Adding complex expert knowledge into chemical database and transforming surfactants in wastewater
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This document discusses adding complex expert knowledge about surfactants to chemical databases to aid in the identification of unknown compounds from wastewater samples. It describes how over 60% of peaks detected by high resolution mass spectrometry in wastewater samples are unknown. Literature data on surfactant properties and spectra were compiled and added to databases to support the identification of homologous series and complex mixtures present. A list of surfactants was developed and incorporated into toxicity databases to enable in silico modeling and computational mass spectrometry approaches to aid non-target screening. International collaboration is helping to establish a global exchange of suspect lists to support the identification of unknown contaminants.
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Identification of unknowns in mass spectrometry based non-targeted analyses (NTA) requires the integration of complementary pieces of data to arrive at a confident, consensus structure. Researchers use chemical reference databases, spectral matching, fragment prediction tools, retention time prediction tools, and a variety of other data to arrive at tentative, probable, and confirmed, if possible, identifications. With the diverse, robust data contained within the US EPA’s CompTox Chemistry Dashboard (https://comptox.epa.gov), the goal of this research is to identify and implement a harmonized identification tool and workflow using previously generated chemistry data. Data has been compiled from product use, functional use prediction models, environmental media occurrence prediction models, and PubMed references, among other sources. We will report on our development of a visualization tool whereby users can visualize the relative contribution of identification-based metrics on a list of candidate structures and observe the greatest likelihood of occurrence. These data and visualization tools support NTA identification via the Dashboard and demonstrate an open, accessible tool for all users of HRMS data. This abstract does not necessarily represent the views or policies of the U.S. Environmental Protection Agency.Structure identification by Mass Spectrometry Non-Targeted Analysis using the...
Structure identification by Mass Spectrometry Non-Targeted Analysis using the...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
Cheminformatics methods form an essential basis for providing analytical scientists with access to data, algorithms and workflows. There are an increasing number of free online databases (compound databases, spectral libraries, data repositories) and a rich collection of software approaches that can be used to support automated structure verification and elucidation, specifically for Nuclear Magnetic Resonance (NMR) and Mass Spectrometry (MS). This presentation will provide an overview of freely available data, tools, databases and approaches available to support chemical structure verification and elucidation and highlight some of the known issues regarding data quality and suggest approaches for resolving some of the issues. The importance of structure and spectral standards for data exchange will be discussed, especially with regard to how spectral data can be made openly available to the community via online tools and through scientific publishing. This work does not necessarily reflect U.S. EPA policy.Overview of open resources to support automated structure verification and e...
Overview of open resources to support automated structure verification and e...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
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, fragmentation prediction tools, and retention time prediction models. The goal of this research is to optimize and implement structure identification functionality within the US EPA’s CompTox Chemistry Dashboard, an open chemistry resource and web application containing data for ~760,000 substances. Rank-ordering the number of sources associated with chemical records within the Dashboard (Data Source Ranking) improves the identification of unknowns by bringing the most likely candidate structures to the top of a search results list. Database searching has been further optimized with the generation of MS-Ready Structures. MS-Ready structures are 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 was designed and released to improve searching efforts. Finally, a scoring-based identification scheme was developed, optimized, and surfaced via the Dashboard using multiple data streams contained within the database underlying the Dashboard. The scoring-based identification scheme improved the identification of unknowns over previous efforts using data source ranking alone. Combining these steps within an open chemistry resource provides a freely available software tool for structure identification and NTA. This abstract does not necessarily represent the views or policies of the U.S. Environmental Protection Agency.Using the US EPA’s CompTox Chemistry Dashboard for structure identification a...
Using the US EPA’s CompTox Chemistry Dashboard for structure identification a...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
Chemical risk assessment is both time-consuming and difficult because it requires the assembly of data for chemicals generally distributed across multiple sources. The US EPA CompTox Chemistry Dashboard is a publicly accessible web-based application providing access to various data streams on ~760,000 chemical substances. These data include experimental and predicted physicochemical property data, bioassay screening data associated with the ToxCast program, consumer product and functional use information and a myriad of related data of value to environmental scientists and toxicologists. At this stage of development, the public dashboard provides access to almost 20 predicted physicochemical and environmental fate and transport endpoints with full transparency in terms of model performance. Experimental and predicted human and ecological toxicity data are also available, as are in vitro to in vivo extrapolation dosimetry predictions and predicted exposure and functional use. In parallel to the CompTox Chemistry Dashboard we are developing RapidTox, a web-based application that enables a rapid, flexible and transparent prioritization process for sets of chemicals using several previously used workflows focused on scoring of traditional risk metrics and the inclusion of alternative hazard and exposure estimates. This presentation will give an overview of the CompTox Chemistry Dashboard, RapidTox, our approaches to building transparent and open prediction models, and our efforts to provide access to real time predictions. This abstract does not necessarily represent U.S. EPA policy.US EPA CompTox Chemistry Dashboard as a source of data to fill data gaps for ...
US EPA CompTox Chemistry Dashboard as a source of data to fill data gaps for ...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
EPA’s National Center for Computational Toxicology is developing automated workflows for curating large databases and providing accurate linkages of data to chemical structures, exposure and hazard information. The data are being made available via the EPA’s CompTox Chemistry Dashboard (https://comptox.epa.gov/dashboard), a publicly accessible website providing access to data for almost 760,000 chemical substances, the majority of these represented as chemical structures. The web application delivers a wide array of computed and measured physicochemical properties, in vitro high-throughput screening data and in vivo toxicity data as well as integrated chemical linkages to a growing list of literature, toxicology, and analytical chemistry websites. In addition, several specific search types are in development to directly support the mass spectroscopy non-targeted screening community, who are generating important data for detecting and assessing environmental exposures to chemicals contained within DSSTox. The application provides access to segregated lists of chemicals that are of specific interests to relevant stakeholders including, for example, scientists interested in algal toxins and hydraulic fracturing chemicals. This presentation will provide an overview of the challenges associated with the curation of data from EPA’s December 2016 Hydraulic Fracturing Drinking Water Assessment Report that represented chemicals reported to be used in hydraulic fracturing fluids and those found in produced water. The data have been integrated into the dashboard with a number of resulting benefits: a searchable database of chemical properties, with hazard and exposure predictions, and open literature. The application of the dashboard to support mass spectrometry non-targeted analysis studies will also be reviewed. This abstract does not reflect U.S. EPA policy.Accessing information for chemicals in hydraulic fracturing fluids using the ...
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Development of a Tool for Systematic Integration of Traditional and New Appro...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
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Identification of unknowns in mass spectrometry based non-targeted analyses (NTA) requires the integration of complementary pieces of data to arrive at a confident, consensus structure. Researchers use chemical reference databases, spectral matching, fragment prediction tools, retention time prediction tools, and a variety of other data to arrive at tentative, probable, and confirmed, if possible, identifications. With the diverse, robust data contained within the US EPA’s CompTox Chemistry Dashboard (https://comptox.epa.gov), the goal of this research is to identify and implement a harmonized identification tool and workflow using previously generated chemistry data. Data has been compiled from product use, functional use prediction models, environmental media occurrence prediction models, and PubMed references, among other sources. We will report on our development of a visualization tool whereby users can visualize the relative contribution of identification-based metrics on a list of candidate structures and observe the greatest likelihood of occurrence. These data and visualization tools support NTA identification via the Dashboard and demonstrate an open, accessible tool for all users of HRMS data. This abstract does not necessarily represent the views or policies of the U.S. Environmental Protection Agency.Structure identification by Mass Spectrometry Non-Targeted Analysis using the...
Structure identification by Mass Spectrometry Non-Targeted Analysis using the...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
Cheminformatics methods form an essential basis for providing analytical scientists with access to data, algorithms and workflows. There are an increasing number of free online databases (compound databases, spectral libraries, data repositories) and a rich collection of software approaches that can be used to support automated structure verification and elucidation, specifically for Nuclear Magnetic Resonance (NMR) and Mass Spectrometry (MS). This presentation will provide an overview of freely available data, tools, databases and approaches available to support chemical structure verification and elucidation and highlight some of the known issues regarding data quality and suggest approaches for resolving some of the issues. The importance of structure and spectral standards for data exchange will be discussed, especially with regard to how spectral data can be made openly available to the community via online tools and through scientific publishing. This work does not necessarily reflect U.S. EPA policy.Overview of open resources to support automated structure verification and e...
