Poster GtoPdb Pharmacology 2017
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Poster describing the IUPHAR/BPS Guide to PHARMACOLOGY (GtoPdb) in 2017, for Pharmacology 2017 in London Dec 11th-13th.
![3. Searching for targets and ligands
2. Current database content
8. References
1 Centre for Integrative Physiology, University of Edinburgh, Edinburgh, UK. 2 School of Life Sciences, University of Nottingham Medical School, Nottingham, UK. 3 Experimental
Medicine and Immunotherapeutics, University of Cambridge, Cambridge. 4 Spedding Research Solutions SAS, Paris, France. * The International Union of Basic and Clinical
Pharmacology Committee on Receptor Nomenclature and Drug Classification.
www.guidetopharmacology.org enquiries@guidetopharmacology.org @GuidetoPHARM
The IUPHAR/BPS Guide to PHARMACOLOGY
in 2017: new features and updates
Supported by:
We especially thank all contributors, collaborators and NC-IUPHAR members
1. Introduction
The IUPHAR/BPS Guide to PHARMACOLOGY (GtoPdb) is an open, expert-driven
database of pharmacological targets and the substances that act on them [1]. It is a
joint initiative between the British Pharmacological Society (BPS) and the International
Union of Basic and Clinical Pharmacology (IUPHAR), which aims to cover the human
targets of licensed drugs and other likely targets of future therapeutics.
The information is presented at two levels:
1. Overviews of the key properties, selective ligands and further reading for a wide
range of human biological targets, which form the basis for the Concise Guide to
PHARMACOLOGY (CGTP) [2].
2. Detailed pharmacological, functional and clinical information for a subset of
important targets.
All data are manually curated from the primary literature and reviewed by an
international network of >500 experts in 96 subcommittees of the IUPHAR Committee
on Receptor Nomenclature and Drug Classification (NC-IUPHAR).
~1,700 established or potential data-supported drug targets
~1,100 additional related proteins
• G protein-coupled receptors (GPCRs), including Orphan GPCRs & Adhesion GPCRs
• Voltage-gated ion channels (VGICs)
• Ligand-gated ion channels (LGICs)
• Other ion channels
• Nuclear hormone receptors (NHRs)
• Enzymes, including kinases & proteases
• Catalytic receptors
• Transporters
~9,000 ligands
• Approved drugs
• Experimental compounds & labelled ligands
• Hormones, neurotransmitters, metabolites
• Endogenous and synthetic peptides
• Antibodies
• Natural products
• Inorganic chemicals
Various search tools are available to find targets and ligands by keyword (Fig. 2),
identifier, reference, chemical structure (Fig. 3), or protein sequence (Fig. 4).
Figure 1. Examples of various kinase database tables
1. Harding SD, et al. (2018) The IUPHAR/BPS Guide to PHARMACOLOGY in 2018: Updates and expansion to encompass
the new Guide to IMMUNOPHARMACOLOGY. Nucl. Acids Res. 46 (Database Issue). doi: 10.1093/nar/gkx1121.
2. Alexander SPH, et al. (2017) The Concise Guide to PHARMACOLOGY 2017/18. Br J Pharmacol. 174 (Suppl 1): S1-
S446.
3. Bento AP, et al. (2014). The ChEMBL bioactivity database: an update. Nucl. Acids Res. 42 (Database Issue): D1083-
D1090.
4. Rose PW, et al. (2017) The RCSB protein data bank: integrative view of protein, gene and 3D structural information. Nucl
Acids Res, 45 (Database Issue), D271-D281.Figure 4. BLAST sequence search for targets
GtoPdb is an ELIXIR UK node resource
Figure 2. Target name search
with autocomplete function
Figure 3. Chemical structure search
4. Navigating target and ligand families
Targets are organised by class, which can be browsed as a tree with families and
subfamilies (Fig. 5). Ligands have also recently been organised into related families and
groups (Fig. 6). Each family/group page lists summary information for the ligands, with
links to more detailed pages (Fig. 7).
Figure 5. Target families
Joanna L. Sharman1, Elena Faccenda1, Simon D. Harding1, Adam J. Pawson1, Christopher Southan1, Stephen P.H.
Alexander2, Anthony P. Davenport3, Michael Spedding4, Jamie A. Davies1 and NC-IUPHAR*
6. SynPHARM database of ligand binding sequences
SynPHARM is a tool for finding ligand binding sequences which can be engineered into
synthetic proteins to confer drugability. It combines pharmacological parameters from
GtoPdb with ligand binding data from the RCSB Protein Data Bank [4] (Fig. 9).
It is freely available at http://synpharm.guidetopharmacology.org.
Figure 9. (A/B) The location of a ligand binding sequence is shown in green on a protein
structure. (C) A residue distance matrix indicating ‘globularity’ of the sequence. The
dotted line represents the binding sequence – the greener the area is the more
compact the sequence.
A B C
5. Comparing ligand affinity across species
Ligand activity graphs provide a quick way to visualise affinity at different targets and
across species. Box plots (Fig. 8A) summarise standardised activity data from GtoPdb
and ChEMBL [3]. Individual data points, assay details and references are provided in an
accompanying table (Fig. 8B).
