Deep learning the collisional cross sections of the peptide universe from a million experimental values

Florian Meier, Niklas D. Köhler, Andreas-David Brunner, Jean-Marc H. Wanka, Eugenia Voytik, Maximilian T. Strauss, Fabian J. Theis () and Matthias Mann ()
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Florian Meier: Max Planck Institute of Biochemistry
Niklas D. Köhler: Institute of Computational Biology, Helmholtz Zentrum München—German Research Center for Environmental Health
Andreas-David Brunner: Max Planck Institute of Biochemistry
Jean-Marc H. Wanka: Institute of Computational Biology, Helmholtz Zentrum München—German Research Center for Environmental Health
Eugenia Voytik: Max Planck Institute of Biochemistry
Maximilian T. Strauss: Max Planck Institute of Biochemistry
Fabian J. Theis: Institute of Computational Biology, Helmholtz Zentrum München—German Research Center for Environmental Health
Matthias Mann: Max Planck Institute of Biochemistry

Nature Communications, 2021, vol. 12, issue 1, 1-12

Abstract: Abstract The size and shape of peptide ions in the gas phase are an under-explored dimension for mass spectrometry-based proteomics. To investigate the nature and utility of the peptide collisional cross section (CCS) space, we measure more than a million data points from whole-proteome digests of five organisms with trapped ion mobility spectrometry (TIMS) and parallel accumulation-serial fragmentation (PASEF). The scale and precision (CV 0.99). Hydrophobicity, proportion of prolines and position of histidines are main determinants of the cross sections in addition to sequence-specific interactions. CCS values can now be predicted for any peptide and organism, forming a basis for advanced proteomics workflows that make full use of the additional information.

Date: 2021
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DOI: 10.1038/s41467-021-21352-8

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