Overview of open resources to support automated structure verification and e...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
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, fragmentation prediction tools, and retention time prediction models. The goal of this research is to optimize and implement structure identification functionality within the US EPA’s CompTox Chemistry Dashboard, an open chemistry resource and web application containing data for ~760,000 substances. Rank-ordering the number of sources associated with chemical records within the Dashboard (Data Source Ranking) improves the identification of unknowns by bringing the most likely candidate structures to the top of a search results list. Database searching has been further optimized with the generation of MS-Ready Structures. MS-Ready structures are 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 was designed and released to improve searching efforts. Finally, a scoring-based identification scheme was developed, optimized, and surfaced via the Dashboard using multiple data streams contained within the database underlying the Dashboard. The scoring-based identification scheme improved the identification of unknowns over previous efforts using data source ranking alone. Combining these steps within an open chemistry resource provides a freely available software tool for structure identification and NTA. This abstract does not necessarily represent the views or policies of the U.S. Environmental Protection Agency.Using the US EPA’s CompTox Chemistry Dashboard for structure identification a...
Using the US EPA’s CompTox Chemistry Dashboard for structure identification a...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
Chemical risk assessment is both time-consuming and difficult because it requires the assembly of data for chemicals generally distributed across multiple sources. The US EPA CompTox Chemistry Dashboard is a publicly accessible web-based application providing access to various data streams on ~760,000 chemical substances. These data include experimental and predicted physicochemical property data, bioassay screening data associated with the ToxCast program, consumer product and functional use information and a myriad of related data of value to environmental scientists and toxicologists. At this stage of development, the public dashboard provides access to almost 20 predicted physicochemical and environmental fate and transport endpoints with full transparency in terms of model performance. Experimental and predicted human and ecological toxicity data are also available, as are in vitro to in vivo extrapolation dosimetry predictions and predicted exposure and functional use. In parallel to the CompTox Chemistry Dashboard we are developing RapidTox, a web-based application that enables a rapid, flexible and transparent prioritization process for sets of chemicals using several previously used workflows focused on scoring of traditional risk metrics and the inclusion of alternative hazard and exposure estimates. This presentation will give an overview of the CompTox Chemistry Dashboard, RapidTox, our approaches to building transparent and open prediction models, and our efforts to provide access to real time predictions. This abstract does not necessarily represent U.S. EPA policy.US EPA CompTox Chemistry Dashboard as a source of data to fill data gaps for ...
US EPA CompTox Chemistry Dashboard as a source of data to fill data gaps for ...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
EPA’s National Center for Computational Toxicology is developing automated workflows for curating large databases and providing accurate linkages of data to chemical structures, exposure and hazard information. The data are being made available via the EPA’s CompTox Chemistry Dashboard (https://comptox.epa.gov/dashboard), a publicly accessible website providing access to data for almost 760,000 chemical substances, the majority of these represented as chemical structures. The web application delivers a wide array of computed and measured physicochemical properties, in vitro high-throughput screening data and in vivo toxicity data as well as integrated chemical linkages to a growing list of literature, toxicology, and analytical chemistry websites. In addition, several specific search types are in development to directly support the mass spectroscopy non-targeted screening community, who are generating important data for detecting and assessing environmental exposures to chemicals contained within DSSTox. The application provides access to segregated lists of chemicals that are of specific interests to relevant stakeholders including, for example, scientists interested in algal toxins and hydraulic fracturing chemicals. This presentation will provide an overview of the challenges associated with the curation of data from EPA’s December 2016 Hydraulic Fracturing Drinking Water Assessment Report that represented chemicals reported to be used in hydraulic fracturing fluids and those found in produced water. The data have been integrated into the dashboard with a number of resulting benefits: a searchable database of chemical properties, with hazard and exposure predictions, and open literature. The application of the dashboard to support mass spectrometry non-targeted analysis studies will also be reviewed. This abstract does not reflect U.S. EPA policy.Accessing information for chemicals in hydraulic fracturing fluids using the ...
Accessing information for chemicals in hydraulic fracturing fluids using the ...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
Multiple regulatory bodies (EPA, ECHA, Health Canada) are currently tasked with prioritizing chemicals for data collection and risk assessments. These prioritization efforts are in response to regulatory mandates to identify chemicals for further assessment. We have developed a web-based application that enables a rapid, flexible and transparent prioritization process. The tool includes multiple data streams related to human and ecological hazard, exposure, and physicochemical properties (persistence and bioaccumulation). For human hazard, the data streams include quantitative points of departure (PODs) that are compiled from multiple sources such as EPA ToxRefDB, ECHA, COSMOS; estimated PODs from high-throughput in vitro screening assays and computational models; and qualitative measurements and predictions of specific endpoints (e.g., genotoxicity, endocrine activity). For ecological hazard, quantitative PODs are taken from the EPA ECOTOX database. Exposure information includes production volume, quantitative predictions using the EPA ExpoCast and SHEDS models, biomonitoring data, and qualitative information such as media occurrence, use profiles and likelihood of consumer and childhood exposures. The use of the tool is illustrated by prioritizing chemicals related to TSCA and the Safer Choice Ingredient List. The underpinning data streams for this application are already available in the EPA CompTox Chemistry Dashboard and have been repurposed to deliver this application. This is in keeping with our overarching software development methodology of providing multiple “building blocks” in the form of databases, web services and visualization components to deliver fit-for purpose applications to the relevant audiences. This abstract does not necessarily represent U.S. EPA policy.Development of a Tool for Systematic Integration of Traditional and New Appro...
Development of a Tool for Systematic Integration of Traditional and New Appro...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
Researchers at EPA’s National Center for Computational Toxicology integrate advances in biology, chemistry, and computer science to examine the toxicity of chemicals and help prioritize chemicals for further research based on potential human health risks. The goal of this research program is to quickly evaluate thousands of chemicals, but at a much reduced cost and shorter time frame relative to traditional approaches. The data generated by the Center includes characterization of thousands of chemicals across hundreds of high-throughput screening assays, consumer use and production information, pharmacokinetic properties, literature data, physical-chemical properties as well as the predictive computational modeling of toxicity and exposure. We have developed a number of databases and applications to deliver the data to the public, academic community, industry stakeholders, and regulators. This presentation will provide an overview of our work to develop an architecture that integrates diverse large-scale data from the chemical and biological domains, our approaches to disseminate these data, and the delivery of models supporting predictive computational toxicology. In particular, this presentation will review our new CompTox Chemistry Dashboard and the developing architecture to support real-time property and toxicity endpoint prediction. This abstract does not reflect U.S. EPA policy.New developments in delivering public access to data from the National Center...
New developments in delivering public access to data from the National Center...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
Non-targeted and suspect screening studies using high resolution mass spectrometry (HRMS) have revolutionized the detection of chemicals in complex matrices. However, data processing remains challenging due to the vast number of chemicals detected in samples, software and computational requirements of data processing, and inherent uncertainty in confidently identifying chemicals from candidate lists. The US EPA has developed functionality within the CompTox Chemicals Dashboard (https://comptox.epa.gov) to address challenges related to data processing and analysis in HRMS. These tools include the generation of “MS-Ready” structures to optimize database searching, retention time prediction for candidate reduction, consensus ranking using chemical metadata, and in silico MS/MS fragmentation prediction for spectral matching. Combining these tools into a comprehensive workflow improves certainty in candidate identification. This presentation will introduce the tools and combined workflow, including visualization and access via the CompTox Chemicals Dashboard. These tools, data, and visualization approaches within an open chemistry resource provides a publicly available software tool to support structure identification and non-targeted analyses. This abstract does not necessarily represent the views or policies of the U.S. Environmental Protection Agency.Chemical identification of unknowns in high resolution mass spectrometry usin...
Chemical identification of unknowns in high resolution mass spectrometry usin...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
Researchers at the EPA’s National Center for Computational Toxicology integrate advances in biology, chemistry, and computer science to examine the toxicity of chemicals and help prioritize chemicals for further research based on potential human health risks. The intention of this research program is to quickly evaluate thousands of chemicals for potential risk but with much reduced cost relative to historical approaches. This work involves computational and data driven approaches including high-throughput screening, modeling, text-mining and the integration of chemistry, exposure and biological data. We have developed a number of databases and applications that are delivering on the vision of developing a deeper understanding of chemicals and their effects on exposure and biological processes that are supporting a large community of scientists in their research efforts. This presentation will provide an overview of our work to bring together diverse large scale data from the chemical and biological domains, our approaches to integrate and disseminate these data, and the delivery of models supporting computational toxicology. This abstract does not reflect U.S. EPA policy.Delivering The Benefits of Chemical-Biological Integration in Computational T...
Delivering The Benefits of Chemical-Biological Integration in Computational T...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
The development of QSAR models is critically dependent on the quality of available data. As part of our efforts to develop public platforms to provide access to predictive models, we have attempted to discriminate the influence of the quality versus quantity of data available to develop and validate QSAR models. We have focused our efforts on the widely used EPISuite software that was initially developed over two decades ago and, specifically, on the PHYSPROP dataset used to train the EPISuite prediction models. This presentation will review our approaches to examining key datasets, the delivery of curated data and the development of machine-learning models for thirteen separate property endpoints of interest to environmental science. We will also review how these data will be made freely accessible to the community via a new “chemistry dashboard”. This abstract does not reflect U.S. EPA policyAn examination of data quality on QSAR Modeling in regards to the environment...
