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The IUPHAR/BPS Guide to PHARMACOLOGY in 2018: updates and expansion to encompass the new guide to IMMUNOPHARMACOLOGY - PubMed

  • ️Mon Jan 01 2018

The IUPHAR/BPS Guide to PHARMACOLOGY in 2018: updates and expansion to encompass the new guide to IMMUNOPHARMACOLOGY

Simon D Harding et al. Nucleic Acids Res. 2018.

Abstract

The IUPHAR/BPS Guide to PHARMACOLOGY (GtoPdb, www.guidetopharmacology.org) and its precursor IUPHAR-DB, have captured expert-curated interactions between targets and ligands from selected papers in pharmacology and drug discovery since 2003. This resource continues to be developed in conjunction with the International Union of Basic and Clinical Pharmacology (IUPHAR) and the British Pharmacological Society (BPS). As previously described, our unique model of content selection and quality control is based on 96 target-class subcommittees comprising 512 scientists collaborating with in-house curators. This update describes content expansion, new features and interoperability improvements introduced in the 10 releases since August 2015. Our relationship matrix now describes ∼9000 ligands, ∼15 000 binding constants, ∼6000 papers and ∼1700 human proteins. As an important addition, we also introduce our newly funded project for the Guide to IMMUNOPHARMACOLOGY (GtoImmuPdb, www.guidetoimmunopharmacology.org). This has been 'forked' from the well-established GtoPdb data model and expanded into new types of data related to the immune system and inflammatory processes. This includes new ligands, targets, pathways, cell types and diseases for which we are recruiting new IUPHAR expert committees. Designed as an immunopharmacological gateway, it also has an emphasis on potential therapeutic interventions.

© The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

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Figures

Figure 1.
Figure 1.

The hierarchical listing for the catalytic receptor families and subfamilies. (A) Shows the GtoPdb view and (B) shows it with the Guide to IMMUNOPHARMACOLOGY (GtoImmuPdb) view switched on, which highlights families containing targets of immunological relevance. A toggle button enables switching between GtoPdb and GtoImmuPdb views, the only difference being that the GtoPdb view does not have highlighting.

Figure 2.
Figure 2.

Human interaction data growth since 2013. The first (left-most) chart shows the number of human targets with curated ligand interactions while the second chart includes only those targets that are supported by quantitative data. The third chart shows the number of target data-supported interactions to approved drugs and the fourth chart shows primary targets of those drugs.

Figure 3.
Figure 3.

Category breakdown at the SID (A) and CID (B) level for GtoPdb PubChem entries. Note, in panel A, that the intersect between approved drug and immunopharmacology is derived from our curation of publications suggesting the association, but are not necessarily approved for immunological clinical indications.

Figure 4.
Figure 4.

Ligand activity chart for palosuran (ACT-058362, GtoPdb ligand ID 3516), a small molecule urotensin II receptor antagonist. Hovering the mouse over the chart on a datapoint gives the median and range if more than one value is reported for the parameters shown on the horizontal axis. Zero indicates no data are available for that parameter. In the example, the results show the IC50 value for palosuran inhibition of binding was about ∼5000-fold lower in rats compared with humans, showing a major difference between the two species.

Figure 5.
Figure 5.

Illustrating the mapping of GO parent terms to the GtoImmuPdb top-level process category, T-cell activation. Six parent terms are mapped, which encompasses 471 distinct child terms. Using GO annotations to UniProt we find that there are 172 human targets in GtoPdb with annotations to one or more of those 471 GO terms (see Table 2).

Figure 6.
Figure 6.

Displaying GtoImmuPdb data. (A) Shows the display of GtoImmuPdb cell type to target associations, here showing T cells. This layout is also used for the display of process association data. (B) Shows the display of ligand disease associations, showing the first three ligands for rheumatoid arthritis.

Figure 7.
Figure 7.

Showing the target detailed view page with immunological data highlighted. (A) Top section of the detailed view page for RIG-1 (DExD/H-Box helicase 58) with immunopharmacology content links highlighted. (B) Immunopharmacology data sections on the detailed view page. (C) Ligand binding data (from Bruton tyrosine kinase) showing the new immunological icon in blue to highlight ligands also tagged in GtoImmuPdb.

Figure 8.
Figure 8.

Schematic diagram illustrating the RDF relationship between the target 5-HT1A receptor and the ligand Ipsapirone.

Comment in

  • A new guide to immunopharmacology.

    Harding SD, Faccenda E, Southan C, Maffia P, Davies JA. Harding SD, et al. Nat Rev Immunol. 2018 Dec;18(12):729. doi: 10.1038/s41577-018-0079-2. Nat Rev Immunol. 2018. PMID: 30327546 No abstract available.

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