There is a growing need for rapid chemical screening and prioritization to inform regulatory decision-making on thousands of chemicals in the environment. We have previously used high-resolution mass spectrometry to examine household vacuum dust samples using liquid chromatography time-of-flight mass spectrometry (LC-TOF/MS). Using a combination of exact mass, isotope distribution, and isotope spacing, molecular features were matched with a list of chemical formulas from the EPA’s Distributed Structure-Searchable Toxicity (DSSTox) database. This has further developed our understanding of how openly available chemical databases, together with the appropriate searches, could be used for the purpose of compound identification. We report here on the utility of the EPA’s iCSS Chemistry Dashboard for the purpose of compound identification using searches against a database of over 720,000 chemicals. We also examine the benefits of QSAR prediction for the purpose of retention time prediction to allow for alignment of both chromatographic and mass spectral properties. This abstract does not reflect U.S. EPA policy.

1. The EPA iCSS Chemistry Dashboard to
Support Compound Identification Using High
Resolution Mass Spectrometry Data
Antony J. Williams†, Andrew McEachran, Jon Sobus,
Chris Grulke, Jennifer Smith, Michelle Krzyzanowski,
Jordan Foster and Jeff Edwards
National Center for Computational Toxicology
U.S. Environmental Protection Agency, RTP, NC
August 21-25, 2016
ACS Fall Meeting, Philadelphia, PA
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. Who is NCCT?
• National Center for Computational Toxicology – part of EPA’s
Office of Research and Development
• Research driven by EPA’s Chemical Safety for Sustainability
Research Program
– Develop new approaches to evaluate the safety of chemicals
– Integrate advances in biology, biotechnology, chemistry, exposure
science and computer science
• Goal - To identify chemical exposures that may disrupt
biological processes and cause adverse outcomes.
1

3. Our Dashboard Applications
• Some of our Web-based Applications
2

4. Introducing Our Latest Dashboard
https://comptox.epa.gov
3
• >720,000 chemicals
• >10 years assembling data

5. Bisphenol A
4

6. Physicochemical Properties
5

7. Bioassay Screening Data
6

8. Functional Use and Composition
7

9. Advanced MS Searches
8

10. Monoisotopic Mass Search
9

11. Monoisotopic Mass Search
10
Found 344 results for '215.096 ± 0.005 amu'

12. Formula Search
11

13. Formula Search
12
Found 8 results for 'C8H14ClN5'

14. Formula Searching
Formulae matching Bisphenol A
13

15. Formula Search Results
14

16. Download to Excel
15

17. Download as SDF file
16

18. SDF file downloaded to desktop
17

19. Rank-Ordering of “Known-Unknowns”
using ChemSpider
18

20. Comparing Performance
19
721k structures

21. Does the Dashboard Add Value?
• Remember:
– Focus on high quality data and curation
– Data sources include EPA data sources and a focus on
environmental chemistry
• No “dilution” by chemical vendors
20

22. Dilution Example…
Morphine Skeleton
21

23. Bisphenol A as an example
ChemSpider: 1564 Structures
22

24. Bisphenol A as an example
Dashboard: 215 Structures
23

25. Chemical Identification
Dashboard vs ChemSpider
Sorted by number of references (ChemSpider) or data sources (Dashboard)
Monoisotopic Mass (+/- 0.005 amu) Search
Position of compound sorted
Source of List # of
Compounds
Search Tool Mean
Position
Median
Position #1 #2 #3 #4 #5+
McEachran et al
Wastewater
34 ChemSpider 1.8 1 28 5 0 0 1
Dashboard 1.3 1 31 2 0 0 1
Misc. NTA Compounds 13 ChemSpider 2 1 7 5 0 0 1
Dashboard 1.7 1 10 2 0 0 1
Bade et al (2016) 19 ChemSpider 2.1 1 11 2 5 0 1
Dashboard 1.6 1 12 3 3 1 0
Rager et al (2016) 24 ChemSpider 2.25 1 15 2 1 2 4
Dashboard 1.08 1 22 2 0 0 0

26. Dashboard vs ChemSpider
Ranking Summary
Mass-based Searching Formula Based Searching
Dashboard ChemSpider Dashboard ChemSpider
Cumulative Average
Position 1.3 2.2 1.2 1.4
% in #1 Position 85% 70% 88% 80%
• Selected peer-reviewed publications
• 162 total individual chemicals in search

27. ChemSpider 6926 Results!!!
26
Tacedinaline
Methyl Red
C.I Disperse
Yellow 3

28. Using Functional Use
to Sort Candidates
27
Anti-cancer Drug
Microbiological
Indicator Dye
Textile/Product Dye

29. Same top hits – different ranking
90 hits only versus 6926 hits
28
18
17
4Tacedinaline
Methyl Red
C.I Disperse
Yellow 3

30. Dashboard: External Links to
Analytical Methods
29

31. National Environmental Methods Index
30

32. RSC Analytical Abstracts
31

33. Integrated Google
Chemical Searches
32

34. Google Chemical Searches
Enhanced with Query Terms
33

35. Non-Targeted Analysis Research
- 1 Dust Sample
- Negative Ionization Mode
- 300 Extracted “Molecular Features”
1) Prioritize “Molecular Features”
2) Correctly assign formulas
3) Correctly assign structures
4) Determine chemical sources
5) Predict chemical concentrations
C17H19NO3 12 µg/g
(1)
(2) (3) (4) (5)
What is contained in house
dust, waste streams etc???

36. Previous Work with Suspect-Screening
The dashboard is being enhanced to
support Non-targeted Analysis

37. Future Work
• Presently researching rank-ordering based
on other criteria – Pubmed
• Additional links to methods – CDC NIOSH
• Links to Mass Spec databases – Thermo’s
mzCloud, Massbank. Metlin etc.
• Consider predicting metabolites and
degradants
• Searching based on “MS-ready” structures
36

38. “MS Ready” structures
• Many compounds are salts – searches
should be on the “neutral form”
• Need to search for adducts (+Na, +K,
+NH4), decarboxylation, loss of water etc.
37

39. Conclusions
• Dashboard support for MS is focused on NTA
research – related to chemical exposure
• Dashboard outperforms ChemSpider for
ranking chemicals of environmental concern
• New searches developed with Non-targeted
Analysis in mind - new rank-ordering
approaches in development
38

40. Acknowledgements
EPA NCCT
Chris Grulke
Jeff Edwards
Ann Richard
Jordan Foster
Jennifer Smith
Andrew McEachran*
Michelle Krzyzanowski
EPA NERL
Jon Sobus
* = ORISE Participant