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Consensus Ranking and Fragmentation Prediction for Identification of Unknowns in High Resolution Mass Spectrometry (ACS Spr2019)
Citation:
Williams, A., A. McEachran, T. Cathey, T. Transue, AND J. Sobus. Consensus Ranking and Fragmentation Prediction for Identification of Unknowns in High Resolution Mass Spectrometry (ACS Spr2019). Presented at American Chemical Society Spring meeting, Orlando, FL, March 31 - April 04, 2019. https://doi.org/10.23645/epacomptox.8085530
Impact/Purpose:
This presentation will provide an overview of a suite of functionality and data sources in the EPA CompTox Chemicals Dashboard that can be used for the identification of chemical substances in different media including food. Abstract and presentation at the Spring 2019 American Chemical Society meeting.
Description:
High resolution mass spectrometry (HRMS) and non-targeted analysis (NTA) have advanced structure identification of unknowns in various sources including environmental media and food stuffs. Structure identification requires the integration of complementary data types such as reference databases, fragmentation prediction tools, and retention time prediction models. One focus for the US EPA’s CompTox Chemicals Dashboard, an open chemistry resource and web application containing data for ~770,000 substances, is to implement structure identification functionality. This includes rank-ordering of candidates based on mass and formula searching across the chemicals collection and we have demonstrated that the number of data 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. Incorporating additional data streams contained within the database underlying the Dashboard further enhances identifications. Integrating tandem mass spectrometry data into NTA workflows enables spectral match scores and increases confidence in structural assignments. We have generated and stored predicted MS/MS fragmentation spectra for the entirety of the Chemistry Dashboard using the in silico fragmentation prediction tool CFM-ID. Predicted fragments incorporated into the identification workflow have been used as both a scoring term and as a candidate threshold cutoff. Combining these steps within an open chemistry resource provides a freely available software tool for structure identification and NTA. This presentation will provide an overview of a suite of functionality and data sources in the EPA CompTox Chemicals Dashboard that can be used for the identification of chemical substances in different media including food. This abstract does not necessarily represent the views or policies of the U.S. Environmental Protection Agency.
URLs/Downloads:
DOI: Consensus Ranking and Fragmentation Prediction for Identification of Unknowns in High Resolution Mass Spectrometry (ACS Spr2019)
WILLIAMS_ACS_CONSENSUS RANKING AND FRAGMENTATION PREDICTION IN HRMS_0324_2019.PDF (PDF, NA pp, 4508.697 KB, about PDF)