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Hosting public domain chemicals data online for the community – the challenges of handling materials
The document discusses challenges and opportunities in managing public domain chemical data online, emphasizing the need for integration and standardization across diverse chemical information sources. It highlights the role of platforms like ChemSpider in crowd-sourced curation and the importance of accurate data representation for effective chemical research and discovery. Additionally, it explores the shift towards open data in science, seeking collaboration and improved data quality to better serve the scientific community.
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Hosting public domain chemicals data online for the community – the challenges of handling materials
- 1. Hosting public domainchemicals data online for the community – the challenges of handling materials Antony Williams Opportunities in Materials Informatics, University of Wisconsin-Madison February 9th , 2015 0000-0002-2668-4821
- 2. About Me… • Iam NOT a materials chemist • I am an NMR spectroscopist by training • Worked on a LIMS while at Kodak • 10 years in commercial cheminformatics • Built the ChemSpider database as a hobby • Worked on validating compounds on Wikipedia • Manage cheminformatics team for RSC • Believer in the value of social networking and Open Data for science • Dane Morgan asked me to tell jokes…
- 3. I would tella chemistry joke… But all of the good ones…
- 4. An ambitious idea…. •Let’s map together all online chemistry data and build systems to integrate it • Heck, let’s integrate chemistry and biology data and add in disease data too if we can • Let’s extract property data and model it and see if we can extract new relationships – quantitative and qualitative • Let’s make it all available on the web…for free
- 6. What about this…. •We’re going to map the world • We’re going to take photos of as many places as we can and link them together • We’ll let people annotate and curate the map • Then let’s make it available free on the web • We’ll make it available for decision making • Put it on Mobile Devices, give it away…
- 7. Where is chemistryonline? • Encyclopedic articles (Wikipedia) • Chemical vendor databases • Metabolic pathway databases • Property databases • Patents with chemical structures • Drug Discovery data • Scientific publications • Compound aggregators • Blogs/Wikis and Open Notebook Science
- 8. Chemistry on theInternet… • Most searching for chemistry on the internet… • Name searching Google/Bing/Yahoo • Name searching Wikipedia • Name searching Wolfram Alpha • Name, name, name, name…searching • Structure searching DOZENS of websites, each with different information or…
- 9. Chemistry on theInternet… • Most searching for chemistry on the internet… • Name searching Google/Bing/Yahoo • Name searching Wikipedia • Name searching Wolfram Alpha • Name, name, name, name…searching • Structure searching DOZENS of websites, each with different information or… • Search ONE website integrating the others!
- 10. • ~30 millionchemicals 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!!! • Note…NOT all websites connected
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- 19. Vendors and datasources
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- 22. Organic Chemistry ishard…
- 23. …it has alkynesof trouble
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- 25. Molfiles 10 9 00 1 0 0 0 0 0 1 V2000 31.2937 -9.0366 0.0000 C 0 0 0 0 0 0 0 0 0 0 0 0 26.6526 -9.0366 0.0000 C 0 0 0 0 0 0 0 0 0 0 0 0 31.2937 -7.7066 0.0000 O 0 0 0 0 0 0 0 0 0 0 0 0 30.1161 -9.6877 0.0000 C 0 0 0 0 0 0 0 0 0 0 0 0 25.5096 -9.6877 0.0000 O 0 0 0 0 0 0 0 0 0 0 0 0 28.9731 -9.0366 0.0000 C 0 0 0 0 0 0 0 0 0 0 0 0 27.8163 -9.7016 0.0000 C 0 0 0 0 0 0 0 0 0 0 0 0 26.6664 -7.7066 0.0000 N 0 0 0 0 0 0 0 0 0 0 0 0 32.4367 -9.6877 0.0000 O 0 0 0 0 0 0 0 0 0 0 0 0 30.1161 -11.0177 0.0000 N 0 0 0 0 0 0 0 0 0 0 0 0 3 1 2 0 0 0 0 4 1 1 0 0 0 0 9 1 1 0 0 0 0 7 2 1 0 0 0 0 5 2 2 0 0 0 0 8 2 1 0 0 0 0 6 4 1 0 0 0 0 4 10 1 6 0 0 0 7 6 1 0 0 0 0 M END
- 26. Molfiles • Molfiles arethe primary exchange format between structure drawing packages • Can be different between different drawing packages • Most commonly carry X,Y coordinates for layout • Can support polymers, organometallics, etc. • Can carry 3D coordinates
- 27. SMILES • SMILES isa common format • Can support polymers, organometallics, etc. • Does NOT carry X,Y or Z coordinates for layout so requires layout algorithms – can be problematic! • Generally different between drawing packages
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- 33. InChI • SINGLE codebase managed by IUPAC – integrated into drawing packages. No variability as with SMILES • InChI Strings can be reversed to structures – same problem as with SMILES – no layout • Adopted by the community (databases, blogs, Wikipedia) – good for searching the internet
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- 37. InChIStrings Hash toInChIKeys
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- 41. Data Quality/Standardization • MANYstructures meant to be something online are MISREPRESENTED. • Commonly you will have better success finding information by name searches than structure – with many caveats of course… • Validating chemical structure representations is laborious work – and it’s shocking to review data…
- 42. Data Quality Issues Williamsand Ekins, DDT, 16: 747-750 (2011) Science Translational Medicine 2011
- 43. Data quality isa known issue
- 44. Data quality isa known issue
- 45. Substructure # of Hits #of Correct Hits No stereochemistry Incomplete Stereochemistry Complete but incorrect stereochemistry Gonane 34 5 8 21 0 Gon-4-ene 55 12 3 33 7 Gon-1,4-diene 60 17 10 23 10 Only 34 out of 149 structures were correct!
