This presentation was given at a TRIANGLE AREA MASS SPECTOMETRY meeting on 01/29/2019 in Research Triangle Park, North Carolina to provide a general overview of the CompTox Chemicals Dashboard to an audience of mass spectrometrists and people interested in the capabilities of the dashboard for chemical forensics, structure identification etc.

1. Structure Identification Approaches Using the
US-EPA CompTox Chemicals Dashboard to
Support Mass Spectrometry Analyses
Triangle Area Mass Spectrometry
RTP, January 2020
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
Antony Williams
Center for Computational Toxicology and Exposure, US-EPA, RTP, NC
…and an enormous cast of characters

2. Outline
• Quick overview of the dashboard
• Specific data of interest to this audience
(it’s not just Computational Toxicology)
• Support for Mass Spectrometry
• Data quality in the public domain
• Work in progress – prototypes
• A request for help
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3. 2
SEARCH
TOX DATA
BIOACTIVITY
SIMILARITY
READ-ACROSS
PUBMED
BATCH SEARCH
CompTox Chemicals Dashboard
https://comptox.epa.gov/dashboard

4. BASIC Search
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5. Detailed Chemical Pages
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6. Properties, Fate and Transport
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7. Properties, Fate and Transport
e.g. Solubility
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8. Properties, Fate and Transport
e.g. logP
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9. Sources of Exposure to Chemicals
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10. Identifiers to Support Searches
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11. Link Access
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12. Mass Spec Links
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13. NIST WebBook
https://webbook.nist.gov/chemistry/
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14. MassBank of North America
https://mona.fiehnlab.ucdavis.edu
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15. Batch
Searching
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16. Aggregate data for a list of chemicals
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17. Batch Search Names
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Excel
Download

18. Add Other Data of Interest
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19. Chemical Lists of
Interest…
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20. 225 Chemical Lists (and growing)
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21. “Volatilome” Human Breath
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22. “Volatilome” Saliva
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23. PFAS lists of Chemicals
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24. Building a “reference” PFAS list
• PFAS structure list (PFASSTRUCT)
is expanded from public databases, EPA
agency lists and literature
• Approaching ~7000 structures – 98.8% have
associated CAS Numbers
• Compare with PubChem 220,720 structures
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25. Formula Search can find isomers
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26. Active expansion of the PFAS list
From 2 to 8 variants of PFOS
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27. Disinfection By-Products
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28. Mycotoxins
• Two lists: 328 and 88 members
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29. Vomitoxin
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30. BIG databases are GREAT!
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1 0 4
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1 0 7
1 0 8
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ChemicalSubstances
• Thanks to all of the public database efforts
• So much benefit from what’s been done
• There are hundreds of them at this point…

31. Vomitoxin - ChemSpider
• 19 “Vomitoxins” – 3 isotopically labeled
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32. Vomitoxin – PubChem
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• 33 unique InChI Keys

33. PubChem – “virtual chemistry”
• Other databases grow quickly…a lot of “virtual
chemistry” and “make on demand” compounds.
Vomitoxin has 7 ZINC stereoforms.
• The Dashboard database grows slowly (next
release is +20k chemicals in 6 months)
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34. ChemSpider – lots of virtuals???
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• 52 million chemicals
from one vendor

35. Taxol: 79 Results
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36. Data Quality is important
• Data quality in free web-based databases!
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37. We’re still cleaning data too
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38. Tire Crumb Rubber (298)
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39. Terpenes in Vape (37)
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40. Hydraulic Fracturing (1640)
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41. Opioids and Metabolites (160)
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42. “MS-ready”
structures
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43. 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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44. 43

45. MS-Ready Mappings from
Details Page
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46. MS-Ready Mappings Set of 20
substances for “PFOS”
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47. Mass and Formula
Searching
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48. Advanced Searches
Mass Search
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49. Advanced Searches
Mass Search
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50. MS-Ready Structures for
Formula Search
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51. MS-Ready Mappings
• EXACT Formula: C10H16N2O8: 3 Hits
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52. MS-Ready Mappings
• Same Input Formula: C10H16N2O8
• MS Ready Formula Search: 125 Chemicals
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53. MS-Ready Mappings
• 125 chemicals returned in total
– 8 of the 125 are single component chemicals
– 3 of the 8 are isotope-labeled
– 3 are neutral compounds and 2 are charged
• Multiple components, stereo, isotopes and
charge all collapsed and mapped through
MS-Ready
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54. Batch Searching
mass and formula
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55. 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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56. Batch Searching Formula/Mass
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57. Searching batches using MS-Ready
Formula (or mass) searching
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58. Batch Search in specific lists
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59. Benefits of bringing it all together
• The true dashboard benefit is integration
• Rank potential candidates for toxicity using
available data – hazard, exposure, in vitro
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60. Candidate ranking
using metadata
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61. 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

62. Data Streams for Ranking
• CompTox Dashboard Data Sources
• PubChem Data Source Count
• PubMed Reference Count
• Toxcast in vitro bioactivity
• Presence in CPDat database
• OPERA PhysChem Properties
• Other possibilities – predicted media
occurrence, frequency of InChIs online

63. Search 228.115 +/- 5.0 ppm
234 single component chemicals
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64. Search 228.115 +/- 5.0 ppm
234 single component chemicals
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65. The original ChemSpider work
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66. 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?