An examination of data quality on QSAR Modeling in regards to the environment...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
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.The EPA iCSS Chemistry Dashboard to Support Compound Identification Using Hig...
The EPA iCSS Chemistry Dashboard to Support Compound Identification Using Hig...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
Researchers at EPA’s National Center for Computational Toxicology integrate advances in biology, chemistry, and computer science to examine the toxicity of chemicals and help prioritize chemicals for further research based on potential human health risks. The goal of this research program is to quickly evaluate thousands of chemicals, but at a much reduced cost and shorter time frame relative to traditional approaches. The data generated by the Center includes characterization of thousands of chemicals across hundreds of high-throughput screening assays, consumer use and production information, pharmacokinetic properties, literature data, physical-chemical properties as well as the predictive computational modeling of toxicity and exposure. We have developed a number of databases and applications to deliver the data to the public, academic community, industry stakeholders, and regulators. This presentation will provide an overview of our work to develop an architecture that integrates diverse large-scale data from the chemical and biological domains, our approaches to disseminate these data, and the delivery of models supporting predictive computational toxicology. In particular, this presentation will review our new publicly-accessible CompTox Dashboard as the first application built on our newly developed architecture. This abstract does not reflect U.S. EPA policy. Delivering The Benefits of Chemical-Biological Integration in Computational T...
Delivering The Benefits of Chemical-Biological Integration in Computational T...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
In the domain of chemistry one of the greatest benefits to publishing research is that data can be shared. Unfortunately, the vast majority of chemical structure data associated with scientific publications remain locked up in document form, primarily in PDF files or trapped on webpages. Despite the explosive growth of online chemical databases and the overall maturity of cheminformatics platforms, many barriers stifle the exchange of chemical structures via publications. These challenges include incomplete support by accepted standards (especially InChI) for advanced stereochemistry, organometallic compounds and generic “Markush” representations, the difference between human-readable and computer-readable forms of data, and challenges with the computer representation of chemical structures. To address these obstacles to chemical structure sharing, US EPA National Center for Computational Toxicology scientists are using a combination of cheminformatics applications and online repositories to distribute chemical structure data associated with their publications. This presentation will describe how EPA-NCCT chemical structure data that is amenable to indexing and distribution are shared and highlight the benefit of open data sharing for modeling, data integration, and increasing research impact. This abstract does not reflect U.S. EPA policy.Sharing chemical structures with peer reviewed publications
Sharing chemical structures with peer reviewed publications US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
High resolution mass spectrometry (HRMS) and non-targeted analysis (NTA) are utilized to identify emerging contaminants and chemical signatures of interest detected in various media. At the US Environmental Protection Agency the CompTox Chemicals Dashboard (https://comptox.epa.gov/dashboard) is an open chemistry resource and web-based application containing data for ~900,000 substances and supports non-targeted and suspect screening analyses. Searching functionality includes identifier searches (e.g. systematic names, trade names and CAS Registry Numbers), mass and formula-based searches and prototype developments include combined substructure-mass/formula searches and searching experimental mass spectral data against predicted fragmentation spectra. A specific type of data mapping in the database uses “MS-Ready” structures, a way to process all registered substances to separate multi-component chemicals into their individual components, removal of stereochemical bonds and desalting and neutralization. This MS-Ready processing supports batch-searching using either mass or formulae to identify candidate chemicals and their mapped substances. A number of chemical lists (https://comptox.epa.gov/dashboard/chemical_lists) have also been developed to support the identification of chemicals related to agrochemistry, specifically pesticides (both active and inert constituents), insecticides and their metabolites and environmental breakdown products). This presentation will provide an overview of how the CompTox Chemicals Dashboard supports mass spectrometry based structure identification and non-targeted analysis of chemicals in agrochemistry. This abstract does not necessarily represent the views or policies of the U.S. Environmental Protection Agency.Structure identification approaches using the EPA CompTox Chemicals Dashboard...
Structure identification approaches using the EPA CompTox Chemicals Dashboard...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
The iCSS CompTox Chemistry Dashboard is a publicly accessible dashboard provided by the National Center for Computation Toxicology at the US-EPA. It serves a number of purposes, including providing a chemistry database underpinning many of our public-facing projects (e.g. ToxCast and ExpoCast). The available data and searches provide a valuable path to structure identification using mass spectrometry as the source data. With an underlying database of over 720,000 chemicals, the dashboard has already been used to assist in identifying chemicals present in house dust. This poster reviews the benefits of the EPA’s platform and underlying algorithms used for the purpose of compound identification using high-resolution mass spectrometry data. Standard approaches for both mass and formula lookup are available but the dashboard delivers a novel approach for hit ranking based on functional use of the chemicals. The focus on high-quality data, novel ranking approaches and integration to other resources of value to mass spectrometrists makes the CompTox Dashboard a valuable resource for the identification of environmental chemicals. This abstract does not reflect U.S. EPA policy.Structure Identification Using High Resolution Mass Spectrometry Data and the...
Structure Identification Using High Resolution Mass Spectrometry Data and the...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
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.Environmental Chemistry Compound Identification Using High Resolution Mass Sp...
Environmental Chemistry Compound Identification Using High Resolution Mass Sp...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
Presentation for Texas A&M Superfund Research Center virtual learning series, Big Data in Environmental Science and Toxicology. More details at https://superfund.tamu.edu/big-data-session-2-aug-18-2021/New Approach Methods - What is That?
New Approach Methods - What is That?US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
The CompTox Chemicals Dashboard is an open chemistry resource and web-based application containing data for ~900,000 substances. While it pales in comparison to other online resources containing many tens of millions of chemical substances it represents two decades of effort to aggregate and curate chemical data to deliver access to physicochemical properties and environmental fate and transport data, in vitro and in vivo toxicity data and consumer product data for over 500,000 products. Associated with the chemical substance collections are specific lists based on chemical classes (e.g. polychlorinated biphenyls (PCBs)), usage categories (e.g. flame retardants, pesticides), specific environmental classes of interest (e.g. disinfectant by-products) and regulatory lists (e.g. TSCA, Toxics release inventory data). The underlying database expands daily as a result of the efforts of curators who continue to harvest data from peer-reviewed publications, regulatory documents and relevant online databases. The cheminformatics architecture allows for mapping between parent chemicals and related substances including metabolites and environmental degradants. The dashboard has become a valuable resource in the identification of chemical substances in the environment.
High resolution mass spectrometry (HRMS) and non-targeted analysis (NTA) are of increasing interest in chemical forensics for the identification of emerging contaminants and chemical signatures of interest. Our research using HRMS for non-targeted and suspect screening analyses utilizes Advanced Search capabilities including mass and formula-based searches. A specific type of data mapping in the underpinning database, using “MS-Ready” structures, has proven to be a valuable approach for structure identification that links structures that can be identified via HRMS with related substances in the form of salts, and other multi-component mixtures that are available in commerce. These MS-Ready structures have been used as an input set for computational MS-fragmentation to provide a database against which to search experimental data for spectral matching. This presentation will provide an overview of how CompTox Chemicals Dashboard, the underlying data, and how it supports structure identification and non-targeted analysis in chemical forensics. This abstract does not necessarily represent the views or policies of the U.S. Environmental Protection Agency.
What chemicals constitute the Exposome? Accessing data via the US EPA’s Comp...
What chemicals constitute the Exposome? Accessing data via the US EPA’s Comp...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
The iCSS Chemistry Dashboard is a publicly accessible dashboard provided by the National Center for Computation Toxicology at the US-EPA. It serves a number of purposes, including providing a chemistry database underpinning many of our public-facing projects (e.g. ToxCast and ExpoCast). The available data and searches provide a valuable path to structure identification using mass spectrometry as the source data. With an underlying database of over 720,000 chemicals, the dashboard has already been used to assist in identifying chemicals present in house dust. However, it can also be applied to many other purposes, e.g., the identification of agrochemicals in waste streams. This presentation will provide a review of the EPA’s platform and underlying algorithms used for the purpose of compound identification using high-resolution mass spectrometry data. We will also discuss progress towards a high-throughput non-targeted analysis platform for use by the mass spectrometry community. This abstract does not reflect U.S. EPA policy.Structure Identification Using High Resolution Mass Spectrometry Data and the...
