Structure verification and elucidation using the ChemSpider database


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The ChemSpider database is an online resource containing >26 million chemicals sourced from over 400 data sources. As a result the database is a rich resource supporting the verification and elucidation of chemical structures and is utilized by mass spectrometrists around the world using the online user interface as well as the application programming interface. This presentation will provide an overview of how ChemSpider can be used for the purpose of structure identification and will include (1) direct interaction with the online interface; (2) integration to mass spectrometry vendor software; (3) applications to the identification of “known unknowns” and a comparison with the capabilities of CAS Scifinder and (4) the hosting of online mass spectral data.

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Structure verification and elucidation using the ChemSpider database

  1. 1. Structure verification and elucidation using the ChemSpider database Antony J Williams, Valery Tkachenko and Alexey Pshenichnov SERMACS, November 16th 2012
  2. 2. Mass Spectrometry for Structure ID Many applications of mass spectrometry are the identification of “knowns” Known structures, previously characterized, previously identified and, increasingly, online Dereplication, identification of “other manufacturers” materials, metabolites, lipids analysis – can be supported by existing databases What large database could serve mass spec. ?
  3. 3. ChemSpider 28 million chemicals with associated data…linked out to 400 data sources…
  4. 4. ChemSpider
  5. 5. What will ChemSpider give us??
  6. 6. What will ChemSpider give us??
  7. 7. What will ChemSpider give us??
  8. 8. What will ChemSpider give us??
  9. 9. Spectra Linked: e.g. Cholesterol
  10. 10. Spectra Linked
  11. 11. For Mass Spectrometrists Valuable searches for Mass Spec would be:  Search the database by mass or formula for structure identification  Search subsets of data – e.g. “metabolism”, pesticides etc  Link structure-based data across the internet  Provide “programming interfaces” to integrate  Does ChemSpider provide value to Mass Spectrometrists?
  12. 12. Pre-calculated data
  13. 13. Mass Spec AnalysisJim Little, Eastman Chemical
  14. 14. ChemSpider Interface
  15. 15. Tinuvin 328
  16. 16. Position sorted by references
  17. 17. Position 1 only
  18. 18. Searching by Monoisotopic Mass
  19. 19. Identification of “Known Unknowns” “Known Unknowns” can be identified by searching in ChemSpider Searching of “segregated” datasets can be performed Datasets can be expanded for specific projects – for example, natural products ID…
  20. 20. Web Services Open Up Collaboration Agilent, Bruker, Waters and Thermo all use our web-based services for compound lookup Many academic sites integrating directly – metabonomics, name lookup, semantic markup
  21. 21. Web Services
  22. 22. Results of the ChemSpider Searchin the MarkerLynx Worksheet
  23. 23. Hit Details in ChemSpider
  24. 24. Calculation of Elemental Composition &ChemSpider Search of Lipid MapsDatabase Performed via MarkerLynx
  25. 25. Commercial Database Access Recently deposited to ChemSpider  EPA/NIST IR Database >5000 spectra Presently under development  NIST MS database >200,000 MS spectra
  26. 26. Coming Soon – NIST DB in ChemSpider
  27. 27. Where next with Analytical Support? PharmaSea project for the identification of natural products – dereplication approaches  Use mass spectrometry searches of natural product slices to identify  Natural product data include from RSC databases (NPU) and ChemSpider data sources – MarinLit for example  Pre-fragment compounds and develop searches  Dereplication using NMR data  NMR features  Predicted spectra and “Verification approaches”
  28. 28. SpectraSchool
  29. 29. Coming Soon Storage and display of ASSIGNED spectra – already started with NMR spectral assignment
  30. 30. Crowdsourcing ChemSpider ChemSpider is crowdsourced Community deposition, annotation and curation Anyone can “Leave Feedback” Registered users can add data
  31. 31. Ideas for Future Work Extended search capabilities Expand existing databases Integrate to metabolic pathways tools
  32. 32. How long until Mobile StructureID?
  33. 33. Acknowledgments RSC eScience Team James Little, Eastman Chemical Company Alexey Pshenichnov, University of Leicester – SpectraSchool ACD/Labs – Assigned Spectra Display Widget Depositors of data – there are many!
  34. 34. Thank youEmail: williamsa@rsc.orgTwitter: ChemConnectorPersonal Blog: www.chemconnector.comSLIDES: