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

By S. Harding, J. Sharman, E. Faccenda, C. Southan, Adam J Pawson, Sam M. Ireland, A. Gray, Liam Bruce, Stephen P. H. Alexander, Stephen Anderton and 8 more. Nucleic Acids Res., 2017

1,659 citations recorded by the source corpus.

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.

Subfields: Computational Theory and Mathematics, Oncology, Pharmacology

View Paper: https://www.semanticscholar.org/paper/ab723f82e9410a3d934a5dded95a898b983a497a

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In Computational Theory and Mathematics

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Citations in the corpus

• The reactome pathway knowledgebase (2019, background): “As shown for the antithrombotic chemical apixaban in Figure 1A, each chemical drug instance is mapped to its counterpart in IUPHAR (8) and if one is available in ChEBI (9) and for additional pharmacological data.”
• SingleCellSignalR: inference of intercellular networks from single-cell transcriptomics (2019, methodology): “Accordingly, we compiled the content of existing databases that contain such LR pairs: FANTOM5 (6), HPRD (27), HPMR (28), the IUPHAR / BPS Guide to Pharmacology (29) and UniProtKB / Swissprot (30) annotations related to families of ligands or receptors covered in the previous databases.”
• GPCRdb in 2018: adding GPCR structure models and ligands (2017, background): “Current data ranges all 398 human non-olfactory GPCRs and 16 G proteins, over 14 000 species orthologues, 30 328 binding site mutations, all 218 experimental structures, and 10 059 extracted ligand interactions.”
• Discovery of Human Signaling Systems: Pairing Peptides to G Protein-Coupled Receptors (2019, methodology): “1; released 05/03/2018) (Harding et al., 2018) using custom Python scripts.”