Non-targeted analysis (NTA) uses high-resolution mass spectrometry to better understand the identity of a wide variety of chemicals present in environmental samples (and other matrices). However, data processing remains challenging due to the vast number of chemicals detected in samples, software and computational requirements of data processing, and inherent uncertainty in confidently identifying chemicals from candidate lists. Analysis of the resultant mass spectrometry information relies on cheminformatics to identify and rank chemicals and the US EPA has developed functionality within the CompTox Chemicals Dashboard (https://comptox.epa.gov/dashboard) to address challenges related to this analysis. These tools include the generation of “MS-Ready” structures to optimize database searching, retention time prediction for candidate reduction, consensus ranking using chemical metadata, and in silico MS/MS fragmentation prediction for spectral matching. Combining these tools into a comprehensive workflow improves certainty in candidate identification. This presentation will review how the CompTox Chemicals Dashboard via its flexible search capabilities, rich data for ~900,000 chemical substances, and visualization approaches within this open chemistry resource provides a freely available software tool to support structure identification and NTA. This abstract does not necessarily represent the views or policies of the U.S. Environmental Protection Agency.

1. Non-targeted analysis supported by data
and cheminformatics delivered via the US
EPA CompTox Chemicals Dashboard
Antony Williams, Alex Chao, Tom Transue, Tommy Cathey,
Elin Ulrich and Jon Sobus
1) National Center for Computational Toxicology, U.S. Environmental Protection Agency, RTP, NC
2) Oak Ridge Institute of Science and Education (ORISE) Research Participant, RTP, NC
3) GDIT, Research Triangle Park, North Carolina, United State
4) National Exposure Research Laboratory, U.S. Environmental Protection Agency, RTP, NC
August 2019
ACS Fall Meeting, San Diego
http://www.orcid.org/0000-0002-2668-4821
The views expressed in this presentation are those of the author and do not necessarily reflect the views or policies of the U.S. EPA

2. An intro to the Dashboard
• Freely available web-based database from the
National Center for Computational Toxicology
• Providing data for 875,000 substances including
– Experimental and predicted physicochemical properties
– In vivo toxicity data harvested from dozens of public resources
– In vitro bioactivity data for thousands of chemicals and assays
– Exposure data including chemicals in consumer products
– Real time predictions for >20 physchem and toxicological endpoints
• Dashboard is used by mass spectrometrists for
chemical identification
• A quick view of general capabilities…
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3. CompTox Chemicals Dashboard
https://comptox.epa.gov/dashboard
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875k Chemical Substances

4. Detailed Chemical Pages
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5. Access to Chemical Hazard Data
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6. Sources of Exposure to Chemicals
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7. Link Access
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Links based on chemical
identifiers to dozens of
online resources –
including analytical data

8. MassBank of North America
https://mona.fiehnlab.ucdavis.edu
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9. “MS-ready”
structures
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10. Overview of MS-Ready Structures
• All structure-based chemical substances are
algorithmically processed to
– Split multicomponent chemicals into individual structures
– Desalt and neutralize individual structures
– Remove stereochemical bonds from all chemicals
• MS-Ready structures are then mapped to
original substances to provide a path between
chemicals detected by mass spectrometry to
original substances
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11. 10

12. MS-Ready Mappings from
Details Page
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13. Two MS-Ready Mappings Set
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14. MS-Ready Mappings Set
All substances containing component
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15. Mass/Formula
Searching and
Metadata Ranking
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16. Advanced Searches
Mass Search
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17. Advanced Searches
Mass Search
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18. MS-Ready Structures for
Formula Search
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19. MS-Ready Mappings
• EXACT Formula: C10H16N2O8: 3 Hits
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20. MS-Ready Mappings
• Same Input Formula: C10H16N2O8
• MS Ready Formula Search: 125 Chemicals
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21. MS-Ready Mappings
• Exact Formula – 3 hits
• MS-Ready Formula – 125 hits!!
– ONLY 8 of the 125 are single component chemicals
– 3 are neutral compounds and 2 are charged
• How can we rank the candidates list?
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22. Candidate ranking
using metadata
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23. Data Source Ranking of
“known unknowns”
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• A mass and/or formula search is
for an unknown chemical but it
is a known chemical contained
within a reference database
• Most likely candidate chemicals
have the most associated data
sources, most associated
literature articles or both
C14H22N2O3
266.16304
Chemical
Reference
Database
Sorted candidate
structures

24. The original ChemSpider work
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25. Is a bigger database better?
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• ChemSpider was 26 million chemicals for
the original work
• Much BIGGER today
• Is bigger better??
• Are there other metadata to use for ranking?

