Journal
JOURNAL OF PROTEOME RESEARCH
Volume 9, Issue 5, Pages 2488-2495Publisher
AMER CHEMICAL SOC
DOI: 10.1021/pr901163d
Keywords
protein-protein interaction; peptide identification; calibration; cross-linked peptides
Categories
Funding
- NIH/NCRR [R01 EB007057, P41 RR0011823]
- NIH/NIAID [5 U54 AI057141-03]
- NATIONAL CENTER FOR RESEARCH RESOURCES [P41RR011823] Funding Source: NIH RePORTER
- NATIONAL INSTITUTE OF ALLERGY AND INFECTIOUS DISEASES [U54AI057141] Funding Source: NIH RePORTER
- NATIONAL INSTITUTE OF BIOMEDICAL IMAGING AND BIOENGINEERING [R01EB007057] Funding Source: NIH RePORTER
- NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES [R01GM096306] Funding Source: NIH RePORTER
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Mass spectrometric identification of cross-linked peptides can provide valuable information about the structure of protein complexes. We describe a straightforward database search scheme that identifies and assigns statistical confidence estimates to spectra from cross-linked peptides. The method is well suited to targeted analysis of a single protein complex, without requiring an isotope labeling strategy. Our approach uses a SEQUEST-style search procedure in which the database is comprised of a mixture of single peptides with and without linkers attached and cross-linked products. In contrast to several previous approaches, we generate theoretical spectra that account for all of the expected peaks from a cross-linked product, and we employ an empirical curve-fitting procedure to estimate statistical confidence measures. We show that our fully automated procedure successfully reidentifies spectra from a previous study, and we provide evidence that our statistical confidence estimates are accurate.
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