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Pretrained Deep Protein Language Model-Aided Estimation of Collision Cross Section

ABSTRACT: Collision cross section (CCS) of peptide ions provides an important separation dimension in liquid chromatography/tandem mass spectrometry-based proteomics that incorporates ion mobility spectrometry (IMS), and its accurate prediction is the basis for advanced proteomics workflows. We constructed an experimental peptide CCS dataset using phosphoproteome data. To obtain a unique set of peptides, we digested HeLa cell extracts with seven proteases (trypsin, LysargiNase, Lys-C, Lys-N, Glu-C, Asp-N, and chymotrypsin), enriched phosphopeptides from the digests, and fractionated the resulting phospho peptides with SCX-StageTip. We then dephosphorylated the phosphopeptides using calf intestine alkaline phosphatase to generate non-phosphorylated peptides with more missed cleavages.

ORGANISM(S): Homo Sapiens (human)

SUBMITTER: Yasushi Ishihama

PROVIDER: PXD046201 | JPOST Repository | Sat May 03 00:00:00 BST 2025

REPOSITORIES: jPOST

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			Action	DRS
	200703ko02phosphoTryp_SCXFr00_inclALL_Slot1-01_1_11455.d.zip	Other
	200703ko03phosphoTryp_SCXFr01_inclALL_Slot1-01_1_11456.d.zip	Other
	200703ko04phosphoTryp_SCXFr02_Slot1-01_1_11457.d.zip	Other
	200703ko05phosphoTryp_SCXFr03_Slot1-01_1_11458.d.zip	Other
	200703ko06phosphoTryp_SCXFr04_Slot1-01_1_11459.d.zip	Other

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