Structure Identification Using High Resolution Mass Spectrometry Data and the...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
The construction of QSAR models is critically dependent on the quality of available data. As part of our efforts to develop public platforms to provide access to predictive models, we have attempted to discriminate the influence of the quality versus quantity of data available to develop and validate QSAR models. We have focused our efforts on the widely used EPISuite software that was initially developed over two decades ago. Specific examples of quality issues for the EPISuite data include multiple records for the same chemical structure with different measured property values, inconsistency between the structure, chemical name and CAS registry number for single records, the inability to convert the SMILES strings into chemical structures, hypervalency in the chemical structures and the absence of stereochemistry for thousands of data records. Relative to the era of EPISuite development, modern cheminformatics tools allow for more advanced capabilities in terms of chemical structure representation and storage, as well as enabling automated data validation and standardization approaches to examine data quality. This presentation will review both our manual and automated approaches to examining key datasets related to the EPISuite training and test data. This includes approaches to validate between chemical structure representations (e.g. molfile and SMILES) and identifiers (chemical names and registry numbers), as well as approaches to standardize the data into QSAR-consumable formats for modeling. We have quantified and segregated the data into various quality categories to allow us to thoroughly investigate the resulting models that can be developed from these data slices and to examine to what extent efforts into the development of large high-quality datasets have the expected pay-off in terms of prediction performance. This abstract does not reflect U.S. EPA policy. The influence of data curation on QSAR Modeling – examining issues of qualit...
The influence of data curation on QSAR Modeling – examining issues of qualit...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
The US EPA’s CompTox Chemicals Dashboard (https://comptox.epa.gov/dashboard) is a freely available web-based application providing access to data for ~900,000 chemical substances, the majority of these represented as chemical structures. The Dashboard also provides access to segregated lists of chemicals that are of specific interest to relevant stakeholders and, in particular, a list of hundreds of disinfection by-product (DBP) chemicals reported in the literature and detected in the laboratory using mass spectrometric techniques. Many of these chemicals are explicit chemical structures whose structures have been confirmed using purchased or synthesized reference standards. However, some of these chemicals may be ambiguous in nature with no explicit positional isomers being possible to define but the formula and mass spec fragmentation sufficient to define a class of chemicals (e.g. dichlorophenol). Such chemicals may be represented with ambiguous chemical structure forms, so-called Markush structures, and mapped to the individual class members. Chemicals accessible via the Dashboard can include access to a wide array of computed and measured physicochemical properties, in vitro high-throughput screening data and in vivo toxicity data, product use information extracted from safety data sheets, and integrated chemical linkages to a growing list of literature, toxicology, and analytical chemistry websites. Since DBP chemicals are primarily identified using mass spectrometric techniques specific search types have been developed to directly support the non-targeted screening community, enabling cohesive workflows to support data generation for the detection and assessment of environmental exposures to chemicals contained within the database. This presentation will provide an overview of the Dashboard, the ongoing expansion of the DBP chemical list and specific functionality supporting identification of DBPs by mass spectrometry. This abstract does not necessarily represent the views or policies of the U.S. Environmental Protection Agency.Web-based access to data for >600 disinfection by-products via the EPA CompTo...
Web-based access to data for >600 disinfection by-products via the EPA CompTo...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
As part of our efforts to develop a public platform to provide access to predictive models we have attempted to disentangle the influence of the quality versus quantity of data available to develop and validate QSAR models. Using a thorough manual review of the data underlying the well-known EPI Suite software, we developed automated processes for the validation of the data using a KNIME workflow. This includes: approaches to validate different chemical structure representations (e.g. molfile and SMILES), identifiers (chemical names and registry numbers), and methods to standardize the data into QSAR-consumable formats for modeling. Our efforts to quantify and segregate data into various quality categories has allowed us to thoroughly investigate the resulting models developed from these data slices, as well as allowing us to examine whether or not efforts into the development of large high-quality datasets has the expected pay-off in terms of prediction performance. Machine-learning approaches have been applied to create a series of models that have been used to generate predicted physicochemical and environmental parameters for over 700,000 chemicals. These data are available online via the EPA’s iCSS Chemistry Dashboard. This abstract does not reflect U.S. EPA policy.The EPA Online Prediction Physicochemical Prediction Platform to Support Envi...
The EPA Online Prediction Physicochemical Prediction Platform to Support Envi...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
Presentation for Texas A&M Superfund Research Center virtual learning series, Big Data in Environmental Science and Toxicology. More details at https://superfund.tamu.edu/big-data-session-1-july-14-2021/How to place your research questions or results into the context of the "Lega...
How to place your research questions or results into the context of the "Lega...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
Non-targeted analysis (NTA) uses high-resolution mass spectrometry to better understand the identity of a wide variety of chemicals present in environmental samples (and other matrices). However, data processing remains challenging due to the vast number of chemicals detected in samples, software and computational requirements of data processing, and inherent uncertainty in confidently identifying chemicals from candidate lists. Analysis of the resultant mass spectrometry information relies on cheminformatics to identify and rank chemicals and the US EPA has developed functionality within the CompTox Chemicals Dashboard (https://comptox.epa.gov/dashboard) to address challenges related to this analysis. These tools include the generation of “MS-Ready” structures to optimize database searching, retention time prediction for candidate reduction, consensus ranking using chemical metadata, and in silico MS/MS fragmentation prediction for spectral matching. Combining these tools into a comprehensive workflow improves certainty in candidate identification. This presentation will review how the CompTox Chemicals Dashboard via its flexible search capabilities, rich data for ~900,000 chemical substances, and visualization approaches within this open chemistry resource provides a freely available software tool to support structure identification and NTA. This abstract does not necessarily represent the views or policies of the U.S. Environmental Protection Agency.Non-targeted analysis supported by data and cheminformatics delivered via the...
Non-targeted analysis supported by data and cheminformatics delivered via the...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
The iCSS CompTox Dashboard is a publicly accessible dashboard provided by the National Center for Computation Toxicology at the US-EPA. It serves a number of purposes, including providing a chemistry database underpinning many of our public-facing projects (e.g. ToxCast and ExpoCast). The available data and searches provide a valuable path to structure identification using mass spectrometry as the source data. With an underlying database of over 720,000 chemicals, the dashboard has already been used to assist in identifying chemicals present in house dust. However, it can also be applied to many other purposes, e.g., the identification of agrochemicals in waste streams. This presentation will provide a review of the EPA’s platform and underlying algorithms used for the purpose of compound identification using high-resolution mass spectrometry data. In order to examine its performance for structure identification, especially in terms of rank-ordering database hits, we have compared it with the ChemSpider database, a well-regarded public database that has become one of the community standards for structure identification. The study has shown that the CompTox Dashboard outperforms ChemSpider in terms of structure identification and ranking providing improved outcomes for mass spectrometry analysis of “known unknowns”. Structure Identification Using High Resolution Mass Spectrometry Data and the...
Structure Identification Using High Resolution Mass Spectrometry Data and the...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
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Researchers at EPA’s National Center for Computational Toxicology integrate advances in biology, chemistry, and computer science to examine the toxicity of chemicals and help prioritize chemicals for further research based on potential human health risks. The goal of this research program is to quickly evaluate thousands of chemicals, but at a much reduced cost and shorter time frame relative to traditional approaches. The data generated by the Center includes characterization of thousands of chemicals across hundreds of high-throughput screening assays, consumer use and production information, pharmacokinetic properties, literature data, physical-chemical properties as well as the predictive computational modeling of toxicity and exposure. We have developed a number of databases and applications to deliver the data to the public, academic community, industry stakeholders, and regulators. This presentation will provide an overview of our work to develop an architecture that integrates diverse large-scale data from the chemical and biological domains, our approaches to disseminate these data, and the delivery of models supporting predictive computational toxicology. In particular, this presentation will review our new CompTox Chemistry Dashboard and the developing architecture to support real-time property and toxicity endpoint prediction. This abstract does not reflect U.S. EPA policy.New developments in delivering public access to data from the National Center...
New developments in delivering public access to data from the National Center...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
Non-targeted and suspect screening studies using high resolution mass spectrometry (HRMS) have revolutionized the detection of chemicals in complex matrices. However, data processing remains challenging due to the vast number of chemicals detected in samples, software and computational requirements of data processing, and inherent uncertainty in confidently identifying chemicals from candidate lists. The US EPA has developed functionality within the CompTox Chemicals Dashboard (https://comptox.epa.gov) to address challenges related to data processing and analysis in HRMS. These tools include the generation of “MS-Ready” structures to optimize database searching, retention time prediction for candidate reduction, consensus ranking using chemical metadata, and in silico MS/MS fragmentation prediction for spectral matching. Combining these tools into a comprehensive workflow improves certainty in candidate identification. This presentation will introduce the tools and combined workflow, including visualization and access via the CompTox Chemicals Dashboard. These tools, data, and visualization approaches within an open chemistry resource provides a publicly available software tool to support structure identification and non-targeted analyses. This abstract does not necessarily represent the views or policies of the U.S. Environmental Protection Agency.Chemical identification of unknowns in high resolution mass spectrometry usin...
