www.guidetopharmacology.org

Slicing and dicing curated protein targets: Analysing the drugged, druggable and tractable

Dr Christopher Southan

April 2015, BPS Focused Meeting: Exploiting the new pharmacology and application to drug discovery

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Outline

• Guide to PHARMACOLOGY database (GtoPdb) content

• Slicing and dicing

• Drugged vs tractable Venn diagram

• High vs low affinity Genome Ontology (GO) splits

• Enzyme targets to pathway mapping

• Source a reagent for a protease target in pathway

• Conclusions

• Acknowledgments

• Questions

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GtoPdb curated content (March 2015 release)

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The power of slicing and dicing via target protein IDs

• Database queries that allow intersects (Boolean AND), unions (Boolean

OR) and differentials (Boolean NOT) e.g.

• Which UniProtKB/Swiss-Prot entries cite “Southan” (= 34)

• AND where organism is “Homo sapiens” (= 9)

• AND have a cross-reference in Guide to PHARMACOLGY (=3)

• Can start the query with any extrinsically “sliced” sets (e.g. from GtoPdb)

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Example : drugged vs tractable (GtoPdb protein IDs

• Human targets, with any ligand = 1371

• Human targets, ligand is approved drug = 464

• Human targets, ligand has pAct 6-8 (lower affinity) = 532

• Human targets, ligand has pAct 9-10 (higher affinity) = 451

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Useful “slice and dice”

tool

Oliveros, J.C. (2007-

2015) Venny. An

interactive tool for

comparing lists with

Venn diagrams.

http://bioinfogp.cnb.csic.e

s/tools/venny/index.html

Difference between drug targets with high vs low affinity

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• Gene ontology splits

(via Panther,

another useful slice

and dice tool)

• Analysis shows clear

bias towards

transporters for low

affinity drugs and

receptors for high

affinity drugs

Enzyme targets with high-affinity drugs: in which pathways ?

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• Of the 56 enzyme targets with high affinity drugs 54 were in a Reactome pathway

• Can display any indexing or x-refs in results (e.g. protease via MEROPS)

Source a high-affinity drug for a protease target in this pathway

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• 15 vendors for saxaglyptin

• Can even find a 2005 BMS patent US7420079

GtoPdb + UniProt + Venny + Panther

• Almost limitless drug target slice and dice options

• Powerful specificity of query building

• Our cross-references in UniProt regularly updated

• Answer and/or hypothesis-test pharmacologically relevant

questions (e.g. multiple pathway perturbation points)

• These can steer your experimental drug discovery work

• Either contact us for advanced slicing from GtoPdb that

you can not get directly (e.g. the affinity cuts) or download

our lists or even the whole database for DIY

• You can also slice and dice on the ligand chemistry side

for example via the PubChem Identifier Exchange Service

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Acknowledgements and questions welcome

• The late Prof Tony Harmar, founder and original PI of GtoPdb

• GtoPdb database team:

• Jamie Davies (Principal Investigator)

• Adam Pawson, Helen Benson, Elena Faccenda (Curators)

• Joanna Sharman (Database Developer)

• Veronika Divincova (Project Administrator)

• Past and present members of NC-IUPHAR and its subcommittees, especially

Michael Spedding, Steve Alexander, Anthony Davenport and John Peters

• Guide to PHARMACOLOGY contributors

• NC-IUPHAR and GtoPdb sponsors

• IUPHAR/BPS Guide to PHARMACOLOGY funders:

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