26. Using Metadata for Ranking
• Chosen dashboard metadata to rank candidates
– Associated data sources
• Lists in the underlying database (more about lists later)
• Associated data sources in PubChem
• Specific source types (e.g. water, surfactants, pesticides)
– Number of associated literature articles (Pubmed)
– Chemicals in the environment – the number of
products/categories containing the chemical is an
important source of data (from CPDat database)
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27. Identification ranks for 1783 chemicals
using multiple data streams
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DS: Data Sources
PC: PubChem
PM: PubMed
STOFF: DB
KEMI: DB
Data Sources alone
rank ~75% of the
chemicals as Top Hit

28. Comparing Search Performance
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• When dashboard contained 720k chemicals
• Only 3% of ChemSpider size
• What was the comparison in performance?

29. SAME dataset for comparison
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30. How did performance compare?
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For the same 162 chemicals,
Dashboard outperforms
ChemSpider for both Mass and
Formula Ranking

31. How did performance compare?
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32. Data Quality is important
• Data quality in free web-based databases!
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33. Public Databases require curation
• There is significant bloating in the public
databases because of lack of curation
• The number of hits retrieved based on
mass or formula searching can explode
based on poorly represented chemicals –
especially stereochemistry issues
• MS-Ready structures will map back to
multiple versions of “the same chemical”.
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34. Will the correct Microcystin LR Stand Up?
ChemSpider Skeleton Search
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35. Comparing ChemSpider Structures
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36. Comparing ChemSpider Structures
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37. Other Searches
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38. Batch Searching
mass and formula
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39. Batch Searching
• Singleton searches are useful but we work
with thousands of masses and formulae!
• Typical questions
– What is the list of chemicals for the formula CxHyOz
– What is the list of chemicals for a mass +/- error
– Can I get chemical lists in Excel files? In SDF files?
– Can I include properties in the download file?
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40. Batch Searching Formula/Mass
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41. Searching batches using MS-Ready
Formula (or mass) searching
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42. Mass
Spectrometry
Related Searches
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43. Find me “related structures”
Formula-Based Search
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44. Select Chemicals of Interest
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45. Find me “related structures”
Based on Structure Similarity
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46. Find me “related structures”
Based on Structure Similarity
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47. Find me “related structures”
Structure Similarity – sort on mass
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48. Chemical Lists
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49. Chemical Lists
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50. EPAHFR: Hydraulic Fracturing
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51. PFAS lists of Chemicals
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52. Research in
Progress
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53. Predicted Mass Spectra
http://cfmid.wishartlab.com/
• MS/MS spectra prediction for ESI+, ESI-, and EI
• Predictions generated and stored for >800,000
structures, to be accessible via Dashboard
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54. Search Expt. vs. Predicted Spectra

55. Search Expt. vs. Predicted Spectra

56. Spectral Viewer Comparison
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57. Prototype Development
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58. Prototype Development
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59. API services and Open Data
• Present API and web services available at
https://actorws.epa.gov/actorws/ but major
redevelopment is underway
• Downloadable data available via the
downloads page
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60. Web Services
https://actorws.epa.gov/actorws/
• Data in UI, JSON and XML format
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61. InChIKey to DTXCIDs
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https://actorws.epa.gov/actorws/dsstox/v02/msready?identifier
=UVOFGKIRTCCNKG-UHFFFAOYSA-N

62. Data and Services
used by the
Community
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63. NORMAN Suspect List Exchange
https://www.norman-network.com/?q=node/236
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64. Integration to MetFrag in place
https://jcheminf.biomedcentral.com/articles/10.1186/s13321-018-0299-2
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65. MassBank mapping to Dashboard
Based on Web Service lookup
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66. Conclusion
• Dashboard access to data for ~875,000 chemicals
• MS-Ready data facilitates structure identification
• Related metadata facilitates candidate ranking
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• Relationship mappings and
chemical lists of great utility
• Dashboard and contents
are one part of the solution
• New developments in
progress, especially API
development, will be very
enabling…

67. Acknowledgements
• IT Development team – especially Jeff
Edwards and Jeremy Dunne
• Chris Grulke for the ChemReg system
• Andrew McEachran (now at Agilent)
• Valery Tkachenko (working on new MS-Ready)
• NERL colleagues – Jon Sobus, Elin Ulrich,
Mark Strynar, Seth Newton, Alex Chao
• Emma Schymanski, LCSB, Luxembourg
• NORMAN Network and all contributors
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68. Contact
Antony Williams
US EPA Office of Research and Development
National Center for Computational Toxicology
EMAIL: Williams.Antony@epa.gov
ORCID: https://orcid.org/0000-0002-2668-4821
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