The Royal Society of Chemistry hosts one of the largest online chemistry databases containing almost 30 million unique chemical structures. The database, ChemSpider, provides the underpinning for a series of eScience projects allowing for the integration of chemical compounds with our archive of scientific publications, the delivery of a reaction database containing millions of reactions as well as a chemical validation and standardization platform developed to help improve the quality of structural representations on the internet. The InChI has been a fundamental part of each of our projects and has been pivotal in our support of international projects such as the Open PHACTS semantic web project integrating chemistry and biology data and the PharmaSea project focused on identifying novel chemical components from the ocean with the intention of identifying new antibiotics. This presentation will provide an overview of the importance of InChI in the development of many of our eScience platforms and how we have used it specifically in the ChemSpider project to provide integration across hundreds of websites and chemistry databases across the web. We will discuss how we are now expanding our efforts to develop a Global Chemistry Network encompassing efforts in Open Source Drug Discovery and the support of data management for neglected diseases.

1. The Importance of the InChI Identifier
as a Foundation Technology for
eScience Platforms at RSC
Antony Williams
Bio-IT,
Boston, April 27th
2014

2. Without the InChI…
• ChemSpider is unlikely to have been built
• It would not have grown into one of the
domains primary online chemistry resources
• The Royal Society of Chemistry would not
have it as an online database, would not
have a large cheminformatics team and
would not be involved in a number of large
scale funded projects around chemistry data

3. • ~30 million chemicals and growing
• Data sourced from >500 different sources
• Crowd sourced curation and annotation
• Ongoing deposition of data from our journals
and our collaborators
• Structure centric hub for web-searching
• …and a really big dictionary!!!

4. ChemSpider

5. ChemSpider

6. Experimental/Predicted Properties

7. Literature references

8. Patents references

9. So what is Yohimbine?

10. Of course it is out there…
Drugbox: 3001/5080 with InChIs
Chembox:5436/7690 with InChIs

11. Tell me more…
• Where can I find the molfile for Yohimbine?
• Papers/Patents about Yohimbine?
• What are the side effects of Yohimbine?
• Where can I order Yohimbine?
• What are the physicochemical properties?
• Metabolic pathways?
• Different synonyms of Yohimbine?
• Synthesis of Yohimbine?
• Side effects of Yohimbine?
• Etc….

12. Quantity!

13. Yohimbine on ChemSpider

14. Downsides of Overall Approach
• Meshing data together based on InChIs
worked for simple molecules
• 2D layout errors inherited or limited by
algorithm
• Complex molecules that are meant to be the
same thing were NOT deduplicated.
Compounds differing by one stereocenter,
named the same, meant to be the same, are
not the same

15. Yohimbine on
ChemSpider..Quality?

16. So where can we travel???

17. So where can we travel???

19. InChI String Search via Google
Give me InChIKeys…

20. And where can we travel???

21. ChemSpider
BRENDA
Wikipedia
ChEMBL
ChEBI
DrugBank

22. Aggregator
Enzymes
Encyclopedia
Pharmacology
Curated Chemicals
Drug-Drug Target

23. How do we build it?
• We deal in Molfiles or SDF files – with coordinates
• Deposit anything that has an InChI – we support
what InChI can handle, good and bad
• Standardization based on “InChI standardization”
• InChIs aggregate (certain) tautomers
• We link out to external sites using their IDs

24. Downsides of InChI
• InChI was a moving target (multi versions) but
overall worked as planned.
• Good for small molecules – but no polymers, issues
with inorganics, organometallics, imperfect
stereochemistry. ChemSpider is “small molecules”
• InChI used as the “deduplicator” – FIRST version of
a compound into the database becomes THE
structure to deduplicate against…

25. Side Effects of InChI Usage

26. SMILES by comparison…

27. Side Effects of InChI Usage

28. Standardization Issues
Depiction based on molfile

29. Standardize
Use the SRS as a guidance document for
standardization
Adjust as necessary to our needs

30. Nitro groups

31. Salt and Ionic Bonds

32. Ammonium salts

33. CVSP

34. NPC Browser Set

35. Checking include InChI
• Many SDF files contain InChIs and SMILES
– comparing the structure contained within
the file with the associated InChI is useful –
turned up a number of errors in checking
online databases

36. So, I’m writing an article…

37. With these…I will lose data 

38. But linking with InChI …

39. Structure Searching the Web

40. Data in Publications
• This is not new, you know the story…
• So much data of value is contained within a
publication and delivered in a PDF form
• PDF files, and unclear licensing/copyright, limit
access to data so I can rework, reuse,
repurpose, text mine etc.
• “I specialize in XXXX. I want a database of
YYYY extracted from publications and made
available, for free, with the capabilities I need,
and the publishers should just do it”