Chemical identification of unknowns in high resolution mass spectrometry usin...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
Researchers at the EPA’s National Center for Computational Toxicology integrate advances in biology, chemistry, and computer science to examine the toxicity of chemicals and help prioritize chemicals for further research based on potential human health risks. The intention of this research program is to quickly evaluate thousands of chemicals for potential risk but with much reduced cost relative to historical approaches. This work involves computational and data driven approaches including high-throughput screening, modeling, text-mining and the integration of chemistry, exposure and biological data. We have developed a number of databases and applications that are delivering on the vision of developing a deeper understanding of chemicals and their effects on exposure and biological processes that are supporting a large community of scientists in their research efforts. This presentation will provide an overview of our work to bring together diverse large scale data from the chemical and biological domains, our approaches to integrate and disseminate these data, and the delivery of models supporting computational toxicology. This abstract does not reflect U.S. EPA policy.Delivering The Benefits of Chemical-Biological Integration in Computational T...
Delivering The Benefits of Chemical-Biological Integration in Computational T...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
The development of QSAR models is critically dependent on the quality of available data. As part of our efforts to develop public platforms to provide access to predictive models, we have attempted to discriminate the influence of the quality versus quantity of data available to develop and validate QSAR models. We have focused our efforts on the widely used EPISuite software that was initially developed over two decades ago and, specifically, on the PHYSPROP dataset used to train the EPISuite prediction models. This presentation will review our approaches to examining key datasets, the delivery of curated data and the development of machine-learning models for thirteen separate property endpoints of interest to environmental science. We will also review how these data will be made freely accessible to the community via a new “chemistry dashboard”. This abstract does not reflect U.S. EPA policyAn examination of data quality on QSAR Modeling in regards to the environment...
An examination of data quality on QSAR Modeling in regards to the environment...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
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.The EPA iCSS Chemistry Dashboard to Support Compound Identification Using Hig...
The EPA iCSS Chemistry Dashboard to Support Compound Identification Using Hig...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
Researchers at EPA’s National Center for Computational Toxicology integrate advances in biology, chemistry, and computer science to examine the toxicity of chemicals and help prioritize chemicals for further research based on potential human health risks. The goal of this research program is to quickly evaluate thousands of chemicals, but at a much reduced cost and shorter time frame relative to traditional approaches. The data generated by the Center includes characterization of thousands of chemicals across hundreds of high-throughput screening assays, consumer use and production information, pharmacokinetic properties, literature data, physical-chemical properties as well as the predictive computational modeling of toxicity and exposure. We have developed a number of databases and applications to deliver the data to the public, academic community, industry stakeholders, and regulators. This presentation will provide an overview of our work to develop an architecture that integrates diverse large-scale data from the chemical and biological domains, our approaches to disseminate these data, and the delivery of models supporting predictive computational toxicology. In particular, this presentation will review our new publicly-accessible CompTox Dashboard as the first application built on our newly developed architecture. This abstract does not reflect U.S. EPA policy. Delivering The Benefits of Chemical-Biological Integration in Computational T...
Delivering The Benefits of Chemical-Biological Integration in Computational T...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
In the domain of chemistry one of the greatest benefits to publishing research is that data can be shared. Unfortunately, the vast majority of chemical structure data associated with scientific publications remain locked up in document form, primarily in PDF files or trapped on webpages. Despite the explosive growth of online chemical databases and the overall maturity of cheminformatics platforms, many barriers stifle the exchange of chemical structures via publications. These challenges include incomplete support by accepted standards (especially InChI) for advanced stereochemistry, organometallic compounds and generic “Markush” representations, the difference between human-readable and computer-readable forms of data, and challenges with the computer representation of chemical structures. To address these obstacles to chemical structure sharing, US EPA National Center for Computational Toxicology scientists are using a combination of cheminformatics applications and online repositories to distribute chemical structure data associated with their publications. This presentation will describe how EPA-NCCT chemical structure data that is amenable to indexing and distribution are shared and highlight the benefit of open data sharing for modeling, data integration, and increasing research impact. This abstract does not reflect U.S. EPA policy.Sharing chemical structures with peer reviewed publications
Sharing chemical structures with peer reviewed publications US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
High resolution mass spectrometry (HRMS) and non-targeted analysis (NTA) are utilized to identify emerging contaminants and chemical signatures of interest detected in various media. At the US Environmental Protection Agency the CompTox Chemicals Dashboard (https://comptox.epa.gov/dashboard) is an open chemistry resource and web-based application containing data for ~900,000 substances and supports non-targeted and suspect screening analyses. Searching functionality includes identifier searches (e.g. systematic names, trade names and CAS Registry Numbers), mass and formula-based searches and prototype developments include combined substructure-mass/formula searches and searching experimental mass spectral data against predicted fragmentation spectra. A specific type of data mapping in the database uses “MS-Ready” structures, a way to process all registered substances to separate multi-component chemicals into their individual components, removal of stereochemical bonds and desalting and neutralization. This MS-Ready processing supports batch-searching using either mass or formulae to identify candidate chemicals and their mapped substances. A number of chemical lists (https://comptox.epa.gov/dashboard/chemical_lists) have also been developed to support the identification of chemicals related to agrochemistry, specifically pesticides (both active and inert constituents), insecticides and their metabolites and environmental breakdown products). This presentation will provide an overview of how the CompTox Chemicals Dashboard supports mass spectrometry based structure identification and non-targeted analysis of chemicals in agrochemistry. This abstract does not necessarily represent the views or policies of the U.S. Environmental Protection Agency.Structure identification approaches using the EPA CompTox Chemicals Dashboard...
Structure identification approaches using the EPA CompTox Chemicals Dashboard...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
The iCSS CompTox Chemistry Dashboard is a publicly accessible dashboard provided by the National Center for Computation Toxicology at the US-EPA. It serves a number of purposes, including providing a chemistry database underpinning many of our public-facing projects (e.g. ToxCast and ExpoCast). The available data and searches provide a valuable path to structure identification using mass spectrometry as the source data. With an underlying database of over 720,000 chemicals, the dashboard has already been used to assist in identifying chemicals present in house dust. This poster reviews the benefits of the EPA’s platform and underlying algorithms used for the purpose of compound identification using high-resolution mass spectrometry data. Standard approaches for both mass and formula lookup are available but the dashboard delivers a novel approach for hit ranking based on functional use of the chemicals. The focus on high-quality data, novel ranking approaches and integration to other resources of value to mass spectrometrists makes the CompTox Dashboard a valuable resource for the identification of environmental chemicals. This abstract does not reflect U.S. EPA policy.Structure Identification Using High Resolution Mass Spectrometry Data and the...
Structure Identification Using High Resolution Mass Spectrometry Data and the...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
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.Environmental Chemistry Compound Identification Using High Resolution Mass Sp...
Environmental Chemistry Compound Identification Using High Resolution Mass Sp...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
Presentation for Texas A&M Superfund Research Center virtual learning series, Big Data in Environmental Science and Toxicology. More details at https://superfund.tamu.edu/big-data-session-2-aug-18-2021/New Approach Methods - What is That?
New Approach Methods - What is That?US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
The CompTox Chemicals Dashboard is an open chemistry resource and web-based application containing data for ~900,000 substances. While it pales in comparison to other online resources containing many tens of millions of chemical substances it represents two decades of effort to aggregate and curate chemical data to deliver access to physicochemical properties and environmental fate and transport data, in vitro and in vivo toxicity data and consumer product data for over 500,000 products. Associated with the chemical substance collections are specific lists based on chemical classes (e.g. polychlorinated biphenyls (PCBs)), usage categories (e.g. flame retardants, pesticides), specific environmental classes of interest (e.g. disinfectant by-products) and regulatory lists (e.g. TSCA, Toxics release inventory data). The underlying database expands daily as a result of the efforts of curators who continue to harvest data from peer-reviewed publications, regulatory documents and relevant online databases. The cheminformatics architecture allows for mapping between parent chemicals and related substances including metabolites and environmental degradants. The dashboard has become a valuable resource in the identification of chemical substances in the environment.
High resolution mass spectrometry (HRMS) and non-targeted analysis (NTA) are of increasing interest in chemical forensics for the identification of emerging contaminants and chemical signatures of interest. Our research using HRMS for non-targeted and suspect screening analyses utilizes Advanced Search capabilities including mass and formula-based searches. A specific type of data mapping in the underpinning database, using “MS-Ready” structures, has proven to be a valuable approach for structure identification that links structures that can be identified via HRMS with related substances in the form of salts, and other multi-component mixtures that are available in commerce. These MS-Ready structures have been used as an input set for computational MS-fragmentation to provide a database against which to search experimental data for spectral matching. This presentation will provide an overview of how CompTox Chemicals Dashboard, the underlying data, and how it supports structure identification and non-targeted analysis in chemical forensics. This abstract does not necessarily represent the views or policies of the U.S. Environmental Protection Agency.
