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Systems BiologyNature Communications
Peer-reviewed journal article

Deep learning the collisional cross sections of the peptide universe from a million training samples

Florian MeieriD, Niklas Köhler, Andreas‐David BrunneriD, Jean-Marc H. Wanka, Eugenia VoytikiD, Maximilian T. StraussiD, Fabian Joachim TheisiD, Matthias ManniD

Abstract

The size and shape of peptide ions in the gas phase are an under-explored dimension for mass spectrometry-based proteomics. To explore the nature and utility of the entire 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, position of prolines and 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.

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02 /Specification & Classification

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