Suspect screening of environmental contaminants by UHPLC-HRMS and transposable Quantitative Structure-Retention Relationship modelling
A Quantitative Structure-Retention Relationship (QSRR) model is proposed and aims at increasing the confidence level associated to the identification of organic contaminants by Ultra-High Performance Liquid Chromatography hyphenated to High Resolution Mass Spectrometry (UHPLC-HRMS) in environmental...
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Veröffentlicht in: | Journal of hazardous materials 2021-05, Vol.409, p.124652-124652, Article 124652 |
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Sprache: | eng |
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Zusammenfassung: | A Quantitative Structure-Retention Relationship (QSRR) model is proposed and aims at increasing the confidence level associated to the identification of organic contaminants by Ultra-High Performance Liquid Chromatography hyphenated to High Resolution Mass Spectrometry (UHPLC-HRMS) in environmental samples under a suspect screening approach. The model was built from a selection of 8 easily accessible physicochemical descriptors, and was validated from a set of 274 organic compounds commonly found in environmental samples. The proposed predictive figure approach is based on the mobile phase composition at solute elution (expressed as % acetonitrile), that has the major advantage of making the model reusable by other laboratories, since the elution composition is independent of both the column geometry and the UHPLC-system. The model quality was assessed and was altered neither by the columns from different lots, nor by the complex matrices of environmental water samples. Then, the solute retention of any organic compound present in water samples is expected to be predicted within ± 14.3% acetonitrile by our model. Solute retention can therefore be used as a supplementary tool for the identification of environmental contaminants by UHPLC-HRMS, in addition to mass spectrometry data already used in the suspect screening approach.
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•A Quantitative Structure-Retention Relationship model was built to improve suspect screening of environmental contaminants.•A novel approach using mobile phase composition at solute elution was introduced, making the model easily transposable.•We thoroughly validated the method and determined the degree of uncertainty of its predictions.•We showed the feasibility, efficiency and limitations of this approach through various application examples. |
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ISSN: | 0304-3894 1873-3336 |
DOI: | 10.1016/j.jhazmat.2020.124652 |