What chemicals constitute the Exposome? Accessing data via the US EPA’s Comp...
What chemicals constitute the Exposome? Accessing data via the US EPA’s Comp...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
The iCSS Chemistry Dashboard is a publicly accessible dashboard provided by the National Center for Computation Toxicology at the US-EPA. It serves a number of purposes, including providing a chemistry database underpinning many of our public-facing projects (e.g. ToxCast and ExpoCast). The available data and searches provide a valuable path to structure identification using mass spectrometry as the source data. With an underlying database of over 720,000 chemicals, the dashboard has already been used to assist in identifying chemicals present in house dust. However, it can also be applied to many other purposes, e.g., the identification of agrochemicals in waste streams. This presentation will provide a review of the EPA’s platform and underlying algorithms used for the purpose of compound identification using high-resolution mass spectrometry data. We will also discuss progress towards a high-throughput non-targeted analysis platform for use by the mass spectrometry community. This abstract does not reflect U.S. EPA policy.Structure Identification Using High Resolution Mass Spectrometry Data and the...
Structure Identification Using High Resolution Mass Spectrometry Data and the...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
The construction of QSAR models is critically dependent on the quality of available data. As part of our efforts to develop public platforms to provide access to predictive models, we have attempted to discriminate the influence of the quality versus quantity of data available to develop and validate QSAR models. We have focused our efforts on the widely used EPISuite software that was initially developed over two decades ago. Specific examples of quality issues for the EPISuite data include multiple records for the same chemical structure with different measured property values, inconsistency between the structure, chemical name and CAS registry number for single records, the inability to convert the SMILES strings into chemical structures, hypervalency in the chemical structures and the absence of stereochemistry for thousands of data records. Relative to the era of EPISuite development, modern cheminformatics tools allow for more advanced capabilities in terms of chemical structure representation and storage, as well as enabling automated data validation and standardization approaches to examine data quality. This presentation will review both our manual and automated approaches to examining key datasets related to the EPISuite training and test data. This includes approaches to validate between chemical structure representations (e.g. molfile and SMILES) and identifiers (chemical names and registry numbers), as well as approaches to standardize the data into QSAR-consumable formats for modeling. We have quantified and segregated the data into various quality categories to allow us to thoroughly investigate the resulting models that can be developed from these data slices and to examine to what extent efforts into the development of large high-quality datasets have the expected pay-off in terms of prediction performance. This abstract does not reflect U.S. EPA policy. The influence of data curation on QSAR Modeling – examining issues of qualit...
The influence of data curation on QSAR Modeling – examining issues of qualit...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
The US EPA’s CompTox Chemicals Dashboard (https://comptox.epa.gov/dashboard) is a freely available web-based application providing access to data for ~900,000 chemical substances, the majority of these represented as chemical structures. The Dashboard also provides access to segregated lists of chemicals that are of specific interest to relevant stakeholders and, in particular, a list of hundreds of disinfection by-product (DBP) chemicals reported in the literature and detected in the laboratory using mass spectrometric techniques. Many of these chemicals are explicit chemical structures whose structures have been confirmed using purchased or synthesized reference standards. However, some of these chemicals may be ambiguous in nature with no explicit positional isomers being possible to define but the formula and mass spec fragmentation sufficient to define a class of chemicals (e.g. dichlorophenol). Such chemicals may be represented with ambiguous chemical structure forms, so-called Markush structures, and mapped to the individual class members. Chemicals accessible via the Dashboard can include access to a wide array of computed and measured physicochemical properties, in vitro high-throughput screening data and in vivo toxicity data, product use information extracted from safety data sheets, and integrated chemical linkages to a growing list of literature, toxicology, and analytical chemistry websites. Since DBP chemicals are primarily identified using mass spectrometric techniques specific search types have been developed to directly support the non-targeted screening community, enabling cohesive workflows to support data generation for the detection and assessment of environmental exposures to chemicals contained within the database. This presentation will provide an overview of the Dashboard, the ongoing expansion of the DBP chemical list and specific functionality supporting identification of DBPs by mass spectrometry. This abstract does not necessarily represent the views or policies of the U.S. Environmental Protection Agency.Web-based access to data for >600 disinfection by-products via the EPA CompTo...
Web-based access to data for >600 disinfection by-products via the EPA CompTo...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
As part of our efforts to develop a public platform to provide access to predictive models we have attempted to disentangle the influence of the quality versus quantity of data available to develop and validate QSAR models. Using a thorough manual review of the data underlying the well-known EPI Suite software, we developed automated processes for the validation of the data using a KNIME workflow. This includes: approaches to validate different chemical structure representations (e.g. molfile and SMILES), identifiers (chemical names and registry numbers), and methods to standardize the data into QSAR-consumable formats for modeling. Our efforts to quantify and segregate data into various quality categories has allowed us to thoroughly investigate the resulting models developed from these data slices, as well as allowing us to examine whether or not efforts into the development of large high-quality datasets has the expected pay-off in terms of prediction performance. Machine-learning approaches have been applied to create a series of models that have been used to generate predicted physicochemical and environmental parameters for over 700,000 chemicals. These data are available online via the EPA’s iCSS Chemistry Dashboard. This abstract does not reflect U.S. EPA policy.The EPA Online Prediction Physicochemical Prediction Platform to Support Envi...
The EPA Online Prediction Physicochemical Prediction Platform to Support Envi...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
Presentation for Texas A&M Superfund Research Center virtual learning series, Big Data in Environmental Science and Toxicology. More details at https://superfund.tamu.edu/big-data-session-1-july-14-2021/How to place your research questions or results into the context of the "Lega...
How to place your research questions or results into the context of the "Lega...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
Non-targeted analysis (NTA) uses high-resolution mass spectrometry to better understand the identity of a wide variety of chemicals present in environmental samples (and other matrices). However, data processing remains challenging due to the vast number of chemicals detected in samples, software and computational requirements of data processing, and inherent uncertainty in confidently identifying chemicals from candidate lists. Analysis of the resultant mass spectrometry information relies on cheminformatics to identify and rank chemicals and the US EPA has developed functionality within the CompTox Chemicals Dashboard (https://comptox.epa.gov/dashboard) to address challenges related to this analysis. These tools include the generation of “MS-Ready” structures to optimize database searching, retention time prediction for candidate reduction, consensus ranking using chemical metadata, and in silico MS/MS fragmentation prediction for spectral matching. Combining these tools into a comprehensive workflow improves certainty in candidate identification. This presentation will review how the CompTox Chemicals Dashboard via its flexible search capabilities, rich data for ~900,000 chemical substances, and visualization approaches within this open chemistry resource provides a freely available software tool to support structure identification and NTA. This abstract does not necessarily represent the views or policies of the U.S. Environmental Protection Agency.Non-targeted analysis supported by data and cheminformatics delivered via the...
Non-targeted analysis supported by data and cheminformatics delivered via the...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
The iCSS CompTox Dashboard is a publicly accessible dashboard provided by the National Center for Computation Toxicology at the US-EPA. It serves a number of purposes, including providing a chemistry database underpinning many of our public-facing projects (e.g. ToxCast and ExpoCast). The available data and searches provide a valuable path to structure identification using mass spectrometry as the source data. With an underlying database of over 720,000 chemicals, the dashboard has already been used to assist in identifying chemicals present in house dust. However, it can also be applied to many other purposes, e.g., the identification of agrochemicals in waste streams. This presentation will provide a review of the EPA’s platform and underlying algorithms used for the purpose of compound identification using high-resolution mass spectrometry data. In order to examine its performance for structure identification, especially in terms of rank-ordering database hits, we have compared it with the ChemSpider database, a well-regarded public database that has become one of the community standards for structure identification. The study has shown that the CompTox Dashboard outperforms ChemSpider in terms of structure identification and ranking providing improved outcomes for mass spectrometry analysis of “known unknowns”. Structure Identification Using High Resolution Mass Spectrometry Data and the...
Structure Identification Using High Resolution Mass Spectrometry Data and the...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
Mais procurados (20)
New developments in delivering public access to data from the National Center...
New developments in delivering public access to data from the National Center...
Chemical identification of unknowns in high resolution mass spectrometry usin...
Chemical identification of unknowns in high resolution mass spectrometry usin...
DMCM2018 Community Resources Connecting Chemistry and Toxicity Knowledge
DMCM2018 Community Resources Connecting Chemistry and Toxicity Knowledge
Delivering The Benefits of Chemical-Biological Integration in Computational T...
Delivering The Benefits of Chemical-Biological Integration in Computational T...
