PXD019086

PXD019086 is an original dataset announced via ProteomeXchange.

Title	Deep learning the collisional cross sections of the peptide universe from a million experimental values
Description	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 <1%) of our data is sufficient to train a recurrent neural network that accurately predicts CCS values solely based on the peptide sequence. Cross section predictions for the synthetic ProteomeTools library validate the model within a 1.3% median relative error (R > 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.
HostingRepository	PRIDE
AnnounceDate	2021-01-18
AnnouncementXML	Submission_2021-04-06_02:06:11.440.xml
DigitalObjectIdentifier
ReviewLevel	Peer-reviewed dataset
DatasetOrigin	Original dataset
RepositorySupport	Unsupported dataset by repository
PrimarySubmitter	Mario Oroshi
SpeciesList	scientific name: Escherichia coli; NCBI TaxID: 562; scientific name: Caenorhabditis elegans; NCBI TaxID: 6239; scientific name: Homo sapiens (Human); NCBI TaxID: 9606; scientific name: Saccharomyces cerevisiae (Baker's yeast); NCBI TaxID: 4932; scientific name: Drosophila melanogaster (Fruit fly); NCBI TaxID: 7227;
ModificationList	No PTMs are included in the dataset
Instrument	timsTOF Pro

Revision	Datetime	Status	ChangeLog Entry
0	2020-05-11 07:51:13	ID requested
1	2021-01-18 08:49:44	announced
⏵ 2	2021-04-06 02:06:12	announced	2021-04-06: Updated publication reference for PubMed record(s): 33608539.

Meier F, K, ö, hler ND, Brunner AD, Wanka JH, Voytik E, Strauss MT, Theis FJ, Mann M, Deep learning the collisional cross sections of the peptide universe from a million experimental values. Nat Commun, 12(1):1185(2021) [pubmed]

submitter keyword: Technical, ion mobility, CCS, TIMS, deep learning

Matthias Mann
contact affiliation	Department Proteomics and Signal Transduction Max Planck Institute of Biochemistry Am Klopferspitz 18 82152 Martinsried Germany
contact email	mmann@biochem.mpg.de
lab head
Mario Oroshi
contact affiliation	Proteomics
contact email	oroshi@biochem.mpg.de
dataset submitter

Dataset FTP location NOTE: Most web browsers have now discontinued native support for FTP access within the browser window. But you can usually install another FTP app (we recommend FileZilla) and configure your browser to launch the external application when you click on this FTP link. Or otherwise, launch an app that supports FTP (like FileZilla) and use this address: ftp://ftp.pride.ebi.ac.uk/pride/data/archive/2021/01/PXD019086

PRIDE project URI

• PRIDE
  1. PXD019086
     1. Label: PRIDE project
     2. Name: Deep learning the collisional cross sections of the peptide universe from a million experimental values