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

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

70. 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

71. “UVCB”
Chemicals
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72. UVCB Chemicals
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73. UVCBs challenge in non-target analysis
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Homologue screening plots from
Swiss Wastewater (Schymanski et al
2014, left) and Novi Sad (right)
o Complex mixtures (UVCBs) are a huge
and very challenging part of the
unknowns in many environmental
samples

74. Public TSCA Inventory on Dashboard
31,460 Chemicals (1/24/2020)
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75. Many Chemicals are “Complex”
>14000 chemicals are UVCBs
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76. “Markush Structures”
https://en.wikipedia.org/wiki/Markush_structure
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77. How to represent complexity?
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78. In the Dashboard
Abstract
Sifter
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79. Literature Searching
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80. Literature Searching
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81. Abstract Sifter for Excel
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82. Work in
Progress
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83. List Registration Activities
• Registering and curating numerous lists
– NIST library of chemicals –clean up especially around
stereochemical representation
– United States Geological Survey chemicals in water
– Scientific Working Group for the Analysis of Seized Drugs
– Synthetic Cannabinoids
– Blood Exposome Database
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84. Blood Exposome Curation
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• Blood exposome data collection from Barupal and
Fiehn. Great work and we reviewing.
• Aggregating large datasets is CHALLENGING
• Comparing with our “Abstract Sifter” approach
• We will iterate into a dashboard form..

85. Prototype Work in Progress
• CFM-ID
– Viewing and Downloading pre-predicted spectra
– Search spectra against the database
• Structure/substructure/similarity search
• Access to API and web services
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86. 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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87. Search Expt. vs. Predicted Spectra

88. Search Expt. vs. Predicted Spectra

89. Spectral Viewer Comparison
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90. Predicted Data Already Public
Publication and Data Files
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https://epa.figshare.com/articles/CFM-ID_Paper_Data/7776212/1

91. Published: Chao et al
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92. Prototype Development
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93. CASMI 2012-2017 revisited
• Application of metadata candidate ranking
and CFM-ID to all five years of CASMI data
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94. Method Amenability Prediction
Charlie Lowe
Why?
• Chromatography-mass
spectrometry can be LC or GC
• Which phase is more appropriate
for which chemicals?

95. Ongoing Work
• Data sources to date
• Massbank of North America
• 9,275 chemicals for non-derivatized GC
• 846 chemicals for derivatized GC
• 816 chemicals for APCI+
• 454 chemicals for APCI-
• 4,907 chemicals for ESI+
• 3,430 chemicals for ESI-
• EPA Non-targeted Analysis Collaborative Trial (ENTACT)
• 886 chemicals for non-derivatized GC
• 44 chemicals for derivatized GC
• 774 chemicals for APCI+
• 431 chemicals for APCI-
• 1,113 chemicals for ESI+
• 648 chemicals for ESI-

96. TMAP Visualization of MoNA GC Data

97. Future Work: Add database of
Collision Cross Section Prediction
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98. API services and Open Data
• Web Services https://actorws.epa.gov/actorws/
• Data sets also available for download..
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99. Web Services
https://actorws.epa.gov/actorws/
• Data in UI, JSON and XML format
• Our services are free of course..
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100. InChIKey to DTXCIDs
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https://actorws.epa.gov/actorws/dsstox/v02/msready?identifier
=UVOFGKIRTCCNKG-UHFFFAOYSA-N

101. Data and Services
used by the
Community
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102. NORMAN Suspect List Exchange
https://www.norman-network.com/?q=node/236
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103. Integration to MetFrag in place
https://jcheminf.biomedcentral.com/articles/10.1186/s13321-018-0299-2
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104. MassBank mapping to Dashboard
Based on Web Service lookup
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105. Conclusion
• Dashboard access to data for ~875,000 chemicals
(~895k in the Spring Release)
• MS-Ready data facilitates structure identification
• Related metadata facilitates candidate ranking
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• Relationship mappings and
chemical lists of great utility
• Curation and mutual
sharing of chemical lists is
important (e.g. NORMAN)

106. ILS
Kamel Mansouri
EPA ORD
Ann Richard
Chris Grulke
Jeremy Dunne
Jeff Edwards
Grace Patlewicz
Alex Chao
Kristin Isaacs
Charles Lowe
James McCord
Seth Newton
Katherine Phillips
Jon Sobus
Mark Strynar
Elin Ulrich
Joach Pleil
GDIT
Ilya Balabin
Tom Transue
Tommy Cathey
Acknowledgements
TEAMS
IT Development Team
Curation Team
Collaborators
Emma Schymanski
NORMAN Network
Andrew McEachran

107. MANY presentations online
https://tinyurl.com/w5hqs55
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108. Contact
Antony Williams
CCTE, US EPA Office of Research and Development,
Williams.Antony@epa.gov
ORCID: https://orcid.org/0000-0002-2668-4821
107
https://doi.org/10.1186/s13321-017-0247-6