An examination of data quality on QSAR Modeling in regards to the environment...
An examination of data quality on QSAR Modeling in regards to the environment...
The EPA iCSS Chemistry Dashboard to Support Compound Identification Using Hig...
The EPA iCSS Chemistry Dashboard to Support Compound Identification Using Hig...
Delivering The Benefits of Chemical-Biological Integration in Computational T...
Delivering The Benefits of Chemical-Biological Integration in Computational T...
Sharing chemical structures with peer reviewed publications
Sharing chemical structures with peer reviewed publications
Structure identification approaches using the EPA CompTox Chemicals Dashboard...
Structure identification approaches using the EPA CompTox Chemicals Dashboard...
Structure Identification Using High Resolution Mass Spectrometry Data and the...
Structure Identification Using High Resolution Mass Spectrometry Data and the...
Environmental Chemistry Compound Identification Using High Resolution Mass Sp...
Environmental Chemistry Compound Identification Using High Resolution Mass Sp...
What chemicals constitute the Exposome? Accessing data via the US EPA’s Comp...
What chemicals constitute the Exposome? Accessing data via the US EPA’s Comp...
Structure Identification Using High Resolution Mass Spectrometry Data and the...
Structure Identification Using High Resolution Mass Spectrometry Data and the...
The influence of data curation on QSAR Modeling – examining issues of qualit...
The influence of data curation on QSAR Modeling – examining issues of qualit...
Web-based access to data for >600 disinfection by-products via the EPA CompTo...
Web-based access to data for >600 disinfection by-products via the EPA CompTo...
The EPA Online Prediction Physicochemical Prediction Platform to Support Envi...
The EPA Online Prediction Physicochemical Prediction Platform to Support Envi...
How to place your research questions or results into the context of the "Lega...
How to place your research questions or results into the context of the "Lega...
Non-targeted analysis supported by data and cheminformatics delivered via the...
Non-targeted analysis supported by data and cheminformatics delivered via the...
Structure Identification Using High Resolution Mass Spectrometry Data and the...
Structure Identification Using High Resolution Mass Spectrometry Data and the...
Semelhante a Adding complex expert knowledge into chemical database and transforming surfactants in wastewater
The increasing popularity of high mass accuracy non-target mass spectrometry methods has yielded extensive identification efforts based on spectral and chemical compound databases in the environmental community and beyond. Increasingly, new methods are relying on open data resources. Candidate structures are often retrieved with either exact mass or molecular formula from large resources such as PubChem, ChemSpider or the EPA CompTox Chemistry Dashboard. Smaller, selective lists of chemicals (also called “suspect lists”) can be used to perform more efficient annotation. Mass spectral libraries can then be used to increase the confidence in tentative identification. Additional metadata (e.g. exposure and hazard information, reference and data source information) can be extremely useful to prioritize substances of high environmental interest. Exchanging information and “sharing structural linkages” between these resources requires extensive curation to ensure that the correct information is shared correctly, yet many valuable datasets arise from scientists and regulators with little official cheminformatics training. This talk will cover curation efforts undertaken to map spectral libraries (e.g. MassBank.EU, mzCloud) and suspect lists from the NORMAN Suspect Exchange (http://www.norman-network.com/?q=node/236) to unique chemical identifiers associated with the US EPA CompTox Chemistry Dashboard. The curation workflow takes advantage of years of experience, as well as contact with the original data providers, to enable open access to valuable, curated datasets to support environmental scientists and the broader research community (e.g. https://comptox.epa.gov/dashboard/chemical_lists). Note: This abstract does not reflect US EPA policy.Curating and Sharing Structures and Spectra for the Environmental Community
Curating and Sharing Structures and Spectra for the Environmental CommunityUS Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
The European MassBank server (www.massbank.eu) was founded in 2012 by the NORMAN Network (www.norman-network.net) to provide open access to mass spectra of substances of environmental interest contributed by NORMAN members. The automated workflow RMassBank was developed as a part of this effort (Stravs et al 2013, DOI: 10.1002/jms.3131; https://github.com/MassBank/RMassBank/). This workflow included automated processing of the mass spectral data, as well as automated annotation using the SMILES, Names and CAS numbers provided by the user. Cheminformatics toolkits (e.g. Open Babel, rcdk) and web services (e.g. the CACTUS Chemical Identifier Resolver, Chemical Translation Services (CTS), ChemSpider, PubChem) were then used to convert and/or retrieve the remaining information for completion of the MassBank records (additional names, InChIs, InChIKeys, several database identifiers, mol files), to avoid excessive burden on the users and reduce the chance of errors. To date, approximately 16,000 MS/MS spectra (61 %*) corresponding with 1,269 (18 %*) unique chemicals (*of all open data as of Nov. 2016) have been uploaded to MassBank.EU via RMassBank. Curating the MassBank.EU records, as part of efforts to provide EPA CompTox Dashboard identifiers (DTXSIDs) for each record, revealed several issues in data quality. In addition, the representation of “ambiguous substances”, for example complex surfactant mixtures of various chain lengths and branching or incompletely-defined structures of transformaton products, is an ongoing challenge. While “ambiguous structures” cannot be represented in the majority of cheminformatics tools, we report on proof-of-concept solutions in this work. This presentation reflects on the effectiveness of the original RMassBank concept but also identifies pitfalls that automated structure annotation with open resources offers to streamline spectra contributions from external laboratories and users with widely ranging cheminformatics experience. Note: this work does not necessarily reflect U.S. EPA policy.Automated Structure Annotation and Curation for MassBank: Potential and Pitfalls
Automated Structure Annotation and Curation for MassBank: Potential and PitfallsUS Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
EPA’s National Center for Computational Toxicology is developing automated workflows for curating large databases within the DSSTox project and for providing accurate linkages of data to chemical structures, exposure, and hazard data. The data are made available via the EPA’s CompTox Chemicals Dashboard1 (https://comptox.epa.gov/dashboard), a publicly accessible website providing access to data for ~875,000 chemical substances, the majority of these represented with chemical structures. The web application delivers a wide array of computed and measured physicochemical properties, in vitro high-throughput screening data and in vivo toxicity data, and linkages to a growing list of literature, toxicology, and analytical chemistry websites. The dashboard version 3:March 2019 release includes support for the invitroDBv3.1 data release2 and includes new functionality to interact with all ToxCast and Tox21 data with the intention of replacing the previously available EDSP21 and ToxCast dashboards. The previous dashboards will be retired in summer 2019.
US-EPA CompTox Chemicals Dashboard: Bioactivity Data for Endocrine Assays
US-EPA CompTox Chemicals Dashboard: Bioactivity Data for Endocrine AssaysUS Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
After one year of intense working group activity, some of our research highlights will be presented.QMC: Transition Workshop - Selected Highlights from the Probabilistic Numeric...
QMC: Transition Workshop - Selected Highlights from the Probabilistic Numeric...The Statistical and Applied Mathematical Sciences Institute
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 (e.g., to support breath research (the volatilome) 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.The US-EPA CompTox Chemicals Dashboard – an online data integration hub suppo...
The US-EPA CompTox Chemicals Dashboard – an online data integration hub suppo...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
The EPA Comptox Chemistry Dashboard is a web-based application providing access to a set of data resources provided by the National Center of Computational Toxicology. Sitting on a foundation of chemistry data for ~750,000 chemical substances the application integrates bioassay screening results, physicochemical and toxicological endpoints (both experimental and predicted) and consumer product and functional use data. By integrating a series of other EPA and public databases (e.g. ECOTOX, the EPA Substance Registry Service, EPA’s ChemView and PubChem), the dashboard provides a hub for connecting to other releases of value to environmental scientists and toxicologists. The underpinning architecture has been developed in a manner allowing for the release of the dashboard as a public resource, as well as for delivering applications used inside confidential business information environments. These applications are being assessed for potential applications to support risk decisions. This presentation will provide an overview of the dashboard focusing specifically on the most recent functionality supporting deeper integration to the ToxCast bioassay data and exposure data and predictions available via the dashboard. This abstract does not reflect U.S. EPA policy.Bringing it all together: A Web-based Database for Chemical and Biological Da...
Bringing it all together: A Web-based Database for Chemical and Biological Da...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
This workshop, organized by HESI’s Technical Committee on Multicomponent Substances (MCS) and Chemical Substances of Unknown or Variable Composition, Complex Reaction Products and Biological Materials (UVCB), was held on December 10-11, 2018 at the HESI Office in Washington, DC. The primary objective of this workshop was to explore approaches to characterize and group UVCB substances considering both established traditional chemical characterization approaches along with lesser utilized “outside the box” approaches. This information was to inform the design of a roadmap to guide future work towards substance prioritization, and hazard and risk assessment frameworks. This work focused on ecological assessment, but human health risk assessment was not excluded from the discussion.
