1. Building linked-data, large-scale chemistry platform: challenges, lessons and solutions
Valery Tkachenko, Alexey Pshenichnov, Aileen Day, Colin Batchelor, Peter Corbett
Royal Society of Chemistry
ACS Spring 2016
San Diego, CA
March 13th 2016

2. ChemSpider –
OpenPHACTS –
Chemistry Data Platform – …

3. 45 million chemicals and growing
Data sourced from >500 different sources
Crowdsourced curation and annotation
Ongoing deposition of data from our journals and our collaborators
A structure centric hub for web-searching

4. ChemSpider

5. Chemical vendors and datasources

6. ChemSpider

7. Properties - experimental

8. Literature and patents references

9. Classification

10. Spectra

11. Multimedia

12. Tagging

13. ChemSpider - Summary Simple, flattish data model
InChI as a primary identifier
Linked by synonyms
Linked by “ExtId”
Standard searches (identity, substructure, similarity)
Very little semantics

14. OpenPHACTS: 2011-2014 Open PHACTS Mission:
Integrate Multiple Research Biomedical Data Resources Into A Single Open & Sustainable Access Point

15. OpenPHACTS Open PHACTS Practical Semantics
GlaxoSmithKline – Coordinator
Universität Wien – Managing entity
Technical University of Denmark
University of Hamburg, Center for Bioinformatics
BioSolveIT GmBH
Consorci Mar Parc de Salut de Barcelona
Leiden University Medical Centre
Royal Society of Chemistry
Vrije Universiteit Amsterdam
Novartis
Merck Serono
H. Lundbeck A/S
Eli Lilly
Netherlands Bioinformatics Centre
Swiss Institute of Bioinformatics
ConnectedDiscovery
EMBL-European Bioinformatics Institute
Janssen Esteve Almirall
OpenLink Scibite
The Open PHACTS Foundation
Spanish National Cancer Research Centre
University of Manchester
Maastricht University
Aqnowledge
University of Santiago de Compostela
Rheinische Friedrich-Wilhelms-Universität Bonn
AstraZeneca
Pfizer
@Open_PHACTS

16. Why is it so hard to…. IP? What’s the structure? Are they in our file?
What’s similar?
What’s the target?
Pharmacology data?
Known Pathways?
Working On Now?
Connections to disease?
Expressed in right cell type?
IP?
Remember this, some of these questions are easier to answer than others
Competitors?

17. Mx/psa, how calculated who did it? Mash up. With your data too,
“Let me compare MW, logP and PSA for known oxidoreductase inhibitors”
“What is the selectivity profile of known p38 inhibitors?”
“Find me compounds that inhibit targets in NFkB pathway assayed in only functional assays with a potency <1 μM”
ChEMBL
DrugBank
Gene Ontology
Wikipathways
GeneGo
Open PHACTS was developed to support the key questions of drug discovery
Business questions have been at the heart of Open PHACTS and have driven the development of the platform
Mx/psa, how calculated who did it?
Mash up. With your data too,
- top layer join together but need them all
commercial
ChEBI
UniProt
UMLS
neXtProt
GVKBio
ConceptWiki
ChemSpider
DisGeNet
TrialTrove
TR Integrity
ChEMBL
Target Class
ENZYME
FDA adverse
events
SureChEMBL 17

18. Open PHACTS was developed to support the key questions of drug discovery
Business questions have been at the heart of Open PHACTS and have driven the development of the platform
Mx/psa, how calculated who did it?
Mash up. With your data too,
- top layer join together but need them all
commercial
Data provided by many publishers
Originally in many formats: relational, SD files and RDF
Worked closely with publishers
Data licensing was a major issue
Over 5 billion triples – 14 datasets & growing
Hosted on beefy hardware; data in memory (aim)
Extensive memcaching
Pose complex queries to extract data
@gray_alasdair
Big Data Integration

19. OpenPHACTS Discovery Platform
RDF
Nanopub Db
VoID
Data Cache
(Virtuoso Triple Store)
Semantic Workflow Engine
Linked Data API (RDF/XML, TTL, JSON)
Domain
Specific
Services
Identity Resolution
Service
Chemistry Registration
Normalisation & Q/C
Identifier
Management
Indexing
Core Platform
P12374
EC2.43.4
CS4532
“Adenosine receptor 2a”
Public Content
Commercial
Public Ontologies
User
Annotations
Apps
Import data into cache
API calls populate SPARQL queries
Integration approach
Data kept in original model
Data cached in central triple store
API call translated to SPARQL query
Query expressed in terms of original data
Queries expanded by IMS to cover URIs of original datasets
21 October 2014
Scientific Lenses – A. J. G. Gray

