The document introduces the IUPHAR/BPS Guide to PHARMACOLOGY (GtoPdb) database. It summarizes that the GtoPdb is curated by an expert team at the University of Edinburgh and provides data on drug targets and their ligands that has been extracted from the literature and standardized. The database aims to be an educational resource for pharmacology and also help with drug discovery by providing standardized pharmacological data to researchers. It discusses how the data is curated, the types of targets and ligands included, usage statistics, funding sources, and plans to expand the scope and linked data capabilities of the GtoPdb.

1. Introducing the IUPHAR/BPS Guide to
PHARMACOLOGY(GtoPdb)
http://www.guidetopharmacology.org/
Webinar presentation by Chris Southan
for ELIXIR-UK all-hands 5th of Dec 2016
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2. Who and where
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• Core team: Christopher Southan, Elena Faccenda, Simon J. Harding, Joanna L.
Sharman, Adam J. Pawson, Prof. Jamie A Davies (PI and Grant holder)
• IUPHAR = International Union of Basic and Clinical Pharmacology
• NC-IUPHAR = Committee on Receptor Nomenclature and Drug Classification
• BPS = British Pharmacological Society
• BJP = British Journal of Pharmacology (Wiley, Oxford)
• Where: University of Edinburgh, Centre for Integrated Physiology, EH8 9XD, UK.
(Chris works remotely from Göteborg, Sweden)

3. Data availability (from ELIXIR form)
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4. Database history
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• In 2012 GtoPdb became single entry point to previously separate but
complementary information sources
• The IUPHAR database (IUPHAR-DB from 2009)
• Guide to Receptors and Channels (GRAC) series of British Journal of
Pharmacology publications

5. NAR history
The IUPHAR/BPS Guide to PHARMACOLOGY in 2016: towards curated quantitative
interactions between 1300 protein targets and 6000 ligands. Southan et. al. Nucleic
Acids Research [2016, 44(D1):D1054-68] (PMID:26464438) 8 citations (EPMC figures)
The IUPHAR/BPS Guide to PHARMACOLOGY: an expert-driven knowledgebase of
drug targets and their ligands. Pawson et al. Nucleic Acids Research [2014,
42(Database issue):D1098-106] (PMID:24234439) 359 citations
IUPHAR-DB: updated database content and new features. Sharman et al. Nucleic
Acids Research [2013, 41(Database issue):D1083-8] (PMID:23087376) 33 citations
IUPHAR-DB: new receptors and tools for easy searching and visualization of
pharmacological data. Sharman et al. Nucleic Acids Research [2011, 39(Database
issue):D534-8] (PMID:21087994) 55 citations
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6. Remits
• Provide access to data on all known biological targets
• Populate the data records by expert curation
• Browsable by wide range of users (from students to Profs)
• Make recommendations on ligands for use in characterising targets
• Provide an entry point into the pharmacological literature
• From BJP papers and reviews to point “back” to database
• Provide an integrated educational resource for principles of basic and
clinical pharmacology
• Distillation of selected content into the BJP “ConsiseGuide” bi-annual
series of reviews
• Content fully open, downloadable and consumable
• Foster innovative drug discovery
• Tight liaison with NC-IPHAR and BPS
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7. Curating the core relationship chain
• Documents are mostly PubMed IDs but some patents also
• Assay is implicitly described in each publication
• Results typically recorded as IC50, Ki, Kd or EC50, log transformed to pAct (e.g.
4-10)
• We define “ligand” as the implicit binding entity, mostly small-molecules but
some peptides, small proteins and therapeutic antibodies
• Target usually resolved to a UniProt ID
• Pick individual interactions from complexes where possible (e.g. PSEN1 for
gamma secretase)
• Have some ligands with unknown molecular mechanism of action (mmoa)
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8. 8

9. Targets
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10. Complementary target coverage:
selectable UniProt cross-references
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11. Ligands
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12. GtoPdb
drugs
• The PubChem query (approved[comment]AND "IUPHAR/BPSGuide to
PHARMACOLOGY"[SourceName]) retrieves just our 1291 substances (SIDs)
• These convert to 1174 distinct compound entries (CIDs)
• 96% vendor matches in PubChem
• The 117 SID difference is mainly antibodies 12
Introduced a
clean
PubChem
select for our
drugs

13. GtoPdb curated small-molecules in PubChem:
Useful intersects and diffs
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14. Recent curated relationship growth
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• Human proteins with quantitative interactions, including kinase screening
data 1429
• Without kinase screening data it is 1322

15. Usage stats
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16. Unique to GtoPdb, NC-IUPHAR:
part SAB, part “supercurator” network
• ~ 60 specialist subcommittees, mostly target family-centric
• ~ 630 scientists globally
• Send regular updates to be curated into the database
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(This is an
older list now
being
updated)

17. The value of ecosystem in-links/cross-pointers
• We have a blog post describing these
https://blog.guidetopharmacology.org/2016/03/30/collation-and-assessment-
of-gtopdb-in-links/
• More that we suspected, probably others we are unaware of
• Includes PubChem, HGNC, UniProtKB/Swiss-Prot, neXtProt, IMGT/mAb-DB,
ChEMBL, UniChem, MEROPS,GPCRdb, ChemSpider, Oprhanet, CARLSBAD,
GLASS, ChemProt, ZINC, DGIdb 2.0 and DrugCentral
• We foster socio-collaborative contacts with most of these, via invitations to our
bi-annual meetings, TCs and conference bar encounters
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18. Funding
• WellcomeTrust 099156/Z/12/Z Nov 2012 - 31 Oct 2015 to Prof Jamie Davis
(taking over from the late Prof.Tony Harmar). University of Edinburgh IT
infrastructure support .
• GtoPdb has also been supported by:The British Pharmacological Society
(March 2011 - March 2015, and IUPHAR (March 2011 – March 2015).
• Current, November 2015 to October 2018, newWellcomeTrust 108420/Z/15/Z
to extend GtoPdb into Immunopharmacology
• Servier Laboratories sponsorship of annual meeting
• The BPS supporting 2 FTEs (March 2016 – March 2020)
• Commitee, headed by Prof. Davies planning future options. Currently
preparingWellcome proposal “GtoAMPdb – a database of antimicrobials,
targets, and mechanisms of resistance”
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19. Plans and issues
• Need to be RDF-ised
• As usual – limitations of curation capacity
• Manual vs auto (brainless) linking
• New data aspects obsoleting older content (e.g. expression data and clinical
variants
• Analytics exposes legacy data issues that are difficult to remediate
• Impingement by other resources
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20. Thank you;
questions
welcome
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Didactic slide slide set from 2014
http://www.slideshare.net/GuidetoPHARM/iupharbps-guide-to-pharmacology-generic-slideset
FAQ
http://www.guidetopharmacology.org/faq.jsp