Identification of cross-linked peptides from large sequence databases

Rinner, Oliver; Seebacher, Jan; Walzthoeni, Thomas; Mueller, Lukas N.; Beck, Martin; Schmidt, Alexander; Mueller, Markus; Aebersold, Ruedi

doi:10.1038/nmeth.1192

Item

ITEM ACTIONSEXPORT

Add to Basket

Local TagsRelease HistoryDetailsSummary

Released

Journal Article

Identification of cross-linked peptides from large sequence databases

MPS-Authors

There are no MPG-Authors in the publication available

External Resource

No external resources are shared

Fulltext (restricted access)

There are currently no full texts shared for your IP range.

Fulltext (public)

There are no public fulltexts stored in PuRe

Supplementary Material (public)

There is no public supplementary material available

Citation

Rinner, O., Seebacher, J., Walzthoeni, T., Mueller, L. N., Beck, M., Schmidt, A., et al. (2008). Identification of cross-linked peptides from large sequence databases. Nature Methods, 5(4), 315-318. doi:10.1038/nmeth.1192.

Cite as: https://hdl.handle.net/21.11116/0000-0007-0264-6

Abstract

We describe a method to identify cross-linked peptides from complex samples and large protein sequence databases by combining isotopically tagged cross-linkers, chromatographic enrichment, targeted proteomics and a new search engine called xQuest. This software reduces the search space by an upstream candidate-peptide search before the recombination step. We showed that xQuest can identify cross-linked peptides from a total Escherichia coli lysate with an unrestricted database search.