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Predicting Compound Amenability with Liquid Chromatography Mass Spectrometry to Improve Non-targeted Analysis (QSAR 2021)
Citation:
Lowe, C., K. Isaacs, A. McEachran, Chris Grulke, J. Sobus, E. Ulrich, A. Richard, A. Chao, J. Wambaugh, AND A. Williams. Predicting Compound Amenability with Liquid Chromatography Mass Spectrometry to Improve Non-targeted Analysis (QSAR 2021). QSAR 2021 International Workshop on QSAR in Environmental and Health Sciences, Virtual, NC, June 07 - 10, 2021. https://doi.org/10.23645/epacomptox.15078534
Impact/Purpose:
Presentation to the QSAR 2021 International Workshop on QSAR in Environmental and Health Sciences June 2021. Non-targeted analysis (NTA) strives to detect and identify a wide range of chemicals without preconceived target list or standards. Such efforts can be applied to and use a variety of exposure science efforts, including basic research into the technique (ENTACT), informatics tools (CompTox Chemicals Dashboard), complex mixtures (UVCBs) and pairing exposure to effects (EDA). Approximately 30 laboratories worldwide are characterizing their non-targeted analysis approaches. Because the instrumental and data processing methods vary significantly, so do performance metrics. Physicochemical properties are statistically different between instrumental method choices (gas vs. liquid chromatography, electrospray vs. atmospheric pressure chemical ionization) showing the techniques cover different portions of chemical space. Current and future NTA research areas are also linked to larger scientific efforts within the exposure community at EPA.
Description:
With the increasing availability of high-resolution mass spectrometers, suspect screening and non-targeted analysis are becoming popular compound-identification tools for environmental researchers. Samples of interest often contain a large (unknown) number of chemicals spanning the detectable mass range of the instrument. In an effort to separate these chemicals prior to injection into the mass spectrometer, a chromatography method is often utilized. There are numerous types of gas and liquid chromatographs that can be coupled to commercially available mass spectrometers. Depending on the instrument used, the researcher is likely to observe different compounds based on the amenability of those chemicals. It would be advantageous if this subset of chemicals could be predicted prior to conducting the experiment, to minimize potential false positive identifications. In this work, we combine experimental data associated with the US EPA’s ToxCast library, along with mass spectrometry data from the MassBank of North America (MONA) database, to predict the amenability of unique compounds with liquid chromatography mass spectrometry (LC-MS). The assembled dataset totals 5,517 unique chemicals either explicitly detected or not detected with LC-MS. The resulting detected/not-detected matrix has been combined with PaDEL molecular descriptors to model which chemicals are amenable to LC-MS. We have constructed random forest models for both positive and negative modes of the electrospray ionization source. The outcome of this work should help inform future suspect screening and non-targeted analyses of potential chemical compound identities. This abstract does not necessarily represent the views or policies of the US EPA.
URLs/Downloads:
DOI: Predicting Compound Amenability with Liquid Chromatography Mass Spectrometry to Improve Non-targeted Analysis (QSAR 2021)
LOWE_AMENABILITY_QSAR_05182021_DC.PDF (PDF, NA pp, 344.892 KB, about PDF)