTR1 inhibitors, based on benzo[d]imidazol-2-amine derivatives. Data are reported on 33 compounds. This series was initially discovered by a virtual screening campaign (J. Med. Chem., 2009, 52, 4454). The inhibitors adopted an alternative binding mode to those of the natural ligands, biopterin and dihydrobiopterin, and classical inhibitors, such as methotrexate. Using both rational medicinal chemistry and structure-based approaches, we were able to derive compounds with potent activity against T. brucei PTR1 (K(i)(app)=7 nM), which had high selectivity over both human and T. brucei dihydrofolate reductase. Unfortunately, these compounds displayed weak activity against the parasites. Kinetic studies and analysis indicate that the main reason for the lack of cell potency is due to the compounds having insufficient potency against the enzyme, which can be seen from the low K(m) to K(i) ratio (K(m)=25 nM and K(i)=2.3 nM, respectively).

IUPHAR-DB: an open-access, expert-curated resource for receptor and ion channel research.

This contribution highlights efforts by the International Union of Basic and Clinical Pharmacology (IUPHAR) Nomenclature Committee (NC-IUPHAR) to classify human receptors and ion channels, to document their properties, and to recommend ligands that are useful for characterization. This effort has inspired the creation of an online database (IUPHAR-DB), which is intended to provide free information to all scientists, summarized from primary literature by experts.

IUPHAR-DB: new receptors and tools for easy searching and visualization of pharmacological data.

The IUPHAR database is an established online reference resource for several important classes of human drug targets and related proteins. As well as providing recommended nomenclature, the database integrates information on the chemical, genetic, functional and pathophysiological properties of receptors and ion channels, curated and peer-reviewed from the biomedical literature by a network of experts. The database now includes information on 616 gene products from four superfamilies in human and rodent model organisms: G protein-coupled receptors, voltage- and ligand-gated ion channels and, in a recent update, 49 nuclear hormone receptors (NHRs). New data types for NHRs include details on co-regulators, DNA binding motifs, target genes and 3D structures. Other recent developments include curation of the chemical structures of approximately 2000 ligand molecules, providing electronic descriptors, identifiers, link-outs and calculated molecular properties, all available via enhanced ligand pages. The interface now provides intelligent tools for the visualization and exploration of ligand structure-activity relationships and the structural diversity of compounds active at each target. The database is freely available at http://www.iuphar-db.org.

N-myristoyltransferase inhibitors as new leads to treat sleeping sickness.

African sleeping sickness or human African trypanosomiasis, caused by Trypanosoma brucei spp., is responsible for approximately 30,000 deaths each year. Available treatments for this disease are poor, with unacceptable efficacy and safety profiles, particularly in the late stage of the disease when the parasite has infected the central nervous system. Here we report the validation of a molecular target and the discovery of associated lead compounds with the potential to address this lack of suitable treatments. Inhibition of this target-T. brucei N-myristoyltransferase-leads to rapid killing of trypanosomes both in vitro and in vivo and cures trypanosomiasis in mice. These high-affinity inhibitors bind into the peptide substrate pocket of the enzyme and inhibit protein N-myristoylation in trypanosomes. The compounds identified have promising pharmaceutical properties and represent an opportunity to develop oral drugs to treat this devastating disease. Our studies validate T. brucei N-myristoyltransferase as a promising therapeutic target for human African trypanosomiasis.

One scaffold, three binding modes: novel and selective pteridine reductase 1 inhibitors derived from fragment hits discovered by virtual screening.

The enzyme pteridine reductase 1 (PTR1) is a potential target for new compounds to treat human African trypanosomiasis. A virtual screening campaign for fragments inhibiting PTR1 was carried out. Two novel chemical series were identified containing aminobenzothiazole and aminobenzimidazole scaffolds, respectively. One of the hits (2-amino-6-chloro-benzimidazole) was subjected to crystal structure analysis and a high resolution crystal structure in complex with PTR1 was obtained, confirming the predicted binding mode. However, the crystal structures of two analogues (2-amino-benzimidazole and 1-(3,4-dichloro-benzyl)-2-amino-benzimidazole) in complex with PTR1 revealed two alternative binding modes. In these complexes, previously unobserved protein movements and water-mediated protein-ligand contacts occurred, which prohibited a correct prediction of the binding modes. On the basis of the alternative binding mode of 1-(3,4-dichloro-benzyl)-2-amino-benzimidazole, derivatives were designed and selective PTR1 inhibitors with low nanomolar potency and favorable physicochemical properties were obtained.

Knowledge-based interaction fingerprint scoring: a simple method for improving the effectiveness of fast scoring functions.

A new method for the postprocessing of docking outputs has been developed, based on encoding putative 3D binding modes (docking solutions) as ligand-protein interactions into simple bit strings, a method analogous to the structural interaction fingerprint. Instead of employing traditional scoring functions, the method uses a series of new, knowledge-based scores derived from the similarity of the bit strings for each docking solution to that of a known reference binding mode. A GOLD docking study was carried out using the Bissantz estrogen receptor antagonist set along with the new scoring method. Superior recovery rates, with up to 2-fold enrichments, were observed when the new knowledge-based scoring was compared to the GOLD fitness score. In addition, top ranking sets of molecules (actives and potential actives or decoys) were structurally diverse with low molecular weights and structural complexities. Principal component analysis and clustering of the fingerprints permits the easy separation of active from inactive binding modes and the visualization of diverse binding modes.

Retrospective docking study of PDE4B ligands and an analysis of the behavior of selected scoring functions.

Scoring forms a major obstacle to the success of any docking study. In general, fast scoring functions perform poorly when used to determine the relative affinity of ligands for their receptors. In this study, the objective was not to rank compounds with confidence but simply to identify a scoring method which could provide a 4-fold hit enrichment in a screening sample over random selection. To this end, LigandFit, a fast shape matching docking algorithm, was used to dock a variety of known inhibitors of type 4 phosphodiesterase (PDE4B) into its binding site determined crystallographically for a series of pyrazolopyridine inhibitors. The success of identifying good poses with this technique was explored through RMSD comparisons with 19 known inhibitors for which crystallographic structures were available. The effectiveness of five scoring functions (PMF, JAIN, PLP2, LigScore2, and DockScore) was then evaluated through consideration of the success in enriching the top ranked fractions of nine artificial databases, constructed by seeding 1980 inactive ligands (pIC50 < 5) with 20 randomly selected inhibitors (pIC50 > 6.5). PMF and JAIN showed high average enrichment factors (greater than 4 times) in the top 5-10% of the ranked databases. Rank-based consensus scoring was then investigated, and the rational combination of 3 scoring functions resulted in more robust scoring schemes with (cScore)-DPmJ (consensus score of DockScore, PMF, and JAIN) and (cScore)-PPmJ (PLP2, PMF, and JAIN) yielding particularly good results. These cScores are believed to be of greater general application. Finally, the analysis of the behavior of the scoring functions across different chemotypes uncovered the inherent bias of the docking and scoring toward compounds in the same structural family as that employed for the crystal structure, suggesting the need to use multiple versions of the binding site for more successful virtual screening strategies.