Poster titled "The imperative of small, high quality data for underpinning big data: the IUPHAR/BPS Guide to PHARMACOLOGY". Presented by Dr. Christopher Southan, at the British Society of Pharmacology, Institute for Translational Medicine & Therapeutics (ITMAT) Meeting, Edinburgh, March 2017, ‘Big Data & the Development of New Medicines’.

1. Christopher Southan1, Antony P. Davenport2, Joanna L. Sharman1, Adam J. Pawson1,
Simon D. Harding1, Elena Faccenda1, Jamie A. Davies1 and NC-IUPHAR3.
1IUPHAR/BPS Guide to PHARMACOLOGY, Centre for Integrative Physiology, University of Edinburgh, EH8 9XD, UK. 2Experimental Medicine and
Immunotherapeutics, University of Cambridge, Addenbrooke's Hospital, Cambridge, CB2 0QQ, UK. 3The International Union of Basic and Clinical
Pharmacology Committee on Receptor Nomenclature and Drug Classification.
The imperative of small, high quality data for underpinning
big data: the IUPHAR/BPS Guide to PHARMACOLOGY
Unique content
• Part of our value derives from relationship mapping
stringencies, expert comments and unique content
• This uniqueness arises from journal selectivity and
frequent quarterly releases capturing new publications
• We have ligand binding interactions for over 70 human
proteins that are neither in DrugBank nor ChEMBL
• Figure 3 (below) provides a breakdown of our PubChem
content that indicated aspects of uniqueness
• We submit all our ligands (as SIDs) but some are too
large to be assigned compound identifiers (CIDs)
• Over 1000 of these are receptor-binding peptides from
the pharmacological literature
• 320 of our structures are unique in PubChem (total 94m)
• Compared to DrugBank we differ by over ½ their content
• We have 1,535 CIDs not in ChEMBL
Examples of GPCR database tables
Conclusions
• The underpinning value of our “small data” quality is
reflected in at least 15 other databases (e.g. UniChem,
PubChem, ChEMBL, UniProt, HGNC, ChemProt and others)
choosing to point their links to us
• GtoPdb supports translational research with ligand binding
data for rodent targets
• We also recommend tool compounds for agonists,
antagonists and radiolabelled ligands
• Our data facilitates both direct mining and integration of
quantitative pharmacology from the translational
disciplines of chemical biology and genetics
• We are increasing our “big data” utility by a) downloads
and web services b) developing Resource Description
Framework (RDF) for integration with other resources
(e.g. OpenPhacts) and c) a Wellcome funded project to
extend our existing schema into the immunopharmacology
domain for expanded relationship capture
Introduction
• The Wellcome Trust funded International Union of
Pharmacology (IUPHAR)/British Pharmacology Society
(BPS) database (GtoPdb)
www.guidetopharmacology.org
• Provides annotated molecular interactions between
endogenous receptor ligands, research compounds,
approved drugs and their Swiss-Prot targets
• Builds on the reputation of its predecessor IUPHAR-DB
• Enables pharmacologists and other bioscientists to
identify key compounds across target classes
• Is being integrated into “big data” resources
www.slideshare.net/GuidetoPHARM/gtopdbitmat2017 cdsouthan@hotmail.com
Fig. 2. Breakdown
of ligand by class
in GtoPdb
UK Node Resource for:
Populating the database
• As described in PMID 26464438, GtoPdb content is
curated from pharmacology and medicinal chemistry
journals, released quarterly, with PubChem updates
• Quality is ensured by expert curation by a highly
qualified team and our unique model of integrating
recommendations and updates from IUPHAR target
class subcommittees of international experts
• We have connected ~14,000 binding values (mainly
IC50, Ki, Kd) between ~8,000 ligands (see Fig. 1) and
~1,500 human proteins (see Fig. 2) thereby defining
7% of the druggable proteome
• We curate out-links to a range of chemistry and
protein databases where we have direct contacts
Fig. 1. Breakdown
of human targets in
GtoPdb
Fig. 3. GtoPdb
ligands in
PubChem