- 46. Patent data inpublic databases
- 47. Patent data inpublic databases
- 48. You just can’ttrust atoms!
- 49. You just can’ttrust atoms! They make up everything…
- 50. ALL variants ofYohimbine!!!
- 51. What’s Methane? OLDPUBCHEM
- 52. What ELSE isMethane???
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- 56. What is theStructure of Vitamin K1?
- 57. Standardize • Use theSRS as a guidance document for standardization • Adjust as necessary to our needs
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- 59. Salt and IonicBonds
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- 61. Can we MAKEQuality Data? • We are building systems for everyone to validate and standardize their data
- 62. DICTIONARIES are powerful •Search all forms of structure IDs • Systematic name(s) • Trivial Name(s) • SMILES • InChI Strings • InChIKeys • Database IDs • Registry Number
- 63. Many Names, OneStructure
- 64. But big andoften noisy
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- 67. With links outto platforms
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- 69. Text Mining onIUPAC Names 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
- 70. Text Mining onIUPAC Names 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
- 71. Name to StructureConversion
- 72. Name to StructureConversion
- 73. ChemSpider “Annotations” • Userscan add • Descriptions, Syntheses and Commentaries • Links to PubMed articles • Links to articles via DOIs • Add spectral data • Add Crystallographic Information Files • Add photos • Add MP3 files • Add Videos
- 74. Spectral Data • Spectraldata to be deposited in standard formats – JCAMP or images • All spectra available at: http://www.chemspider.com/spectra.aspx • Data are deposited on a regular basis • Students • Chemical vendors • Growing collection now
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- 79. It’s exactly theWRONG WAY! • We should NOT be mining data out of future publications • Structures should be submitted “correctly” • Spectra should be digital spectral formats, not images • ESI should be RICH and interactive, preferably with OPEN DATA
- 80. An Adventure intothe World of Small but significant contribution..
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- 82. Micropublishing with PeerReview (a chemical synthesis blog?)
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- 85. Chemistry data isof value? • Reference databases generate hundreds of millions of dollars/euros per year • So much data generated that could go public • Maybe 5% of all data generated is published • There is no “Journal of Failed Experiments” • Funding agencies start to demand Open Data • Scientists want funding but also recognition
- 86. A shift toOpenness
- 87. How will Iget recognized? • Who in the room has an ORCID?
- 88. Deposition of ResearchData • If we manage compounds, syntheses and analytical data… • If we have security and provenance of data… • If we deliver user interfaces to satisfy the various use cases… • Then we have delivered electronic lab notebooks for chemistry laboratories. ELNs are research data repositories
- 89. Recognition: need tohave Impact
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- 91. National Information Standards Organizationand “Altmetrics” http://www.niso.org/apps/group_public/download.php/13295/niso_altmetrics_white_paper_draft_v4.pdf
- 92. What are webuilding? • We are building the “RSC Data Repository” • Containers for compounds, reactions, analytical data, tabular data • Algorithms for data validation and standardization • Flexible indexing and search technologies • A platform for modeling data and hosting existing models and predictive algorithms
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- 97. Deposition of Data •Developing systems that provides feedback to users regarding data quality • Validate/standardize chemical compounds • Check for balanced reactions • Checks spectral data • EXAMPLE Future work • Properties – compare experimental to pred. • Automated structure verification - NMR
- 98. So we knowabout ORGANICS • Comment – you don’t know all of the challenges until you start to work in the area! • We, and cheminformatics companies, have solved MANY, but not all of the issues regarding organic chemistry management • The majority of our approaches do not map to materials • No standard ways to represent compounds • No InChI for materials
- 99. Questions to consider… •Organics are hard enough! • What are your best dictionaries of materials? • We have chemical ontologies. Status for materials? • Is open annotation of your databases possible? • What standards do you have for materials data exchange?
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- 101. Known Challenges • Manymaterials are non-stoichiometric • How to represent composite materials (e.g. supported catalysts)? • Methods to distinguish novelty in materials (equivalent to diversity in organic structures)? • Many more I will learn at this workshop..?
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- 103. Internet Data The Future CommercialSoftware Pre-competitive Data Open Science Open Data Publishers Educators Open Databases Chemical Vendors Small organic molecules Undefined materials Organometallics Nanomaterials Polymers Minerals Particle bound Links to Biologicals
- 104. Thank you Email: williamsa@rsc.org ORCID:0000-0002-2668-4821 Twitter: @ChemConnector Personal Blog: www.chemconnector.com SLIDES: www.slideshare.net/AntonyWilliams