The US-EPA CompTox Chemicals Dashboard – a key player in the domain of Open Science, Cheminformatics, and Online Databases supporting Non-Targeted Screening
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The US-EPA CompTox Chemicals Dashboard is a comprehensive tool designed to support open science and cheminformatics, facilitating non-targeted screening and data access for over 875,000 chemicals. The dashboard offers features such as mass spectrometry support, advanced chemical searches, and integration of various data sources for toxicity ranking while continuously improving the data quality and quantity. Ongoing developments include prototypes for predicted mass spectra and APIs to enhance data accessibility for the research community.
The US-EPA CompTox Chemicals Dashboard – a key player in the domain of Open Science, Cheminformatics, and Online Databases supporting Non-Targeted Screening
- 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
- 6. Properties, Fate and Transport 5
- 7. Sources of Exposure to Chemicals 6
- 8. Identifiers to Support Searches 7
- 12. MassBank of North America https://mona.fiehnlab.ucdavis.edu 11
- 14. Aggregate data for a list of chemicals 13
- 16. Add Other Data of Interest 15
- 18. 225 Chemical Lists (and growing) 17
- 20. Tire Crumb Rubber (298) 19
- 22. Opioids and Metabolites (160) 21
- 24. PFAS lists of Chemicals 23
- 25. Mycotoxins • Two lists: 328 and 88 members 24
- 26. BIG databases are GREAT! P u b C h e m C A S R e g is try C h e m S p id e r E P A D S S T o x B lo o d E x p o s o m e 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
- 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
- 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
- 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
- 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
- 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
- 67. How to represent complexity? 66
- 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
- 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
- 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
- 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