This talk provided an overview of non-targeted screening approaches for structure identification, especially in regards to UVCB chemicals with homologous series. It also provided an overview of the CompTox Chemicals Dashboard and cheminformatics approaches related to UVCB chemicals.Non-targeted screening to improve substance identity for Chemical Substances ...
Non-targeted screening to improve substance identity for Chemical Substances ...US Environmental Protection Agency (EPA), Center for Computational Toxicology and Exposure
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Adding complex expert knowledge into chemical database and transforming surfactants in wastewater
- 1. 1 Adding Complex Expert KnowledgeAdding Complex Expert Knowledge into Chemical Databases:into Chemical Databases: Transforming Surfactants in WastewaterTransforming Surfactants in Wastewater Emma Schymanski Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg. Email: emma.schymanski@uni.lu Juliane Hollender (Eawag, Dübendorf, Switzerland) Chris Grulke (NCCT, US EPA, Research Triangle Park, NC, USA) Antony J. Williams (NCCT, US EPA, Research Triangle Park, NC, USA) The views expressed in this presentation are those of the authors and do not necessarily reflect the views or policies of the U.S. Environmental Protection Agency.
- 2. 2 Why Add Complex Expert Knowledge to Databases? (l) Schymanski et al. 2014, ES&T, 48: 1811-1818. DOI: 10.1021/es4044374. (r) Source: N. Zamboni Unknowns and High Resolution Mass Spectrometry o Over 60 % of HR-MS peaks are potentially relevant but unknown
- 3. 3 Why Add Complex Expert Knowledge to Databases? Schymanski et al. 2014, ES&T, DOI: 10.1021/es4044374; M. Loos & H Singer, 2017. J. Cheminf. DOI: 10.1186/s13321-017-0197-z Homologous Series and UVCBs in our samples …. S OO OH CH3 CH3 m n C9H19 O O S O O OHm
- 4. 4 Why Add Complex Expert Knowledge to Databases? 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 puzzle
- 5. 5 Swiss Wastewater: Top 30 Peaks (ESI-) Schymanski et al. (2014), ES&T, 48: 1811-1818. DOI: 10.1021/es4044374 Artificial Sweeteners Diclofenac Pictures: www.coca-cola-com; www.rivella.ch; www.voltargengel.com
- 6. 6 Grouping Isotopes and Adducts Schymanski et al. (2014), ES&T, 48: 1811-1818. DOI: 10.1021/es4044374 0 3000 6000 9000 12000 15000 positive 2% 27% 100% Noise/Blank Targets Non-targets 0 3000 6000 9000 12000 15000 positivenegative 1% 30% 100%
- 7. 7 Swiss Wastewater: Top 30 Peaks (ESI-) Schymanski et al. (2014), ES&T, 48: 1811-1818. DOI: 10.1021/es4044374 S OO O - O S O - O CH2 m/z = 79.96 m/z = 183.01 Picture: www.momsteam.com
- 8. 8 Surfactant Screening From Literature Schymanski et al. (2014), ES&T, 48: 1811-1818. DOI: 10.1021/es4044374 Literature sources o Formulas, masses (ions), retention times and intensities o Spectra of selected compounds (different instruments) Gonzalez et al. Rapid Comm. Mass Spec. 2008, 22: 1445-54 Lara-Martin et al. EST. 2010, 44: 1670-1676
- 9. 9 Surfactant Screening From Literature Adding literature spectra to www.massbank.eu/MassBank/ Enable access and comparison Lara-Martin et al. EST. 2010, 44: 1670-1676 39 literature spectra (so far) Schymanski et al. (2014), ES&T, 48: 1811-1818. DOI: 10.1021/es4044374
- 10. 10 Supporting Evidence for Homologues M. Loos & H Singer, 2017. J. Cheminf. DOI: 10.1186/s13321-017-0197-z & Schymanski et al. 2014, ES&T DOI: 10.1021/es4044374 S OO OH CH3 CH3 m n DATS S OO OH O OH CH3 ()n ()m SPAC S OO OH O OHCH3 ()n ()m STAC http://www.envihomolog.eawag.ch/
- 11. 11 Supporting Evidence for Homologues Schymanski et al. (2014), ES&T, 48: 1811-1818. DOI: 10.1021/es4044374
- 12. 12 Supporting Evidence for Homologues Stravs et al. (2013), J. Mass Spectrom, 48(1):89-99. DOI: 10.1002/jms.3131 OHSO O CH3 O OH m n SPA-9C m+n=6 Formulas: http://sourceforge.net/projects/genform/ Meringer et al, 2011, MATCH 65, 259-290 Data: Schymanski et al. 2014, ES&T, 48: 1811-1818. DOI: 10.1021/es4044374 Chromatography and MS/MS Annotation Literature: LIT00034,35 Sample: ETS00002 Standard: ETS00016,17,19,20 https://github.com/MassBank/RMassBank/
- 13. 13 Swiss Wastewater: Top 30 Peaks (ESI-) Schymanski et al. (2014), ES&T, 48: 1811-1818. DOI: 10.1021/es4044374 Acesulfame Diclofenac Cyclamate Saccharin C10DATS C10SPAC SPA5C C15DATS STA6C C9DATS SPA2DC S OO OH O OH CH3 S OO OH CH3 CH3 ()n ()m SPAC DATS ()n ()m
- 14. 14 NORMAN Suspect Exchange o http://www.norman-network.com/?q=node/236 Schymanski, Aalizadeh et al. in prep.
- 15. 15 Eawag Surfactant List Schymanski et al 2014, ES&T, 48: 1811-1818. DOI: 10.1021/es4044374
- 16. 16 Using Generic Structures for Screening/Linking o https://github.com/schymane/RChemMass/
- 17. 17 Eawag Surfactant List (after many late nights…) Schymanski et al 2014, ES&T, 48: 1811-1818. DOI: 10.1021/es4044374 https://comptox.epa.gov/dashboard/chemical_lists/eawagsurf
- 18. 18 Eawag Surfactant List in CompTox Dashboard Schymanski, Grulke, Williams et al, in prep. & Williams et al. 2017 J. Cheminformatics 9:61 DOI: 10.1186/s13321-017-0247-6 https://comptox.epa.gov/dashboard/chemical_lists/eawagsurf CDK Depict
- 19. 19 Cross-Linking with Lists in CompTox Dashboard
- 20. 20 Structures now accessible for Computational MS Schymanski, Grulke, Williams et al, in prep. & Williams et al. 2017 J. Cheminformatics 9:61 DOI: 10.1186/s13321-017-0247-6 https://comptox.epa.gov/dashboard/chemical_lists/eawagsurf
- 22. 22
- 23. 23 European (World-)Wide Exchange of Suspects Schymanski et al. 2015, ABC, DOI: 10.1007/s00216-015-8681-7 NORMAN Suspect List Exchange: http://www.norman-network.com/?q=node/236 Schymanski et al. 2015, ABC, DOI: 10.1007/s00216-015-8681-7 Tentatively Identified Spectra: http://goo.gl/0t7jGp Hits in GNPS MassIVE datasets: TPs in skin: http://goo.gl/NmO4tx Surfactants: http://goo.gl/7sY9Pf
- 24. 24 2015: European Non-target Screening Trial Schymanski et al, 2014, ES&T. DOI: 10.1021/es5002105 & Schymanski et al. 2015, ABC, DOI: 10.1007/s00216-015-8681-7 Peak picking Non-target HR-MS(/MS) Acquisition Target Screening Suspect Screening Non-target Screening Start Level 1 Confirmed Structure by reference standard Level 2 Probable Structure by library/diagnostic evidence Start Level 3 Tentative Candidate(s) suspect, substructure, class Level 4 Unequivocal Molecular Formula insufficient structural evidence Start Level 5 Mass of Interest multiple detection, trends, … “downgrading” with contradictory evidence Increasing identification confidence Target list Suspect list Peak picking or XICs
- 25. 25 Eawag Surfactant List in CompTox Dashboard CDK Depict https://www.slideshare.net/AntonyWilliams/ markush-enumeration-to-manage-mesh-and-manipulate-substances-of-unknown-or-variable-composition
- 26. 26 Target, Suspect and Non-Target Screening KNOWNS SUSPECTS No Prior Knowledge HPLC separation and HR-MS/MS TARGET ANALYSIS SUSPECT SCREENING NON-TARGET SCREENING Targets found Suspects found Masses of interest (Molecular formula) DATABASE SEARCH STRUCTURE GENERATION Confirmation and quantification of compounds present Candidate selection (retention time, MS/MS, calculated properties) Sampling extraction (SPE) HPLC separation HR-MS/MS Time, Effort & Number of Compounds…. SUSPECTS SPECTRUM SEARCH Spectral match