Column selection for comprehensive two-dimensional liquid chromatography using the hydrophobic subtraction model

Rebecca K. Lindsey; Becky L. Eggimann; Dwight R. Stoll; Peter W. Carr; Mark R. Schure; J. Ilja Siepmann

doi:10.1016/j.chroma.2018.09.018

Column selection for comprehensive two-dimensional liquid chromatography using the hydrophobic subtraction model

Rebecca K. Lindsey, Becky L. Eggimann, Dwight R. Stoll, Peter W. Carr, Mark R. Schure, J. Ilja Siepmann

Chemistry (Twin Cities)

Research output: Contribution to journal › Article › peer-review

13 Scopus citations

Abstract

Two-dimensional (2D) liquid chromatography (2DLC) methods have grown in popularity due to their enhanced peak capacity that allows for resolving complex samples. Given the large number of commercially available column types, one of the major challenges in implementing 2DLC methods is the selection of suitable column pairs. Column selection is typically informed by chemical intuition with subsequent experimental optimization. In this work a computational screening method for 2DLC is proposed whereby virtual 2D chromatograms are calculated utilizing the Snyder–Dolan hydrophobic subtraction model (HSM) for reversed-phase column selectivity. Towards this end, 319 225 column pairs resulting from the combination of 565 columns and 100 sets of 1000 diverse analytes are examined. Compared to other screening approaches, the present method is highly predictive for column pairs that are able to resolve the largest number of analytes. This approach shows a strong sensitivity to the choice of the second dimension column (having a shorter operating time) and a preference for those with embedded polar moieties, whereas a relatively weak preference for C ₁₈ and phenyl columns is found for the first dimension.

Original language	English (US)
Pages (from-to)	47-55
Number of pages	9
Journal	Journal of Chromatography A
Volume	1589
DOIs	https://doi.org/10.1016/j.chroma.2018.09.018
State	Published - Mar 29 2019

Bibliographical note

Funding Information:
Financial support from the National Science Foundation (CHE-1152998 and CHE-1213244) is gratefully acknowledged. Computer resources were provided by the Minnesota Supercomputing Institute at the University of Minnesota.

Funding Information:
Financial support from the National Science Foundation ( CHE-1152998 and CHE-1213244 ) is gratefully acknowledged. Computer resources were provided by the Minnesota Supercomputing Institute at the University of Minnesota.

Publisher Copyright:
© 2018 Elsevier B.V.

Keywords

Hydrophobic subtraction model
Reversed-phase liquid chromatography
Two-dimensional chromatography

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10.1016/j.chroma.2018.09.018

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title = "Column selection for comprehensive two-dimensional liquid chromatography using the hydrophobic subtraction model",

abstract = " Two-dimensional (2D) liquid chromatography (2DLC) methods have grown in popularity due to their enhanced peak capacity that allows for resolving complex samples. Given the large number of commercially available column types, one of the major challenges in implementing 2DLC methods is the selection of suitable column pairs. Column selection is typically informed by chemical intuition with subsequent experimental optimization. In this work a computational screening method for 2DLC is proposed whereby virtual 2D chromatograms are calculated utilizing the Snyder–Dolan hydrophobic subtraction model (HSM) for reversed-phase column selectivity. Towards this end, 319 225 column pairs resulting from the combination of 565 columns and 100 sets of 1000 diverse analytes are examined. Compared to other screening approaches, the present method is highly predictive for column pairs that are able to resolve the largest number of analytes. This approach shows a strong sensitivity to the choice of the second dimension column (having a shorter operating time) and a preference for those with embedded polar moieties, whereas a relatively weak preference for C 18 and phenyl columns is found for the first dimension.",

keywords = "Hydrophobic subtraction model, Reversed-phase liquid chromatography, Two-dimensional chromatography",

author = "Lindsey, {Rebecca K.} and Eggimann, {Becky L.} and Stoll, {Dwight R.} and Carr, {Peter W.} and Schure, {Mark R.} and Siepmann, {J. Ilja}",

note = "Funding Information: Financial support from the National Science Foundation (CHE-1152998 and CHE-1213244) is gratefully acknowledged. Computer resources were provided by the Minnesota Supercomputing Institute at the University of Minnesota. Funding Information: Financial support from the National Science Foundation ( CHE-1152998 and CHE-1213244 ) is gratefully acknowledged. Computer resources were provided by the Minnesota Supercomputing Institute at the University of Minnesota. Publisher Copyright: {\textcopyright} 2018 Elsevier B.V.",

year = "2019",

month = mar,

day = "29",

doi = "10.1016/j.chroma.2018.09.018",

language = "English (US)",

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pages = "47--55",

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AU - Lindsey, Rebecca K.

AU - Eggimann, Becky L.

AU - Stoll, Dwight R.

AU - Carr, Peter W.

AU - Schure, Mark R.

AU - Siepmann, J. Ilja

N1 - Funding Information: Financial support from the National Science Foundation (CHE-1152998 and CHE-1213244) is gratefully acknowledged. Computer resources were provided by the Minnesota Supercomputing Institute at the University of Minnesota. Funding Information: Financial support from the National Science Foundation ( CHE-1152998 and CHE-1213244 ) is gratefully acknowledged. Computer resources were provided by the Minnesota Supercomputing Institute at the University of Minnesota. Publisher Copyright: © 2018 Elsevier B.V.

PY - 2019/3/29

Y1 - 2019/3/29

N2 - Two-dimensional (2D) liquid chromatography (2DLC) methods have grown in popularity due to their enhanced peak capacity that allows for resolving complex samples. Given the large number of commercially available column types, one of the major challenges in implementing 2DLC methods is the selection of suitable column pairs. Column selection is typically informed by chemical intuition with subsequent experimental optimization. In this work a computational screening method for 2DLC is proposed whereby virtual 2D chromatograms are calculated utilizing the Snyder–Dolan hydrophobic subtraction model (HSM) for reversed-phase column selectivity. Towards this end, 319 225 column pairs resulting from the combination of 565 columns and 100 sets of 1000 diverse analytes are examined. Compared to other screening approaches, the present method is highly predictive for column pairs that are able to resolve the largest number of analytes. This approach shows a strong sensitivity to the choice of the second dimension column (having a shorter operating time) and a preference for those with embedded polar moieties, whereas a relatively weak preference for C 18 and phenyl columns is found for the first dimension.

AB - Two-dimensional (2D) liquid chromatography (2DLC) methods have grown in popularity due to their enhanced peak capacity that allows for resolving complex samples. Given the large number of commercially available column types, one of the major challenges in implementing 2DLC methods is the selection of suitable column pairs. Column selection is typically informed by chemical intuition with subsequent experimental optimization. In this work a computational screening method for 2DLC is proposed whereby virtual 2D chromatograms are calculated utilizing the Snyder–Dolan hydrophobic subtraction model (HSM) for reversed-phase column selectivity. Towards this end, 319 225 column pairs resulting from the combination of 565 columns and 100 sets of 1000 diverse analytes are examined. Compared to other screening approaches, the present method is highly predictive for column pairs that are able to resolve the largest number of analytes. This approach shows a strong sensitivity to the choice of the second dimension column (having a shorter operating time) and a preference for those with embedded polar moieties, whereas a relatively weak preference for C 18 and phenyl columns is found for the first dimension.

KW - Hydrophobic subtraction model

KW - Reversed-phase liquid chromatography

KW - Two-dimensional chromatography

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ER -

Column selection for comprehensive two-dimensional liquid chromatography using the hydrophobic subtraction model

Abstract

Bibliographical note

Keywords

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