20. Gleevec®: Imatinib Mesylate
YLMAHDNUQAMNNX-UHFFFAOYSA-N
Mesylate
ChemSpider
Drugbank
PubChem
Example drug: Gleevec Cancer drug for leukemia
Lookup in three popular public chemical databases
Different results
21 October 2014
Scientific Lenses – A. J. G. Gray

21. Scientific Lenses – A. J. G. Gray
Structure Lens
I need to compute an analysis, give me details of the active compound in Gleevec.
Strict
Relaxed
Analysing
Browsing
Interested in physiochemical properties of Gleevec
skos:exactMatch
(InChI)
21 October 2014
Scientific Lenses – A. J. G. Gray

22. Lens Effects: Ibuprofen
Commercial ibuprofen is a racemic mixture containing the same proportion of two chiral forms. Both chiral forms are equally active. Typically, the user will wish to retrieve info for any stereoisomer.
CHEMBL427526
CHEMBL521
CHEMBL175
21 October 2014
Scientific Lenses – A. J. G. Gray

23. Scientific Lenses – A. J. G. Gray
Default Lens
Commercial ibuprofen is a racemic mixture containing the same proportion of two chiral forms. Both chiral forms are equally active. Typically, the user will wish to retrieve info for any stereoisomer.
21 October 2014
Scientific Lenses – A. J. G. Gray

24. Scientific Lenses – A. J. G. Gray
Stereoisomer Lens
Commercial ibuprofen is a racemic mixture containing the same proportion of two chiral forms. Both chiral forms are equally active. Typically, the user will wish to retrieve info for any stereoisomer.
21 October 2014
Scientific Lenses – A. J. G. Gray

25. Scientific Lenses – A. J. G. Gray
Mapping Generation
ops:OPS437281 ✔
is_stereoisomer_of [ci:CHEMINF_000461]
has_stereoundefined_parent [ci:CHEMINF_000456]
Other relationships
has part
is tautomer of
uncharged counterpart
isotope …
ops:OPS380297
Validate structure: Source data is messy!
Identify common problems:
Charge imbalance
Stereochemistry
Compute physiochemical properties
Identify related properties based on structure
17 relationship types
ops:OPS380297
21 October 2014
Scientific Lenses – A. J. G. Gray

26. OpenPHACTS UI http://explorer.openphacts.org/

27. Scientific Lenses – A. J. G. Gray
Explorer Screenshot
21 October 2014
Scientific Lenses – A. J. G. Gray

28. Scientific Lenses – A. J. G. Gray
Explorer Screenshot
Pharmacology count 2370  3044
21 October 2014
Scientific Lenses – A. J. G. Gray

29. OpenPHACTS - Summary Principal difference – inter-domain links
More complex, but still structure-centric data model
Ontological relationships introduced
Chemical Lenses – new type of search

30. Chemistry Data Platform – 2014 - …

31. Dimensions and complexity of science
What about science and chemistry in particular?

33. RSC Archive – since 1841

34. Digitally Enabling RSC Archive

35. ChemSpider Synthetic Pages
Compounds
Reaction
Analytical Data
Text and References

36. RSC Databases RSC Compounds RSC Reactions RSC Spectra RSC Crystals
RSC Polymers
RSC Materials
RSC Assays
RSC Algorithms
RSC Models
…and on…

37. Compounds domain

39. Data quality issue and CVSP
Robochemistry
Proliferation of errors in public and private databases
ChemSpider
PubChem
DrugBank
KEGG
ChEBI/ChEMBL
Automated quality control system

40. Chemistry Validation and Standardization Platform

41. Chemistry Validation and Standardization Platform

42. Reactions domain
Information typically associated with reactions

44. Analytical data domain

45. Crystallography domain

46. Chemistry Data Platform - Summary
Simplified models within domain
Domains are described with its own models with embedded semantics
No proper domain-specific identifiers
Extensive quality control – CVSP (DOI /s )

47. There is no way back

48. Thank you
Slides: 48