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What chemicals constitute the Exposome?
Accessing data via the US EPA’s
CompTox Chemicals Dashboard
ISES
September 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
1
SEARCH
TOX DATA
BIOACTIVITY
SIMILARITY
READ-ACROSS
PUBMED
BATCH SEARCH
CompTox Chemicals Dashboard
https://comptox.epa.gov/dashboard
How many chemicals to consider?
• Dashboard content is small but focused
curated content
• Dashboard ~900,000
• ChemSpider ~90,000,000
• PubChem ~111,000,000
• CAS ~ 165,000,000
2
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…
What chemicals constitute the Exposome?
• What constitutes the exposome is, of
course, difficult to answer.
• Focused chemical list expansion highlights
chemical classes of interest – chemicals in
commerce, pesticides, cosmetics, PFAS
4
Aspects of the Dashboard Data
No “large library” dilution
• The top 6 data sources on ChemSpider
are vendor collections
5
Data Quality Dilution
Vomitoxin
6
Vomitoxin - ChemSpider
• 19 “Vomitoxins” – 3 isotopically labeled
7
Vomitoxin – PubChem
8
• 33 unique InChI Keys
PubChem – “virtual chemistry”
Large Databases – collapse
• Lots of “virtual chemistry” and “MODs”
• Vomitoxin has 7 ZINC stereoforms.
• Care is needed to choose subsets of interest
and Emma Schymanski et al are doing this
9
Chemical
Lists
10
~275 Chemical Lists (and growing)
11
Public TSCA Inventory on Dashboard
33,364 Chemicals (9/6/2020)
12
Hydraulic Fracturing (1640)
13
Tire Crumb Rubber (298)
14
Disinfection By-Products
15
PFAS lists of Chemicals
16
PFAS Structure List (8163)
17
Blood Exposome
Curation in Process
18
• Blood exposome data collection from Barupal
and Fiehn. We are reviewing and curating.
“UVCB”
Chemicals
19
UVCB Chemicals
20
Public TSCA Inventory on Dashboard
31,460 Chemicals (1/24/2020)
21
Many Chemicals are “Complex”
>14000 chemicals are UVCBs
22
Representing complexity
Markush representations
23
Chemicals
in Commerce
24
Factotum Database
Consumer Products Database
25
Factotum Database
Consumer Products Database
26
Sources of Exposure to Chemicals
27
Candidate ranking
using metadata
28
Data Source Ranking of
“known unknowns”
29
• 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
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
Comparing Search Performance
31
• When dashboard contained 720k chemicals
• Only 3% of ChemSpider size
• What was the comparison in performance?
SAME dataset for comparison
32
How did performance compare?
33
For the same 162 chemicals,
Dashboard outperforms
ChemSpider for both Mass and
Formula Ranking
“MS-ready” structures
supporting searches
34
35
“MS-Ready” Structures
Batch
Searching
36
Batch Search Names
37
Excel
Download
Add Other Data of Interest
38
Batch Searching Formula/Mass
39
Searching batches using MS-Ready
Formula (or mass) searching
40
Benefits of bringing it all together
• The true dashboard benefit is integration
• Rank potential candidates for toxicity using
available data – hazard, exposure, in vitro
41
Conclusion
• Dashboard access to data for ~882,000 chemicals
• Chemical Lists support exposome analysis
• Related metadata facilitates candidate ranking
42
• Relationship mappings and
chemical lists of great utility
• Curation and mutual
sharing of chemical lists is
important (e.g. NORMAN)
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
Tom Transue
Tommy Cathey
Acknowledgements
TEAMS
IT Development Team
Curation Team
Collaborators
Emma Schymanski
NORMAN Network
Andrew McEachran

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