Collision Cross Section Calculations to Aid Metabolite Annotation.

Journal: Journal of the American Society for Mass Spectrometry
Published Date:

Abstract

The interpretation of ion mobility coupled to mass spectrometry (IM-MS) data to predict unknown structures is challenging and depends on accurate theoretical estimates of the molecular ion collision cross section (CCS) against a buffer gas in a low or atmospheric pressure drift chamber. The sensitivity and reliability of computational prediction of CCS values depend on accurately modeling the molecular state over accessible conformations. In this work, we developed an efficient CCS computational workflow using a machine learning model in conjunction with standard DFT methods and CCS calculations. Furthermore, we have performed Traveling Wave IM-MS (TWIMS) experiments to validate the extant experimental values and assess uncertainties in experimentally measured CCS values. The developed workflow yielded accurate structural predictions and provides unique insights into the likely preferred conformation analyzed using IM-MS experiments. The complete workflow makes the computation of CCS values tractable for a large number of conformationally flexible metabolites with complex molecular structures.

Authors

  • Susanta Das
    Department of Chemistry, Michigan State University, 578 South Shaw Lane, East Lansing, Michigan 48824, United States.
  • Kiyoto Aramis Tanemura
    Department of Chemistry, Michigan State University, 578 South Shaw Lane, East Lansing, Michigan 48824, United States.
  • Laleh Dinpazhoh
    Department of Chemistry, Michigan State University, 578 South Shaw Lane, East Lansing, Michigan 48824, United States.
  • Mithony Keng
    Department of Chemistry, Michigan State University, 578 South Shaw Lane, East Lansing, Michigan 48824, United States.
  • Christina Schumm
    Department of Chemistry, Michigan State University, 578 South Shaw Lane, East Lansing, Michigan 48824, United States.
  • Lydia Leahy
    Department of Chemistry, Michigan State University, 578 South Shaw Lane, East Lansing, Michigan 48824, United States.
  • Carter K Asef
    School of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, Georgia 30332, United States.
  • Markace Rainey
    School of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, Georgia 30332, United States.
  • Arthur S Edison
    Departments of Genetics and Biochemistry, Institute of Bioinformatics and Complex Carbohydrate Center, University of Georgia, 315 Riverbend Road, Athens, Georgia 30602, United States.
  • Facundo M Fernández
    School of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, Georgia 30332, United States.
  • Kenneth M Merz
    Departments of Chemistry and of Biochemistry and Molecular Biology, Michigan State University, East Lansing, Michigan 48824, United States.