41. “Data enable” publications?
• We would LOVE to bring data out of our archive
• What could we do?
• Find chemical names and generate structures
• Find chemical images and generate structures
• Find reactions – and make a database!
• Find data (MP, BP, LogP) and host. Build
models!
• Find figures and database them
• Find spectra (and link to structures)
• Validate the data algorithmically

42. RSC Archive – since 1841

43. Text Mining
The N-(β-hydroxyethyl)-N-methyl-N'-(2-trifluoromethyl-1,3,4-
thiadiazol-5-yl)urea prepared in Example 6 , thionyl chloride ( 5
ml ) and benzene ( 50 ml ) were charged into a glass reaction
vessel equipped with a mechanical stirrer , thermometer and
reflux condenser .
The reaction mixture was heated at reflux with stirring , for a
period of about one-half hour .
After this time the benzene and unreacted thionyl chloride were
stripped from the reaction mixture under reduced pressure to
yield the desired product N-(β-chloroethyl)-N-methyl-N'-(2-
trifluoromethyl-1,3,4-thiaidazol-5-yl)urea as a solid residue

44. Text Mining
The N-(β-hydroxyethyl)-N-methyl-N'-(2-trifluoromethyl-1,3,4-
thiadiazol-5-yl)urea prepared in Example 6 , thionyl chloride ( 5
ml ) and benzene ( 50 ml ) were charged into a glass reaction
vessel equipped with a mechanical stirrer , thermometer and
reflux condenser .
The reaction mixture was heated at reflux with stirring , for a
period of about one-half hour .
After this time the benzene and unreacted thionyl chloride were
stripped from the reaction mixture under reduced pressure to
yield the desired product N-(β-chloroethyl)-N-methyl-N'-(2-
trifluoromethyl-1,3,4-thiaidazol-5-yl)urea as a solid residue

45. But names = structures
• Systematic names can be generated FROM
chemical structures algorithmically

46. But names = structures
• …and structures from systematic names

47. But what of trivial names?
• What about trivial names, trade names, CAS
numbers, multilingual names etc.?

48. Searching that lipid in patents

49. Aspirin on ChemSpider

50. Work in Progress

51. Work in Progress

52. Work in Progress

53. Work in Progress

54. But Context Gives Reactions
The N-(β-hydroxyethyl)-N-methyl-N'-(2-trifluoromethyl-1,3,4-
thiadiazol-5-yl)urea prepared in Example 6 , thionyl chloride ( 5
ml ) and benzene ( 50 ml ) were charged into a glass reaction
vessel equipped with a mechanical stirrer , thermometer and
reflux condenser .
The reaction mixture was heated at reflux with stirring , for a
period of about one-half hour .
After this time the benzene and unreacted thionyl chloride were
stripped from the reaction mixture under reduced pressure to
yield the desired product N-(β-chloroethyl)-N-methyl-N'-(2-
trifluoromethyl-1,3,4-thiaidazol-5-yl)urea as a solid residue

55. ChemSpider Reactions

56. ChemSpider as a Foundation
• >30 million chemicals (and growing)
• ChemSpider is free to access for everyone –
and the API means people program against it
• What projects can we benefit?

57. Support grant-based services
• Multiple European consortium-based grants
• PharmaSea (FP7 funded)
• Open PHACTS (IMI funded)
• UK National Chemical Database Service
(http://cds.rsc.org) – developing data repository
for lab data, integrate Electronic Lab Notebooks
• Open Drug Discovery projects

59. PharmaSea

60. • 3-year Innovative Medicines Initiative project
• Integrating chemistry and biology data using
semantic web technologies
• Open code, open data, open standards
• Academics, Pharmas, Publishers…
• To put medicines in the pipeline…

61. Open PHACTS

62. All Databases We Generate…
• All databases and systems we build now
include generated InChIs
• InChIs are facilitating discoverability via
searching on Google (see Chris’ talk) but
also for querying and linking

63. But we are still VERY LIMITED
• RSC deals with way more than organics,
inorganics, organometallics – we are building a
data repository to include materials, polymers,
ambiguous materials etc.
• There are many plans for InChI moving forward
– Markush, polymers, organometallics etc

64. The great promise should be
obvious
• InChIs are here to stay
• They will evolve, they will encompass, we will
adopt and adapt
• Public and private databases will federate &
build a linked environment of validated data!
• Data validation and standardization is
needed
• Open Data will continue to proliferate
• InChIs are in the “Semantic Web” already

65. If InChI never existed …
• ChemSpider would never have been built
• Database linking would suffer dramatically
• The web would not be “structure searchable”
• Cheminformatics tools would likely not be
linking to public domain databases in the
same way

66. Thank you
Email: williamsa@rsc.org
ORCID: 0000-0002-2668-4821
Twitter: @ChemConnector
Personal Blog: www.chemconnector.com
SLIDES: www.slideshare.net/AntonyWilliams