Abstract
The mass spectrometric identification of chemically cross-linked peptides (CXMS) specifies spatial restraints of protein complexes; these values complement data obtained from common structure-determination techniques. Generic methods for determining false discovery rates of cross-linked peptide assignments are currently lacking, thus making data sets from CXMS studies inherently incomparable. Here we describe an automated target-decoy strategy and the software tool xProphet, which solve this problem for large multicomponent protein complexes.
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Acknowledgements
This work was supported by the European Union 7th Framework project PROSPECTS (Proteomics Specification in Space and Time, grant HEALTH-F4-2008-201648) and ERC advanced grant 'Proteomics v3.0' (grant no. 233226) of the European Union to R.A. We thank O. Rinner and A.I. Nesvizhskii for constructive discussions.
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T.W. and A.L. performed cross-linking experiments and mass spectrometry analysis. T.W. and M.C. developed the target-decoy algorithm. T.W. analyzed the data and designed and wrote the software. S.B. purified 26S proteasomes; F.F. provided the structural model of the 26S proteasome; and T.W., A.L., S.B., M.C., F.H., F.F., M.B. and R.A. discussed and designed experiments. All authors contributed to writing the manuscript.
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Supplementary Text and Figures
Supplementary Figures 1–6, Supplementary Table 1, Supplementary Results 1–3 and Supplementary Methods (PDF 522 kb)
Supplementary Table 2
Identifications of the 8-mix data set. (XLSX 49 kb)
Supplementary Table 3
Identifications of the 26S data set. (XLSX 47 kb)
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Walzthoeni, T., Claassen, M., Leitner, A. et al. False discovery rate estimation for cross-linked peptides identified by mass spectrometry. Nat Methods 9, 901–903 (2012). https://doi.org/10.1038/nmeth.2103
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DOI: https://doi.org/10.1038/nmeth.2103
