Journal of the American Society for Mass Spectrometry

, Volume 20, Issue 9, pp 1593–1602 | Cite as

The contributions of molecular framework to IMS collision cross-sections of gas-phase peptide ions

  • Lei Tao
  • David B. Dahl
  • Lisa M. Pérez
  • David H. Russell


Molecular dynamics (MD) is an essential tool for correlating collision cross-section data determined by ion mobility spectrometry (IMS) with candidate (calculated) structures. Conventional methods used for ion structure determination rely on comparing the measured cross-sections with the calculated collision cross-section for the lowest energy structure(s) taken from a large pool of candidate structures generated through multiple tiers of simulated annealing. We are developing methods to evaluate candidate structures from an ensemble of many conformations rather than the lowest energy structure. Here, we describe computational simulations and clustering methods to assign backbone conformations for singly-protonated ions of the model peptide (NH2-Met-Ile-Phe-Ala-Gly-Ile-Lys-COOH) formed by both MALDI and ESI, and compare the structures of MIFAGIK derivatives to test the ‘sensitivity’ of the cluster analysis method. Cluster analysis suggests that [MIFAGIK + H]+ ions formed by MALDI have a predominantly turn structure even though the low-energy ions prefer partial helical conformers. Although the ions formed by ESI have collision cross-sections that are different from those formed by MALDI, the results of cluster analysis indicate that the ions backbone structures are similar. Chemical modifications (N-acetyl, methylester as well as addition of Boc or Fmoc groups) to MIFAGIK alter the distribution of various conformers; the most dramatic changes are observed for the [M + Na]+ ion, which show a strong preference for random coil conformers owing to the strong solvation by the backbone amide groups.


MALDI Fmoc Lower Energy Structure Populated Cluster Charge Site 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© American Society for Mass Spectrometry 2009

Authors and Affiliations

  • Lei Tao
    • 1
  • David B. Dahl
    • 2
  • Lisa M. Pérez
    • 3
  • David H. Russell
    • 1
  1. 1.The Laboratory for Biological Mass Spectrometry, Department of ChemistryTexas A and M UniversityCollege StationUSA
  2. 2.Department of StatisticsTexas A and M UniversityCollege StationUSA
  3. 3.The Laboratory for Molecular SimulationTexas A and M UniversityCollege StationUSA

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