High resolution mass spectrometry (HRMS) and non-targeted analysis (NTA) are advancing the identification of emerging contaminants in environmental matrices, improving the means by which exposure analyses can be conducted. However, confidence in structure identification of unknowns in NTA presents challenges to analytical chemists. Structure identification requires integration of complementary data types such as reference databases (either commercial or open databases), fragmentation prediction tools, and retention time prediction models. One goal of our research is to optimize and implement structure identification functionality within the US EPA’s CompTox Chemicals Dashboard, an open chemistry resource and web application containing data for ~900,000 substances. Database searching using mass or formula-based inputs has been optimized for structure identification using “MS-Ready Structures”: de-salted, stripped of stereochemistry, and mixture separated to replicate the form of a chemical observed via HRMS. Functionality to conduct batch searching of molecular formulae and monoisotopic masses has also been implemented. While the increasing number of free online databases are of value to support chemical structure verification and elucidation there are known issues regarding data quality and careful data curation is a very necessary part of the development of these resources. This presentation will provide an overview of our latest enhancements to the dashboard to support mass spectrometry, incorporation of specific datasets (i.e. to support breath research and household dust analysis) and the value of metadata and predicted fragmentation spectral matching to support structure identification. This abstract does not necessarily represent the views or policies of the U.S. Environmental Protection Agency.

1. The US-EPA CompTox Chemicals Dashboard
– a key player in the domain of Open Science,
Cheminformatics, and Online Databases
supporting Non-Targeted Screening
Pittcon, March 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 J. Williams, Elin Ulrich, Joachim Pleil,
Alex Chao, Charles Lowe, Andrew McEachran*
and Jon Sobus
Center for Computational Toxicology and Exposure, US-EPA, RTP, NC
*Agilent Inc.
…

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
1

3. 2
SEARCH
TOX DATA
BIOACTIVITY
SIMILARITY
READ-ACROSS
PUBMED
BATCH SEARCH
CompTox Chemicals Dashboard
https://comptox.epa.gov/dashboard

4. BASIC Search
3

5. Detailed Chemical Pages
4

6. Properties, Fate and Transport
5

7. Sources of Exposure to Chemicals
6

8. Identifiers to Support Searches
7

9. Link Access
8

10. Mass Spec Links
9

11. NIST WebBook
https://webbook.nist.gov/chemistry/
10

12. MassBank of North America
https://mona.fiehnlab.ucdavis.edu
11

13. Batch
Searching
12

14. Aggregate data for a list of chemicals
13

15. Batch Search Names
14
Excel
Download

16. Add Other Data of Interest
15

17. Chemical Lists of
Interest…
16

18. 225 Chemical Lists (and growing)
17

19. “Volatilome” Human Breath
18

20. Tire Crumb Rubber (298)
19

21. Hydraulic Fracturing (1640)
20

22. Opioids and Metabolites (160)
21

23. Disinfection By-Products
22

24. PFAS lists of Chemicals
23

25. Mycotoxins
• Two lists: 328 and 88 members
24

26. BIG databases are GREAT!
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1 0 4
1 0 5
1 0 6
1 0 7
1 0 8
1 0 9
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…

27. Data Quality is important
• Data quality in free web-based databases!
26

28. Vomitoxin
27

29. Vomitoxin - ChemSpider
• 19 “Vomitoxins” – 3 isotopically labeled
28

30. Vomitoxin – PubChem
29
• 33 unique InChI Keys

31. 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)
30

32. “MS-ready”
structures
31

33. 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
32

34. 33

35. MS-Ready Mappings from
Details Page
34

36. MS-Ready Mappings Set of 20
substances for “PFOS”
35

37. Mass and Formula
Searching
36

38. Advanced Searches
Mass Search
37

39. Advanced Searches
Mass Search
38

40. MS-Ready Structures for
Formula Search
39

41. MS-Ready Mappings
• EXACT Formula: C10H16N2O8: 3 Hits
40

42. MS-Ready Mappings
• Same Input Formula: C10H16N2O8
• MS Ready Formula Search: 125 Chemicals
41

43. 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
42

44. Batch Searching
mass and formula
43

45. 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?
44

46. Batch Searching Formula/Mass
45

47. Searching batches using MS-Ready
Formula (or mass) searching
46

48. Batch Search in specific lists
47

49. Benefits of bringing it all together
• The true dashboard benefit is integration
• Rank potential candidates for toxicity using
available data – hazard, exposure, in vitro
48