Figure 8. Chart and table showing palosuran activity at human and rat UT receptors
Figure 1. Examples of data types for NHRs
Figure 6. Ligand families
Figure 7. A ligand family summary page
A B
7. Downloading data
Data are available to download in various formats:
• Lists of targets, ligands and interactions in CSV format
• REST web services for computational access to data in JSON format
• SQL database dump files
• Interaction data are now available in RDF format for semantic integration](https://image.slidesharecdn.com/postergtopdbpharmacology2017-171128143632/75/Poster-GtoPdb-Pharmacology-2017-1-2048.jpg)
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Poster GtoPdb Pharmacology 2017
- 1. 3. Searching for targets and ligands 2. Current database content 8. References 1 Centre for Integrative Physiology, University of Edinburgh, Edinburgh, UK. 2 School of Life Sciences, University of Nottingham Medical School, Nottingham, UK. 3 Experimental Medicine and Immunotherapeutics, University of Cambridge, Cambridge. 4 Spedding Research Solutions SAS, Paris, France. * The International Union of Basic and Clinical Pharmacology Committee on Receptor Nomenclature and Drug Classification. www.guidetopharmacology.org enquiries@guidetopharmacology.org @GuidetoPHARM The IUPHAR/BPS Guide to PHARMACOLOGY in 2017: new features and updates Supported by: We especially thank all contributors, collaborators and NC-IUPHAR members 1. Introduction The IUPHAR/BPS Guide to PHARMACOLOGY (GtoPdb) is an open, expert-driven database of pharmacological targets and the substances that act on them [1]. It is a joint initiative between the British Pharmacological Society (BPS) and the International Union of Basic and Clinical Pharmacology (IUPHAR), which aims to cover the human targets of licensed drugs and other likely targets of future therapeutics. The information is presented at two levels: 1. Overviews of the key properties, selective ligands and further reading for a wide range of human biological targets, which form the basis for the Concise Guide to PHARMACOLOGY (CGTP) [2]. 2. Detailed pharmacological, functional and clinical information for a subset of important targets. All data are manually curated from the primary literature and reviewed by an international network of >500 experts in 96 subcommittees of the IUPHAR Committee on Receptor Nomenclature and Drug Classification (NC-IUPHAR). ~1,700 established or potential data-supported drug targets ~1,100 additional related proteins • G protein-coupled receptors (GPCRs), including Orphan GPCRs & Adhesion GPCRs • Voltage-gated ion channels (VGICs) • Ligand-gated ion channels (LGICs) • Other ion channels • Nuclear hormone receptors (NHRs) • Enzymes, including kinases & proteases • Catalytic receptors • Transporters ~9,000 ligands • Approved drugs • Experimental compounds & labelled ligands • Hormones, neurotransmitters, metabolites • Endogenous and synthetic peptides • Antibodies • Natural products • Inorganic chemicals Various search tools are available to find targets and ligands by keyword (Fig. 2), identifier, reference, chemical structure (Fig. 3), or protein sequence (Fig. 4). Figure 1. Examples of various kinase database tables 1. Harding SD, et al. (2018) The IUPHAR/BPS Guide to PHARMACOLOGY in 2018: Updates and expansion to encompass the new Guide to IMMUNOPHARMACOLOGY. Nucl. Acids Res. 46 (Database Issue). doi: 10.1093/nar/gkx1121. 2. Alexander SPH, et al. (2017) The Concise Guide to PHARMACOLOGY 2017/18. Br J Pharmacol. 174 (Suppl 1): S1- S446. 3. Bento AP, et al. (2014). The ChEMBL bioactivity database: an update. Nucl. Acids Res. 42 (Database Issue): D1083- D1090. 4. Rose PW, et al. (2017) The RCSB protein data bank: integrative view of protein, gene and 3D structural information. Nucl Acids Res, 45 (Database Issue), D271-D281.Figure 4. BLAST sequence search for targets GtoPdb is an ELIXIR UK node resource Figure 2. Target name search with autocomplete function Figure 3. Chemical structure search 4. Navigating target and ligand families Targets are organised by class, which can be browsed as a tree with families and subfamilies (Fig. 5). Ligands have also recently been organised into related families and groups (Fig. 6). Each family/group page lists summary information for the ligands, with links to more detailed pages (Fig. 7). Figure 5. Target families Joanna L. Sharman1, Elena Faccenda1, Simon D. Harding1, Adam J. Pawson1, Christopher Southan1, Stephen P.H. Alexander2, Anthony P. Davenport3, Michael Spedding4, Jamie A. Davies1 and NC-IUPHAR* 6. SynPHARM database of ligand binding sequences SynPHARM is a tool for finding ligand binding sequences which can be engineered into synthetic proteins to confer drugability. It combines pharmacological parameters from GtoPdb with ligand binding data from the RCSB Protein Data Bank [4] (Fig. 9). It is freely available at http://synpharm.guidetopharmacology.org. Figure 9. (A/B) The location of a ligand binding sequence is shown in green on a protein structure. (C) A residue distance matrix indicating ‘globularity’ of the sequence. The dotted line represents the binding sequence – the greener the area is the more compact the sequence. A B C 5. Comparing ligand affinity across species Ligand activity graphs provide a quick way to visualise affinity at different targets and across species. Box plots (Fig. 8A) summarise standardised activity data from GtoPdb and ChEMBL [3]. Individual data points, assay details and references are provided in an accompanying table (Fig. 8B). Figure 8. Chart and table showing palosuran activity at human and rat UT receptors Figure 1. Examples of data types for NHRs Figure 6. Ligand families Figure 7. A ligand family summary page A B 7. Downloading data Data are available to download in various formats: • Lists of targets, ligands and interactions in CSV format • REST web services for computational access to data in JSON format • SQL database dump files • Interaction data are now available in RDF format for semantic integration