50. Candidate ranking
using metadata
49

51. Data Source Ranking of
“known unknowns”
50
• 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

52. 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

53. Search 228.115 +/- 5.0 ppm
234 single component chemicals
52

54. Search 228.115 +/- 5.0 ppm
234 single component chemicals
53

55. The original ChemSpider work
54

56. Is a bigger database better?
55
• ChemSpider was 26 million chemicals for
the original work
• Much BIGGER today
• Is bigger better??
• Are there other metadata to use for ranking?

57. Comparing Search Performance
56
• When dashboard contained 720k chemicals
• Only 3% of ChemSpider size
• What was the comparison in performance?

58. SAME dataset for comparison
57

59. How did performance compare?
58
For the same 162 chemicals,
Dashboard outperforms
ChemSpider for both Mass and
Formula Ranking

60. Identification ranks for 1783 chemicals
using multiple data streams
59
DS: Data Sources
PC: PubChem
PM: PubMed
STOFF: DB
KEMI: DB
Data Sources alone
rank ~75% of the
chemicals as Top Hit

61. “UVCB”
Chemicals
60

62. UVCB Chemicals
61

63. UVCBs challenge in non-target analysis
62
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

64. Public TSCA Inventory on Dashboard
31,460 Chemicals (1/24/2020)
63

65. Many Chemicals are “Complex”
>14000 chemicals are UVCBs
64

66. “Markush Structures”
https://en.wikipedia.org/wiki/Markush_structure
65

67. How to represent complexity?
66

68. Work in
Progress
67

69. 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
68

70. 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
• Integration to EPA “Chemical Transformation
Simulator”
69

71. 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
70

72. Search Expt. vs. Predicted Spectra

73. Search Expt. vs. Predicted Spectra

74. Spectral Viewer Comparison
73

75. Example match
74

76. Predicted Data Already Public
Publication and Data Files
75
https://epa.figshare.com/articles/CFM-ID_Paper_Data/7776212/1

77. Published: Alex Chao et al
76

78. Prototype Development
77

79. CASMI 2012-2017 revisited
• Application of metadata candidate ranking
and CFM-ID to all five years of CASMI data
78

80. Method Amenability Prediction
Charlie Lowe
Why?
• Chromatography-mass
spectrometry can be LC or GC
• Which phase is more appropriate
for which chemicals?

81. 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-

82. TMAP Visualization of MoNA GC Data

83. API services and Open Data
• Web Services https://actorws.epa.gov/actorws/
• Data sets also available for download..
82

84. Web Services
https://actorws.epa.gov/actorws/
• Data in UI, JSON and XML format
• Our services are free of course..
83

85. InChIKey to DTXCIDs
84
https://actorws.epa.gov/actorws/dsstox/v02/msready?identifier
=UVOFGKIRTCCNKG-UHFFFAOYSA-N

86. Data and Services
used by the
Community
85

87. NORMAN Suspect List Exchange
https://www.norman-network.com/?q=node/236
86

88. Integration to MetFrag in place
https://jcheminf.biomedcentral.com/articles/10.1186/s13321-018-0299-2
87

89. MassBank mapping to Dashboard
Based on Web Service lookup
88

90. 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
89
• Relationship mappings and
chemical lists of great utility
• Curation and mutual
sharing of chemical lists is
important (e.g. NORMAN)

91. ILS
Kamel Mansouri
EPA ORD
Ann Richard
Chris Grulke
John Wambaugh
Jeremy Dunne
Jeff Edwards
Grace Patlewicz
Alex Chao
Kristin Isaacs
Charles Lowe
James McCord
Seth Newton
Katherine Phillips
Tom Purucker
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 &
the NORMAN Network

92. Contact
Antony Williams
CCTE, US EPA Office of Research and Development,
Williams.Antony@epa.gov
ORCID: https://orcid.org/0000-0002-2668-4821
91
https://doi.org/10.1186/s13321-017-0247-6