4.5 Article

Chromatographic retention time prediction for posttranslationally modified peptides

期刊

PROTEOMICS
卷 12, 期 8, 页码 1151-1159

出版社

WILEY-BLACKWELL
DOI: 10.1002/pmic.201100386

关键词

Bioinformatics; Machine learning; Posttranslational modification; Retention time prediction; Reversed-phase liquid chromatography

资金

  1. Swedish Research Council
  2. European Molecular Biology Foundation (EMBO)
  3. Ghent University
  4. European Union [262067-PRIME-XS]

向作者/读者索取更多资源

Retention time prediction of peptides in liquid chromatography has proven to be a valuable tool for mass spectrometry-based proteomics, especially in designing more efficient procedures for state-of-the-art targeted workflows. Additionally, accurate retention time predictions can also be used to increase confidence in identifications in shotgun experiments. Despite these obvious benefits, the use of such methods has so far not been extended to (posttranslationally) modified peptides due to the absence of efficient predictors for such peptides. We here therefore describe a new retention time predictor for modified peptides, built on the foundations of our existing Elude algorithm. We evaluated our software by applying it on five types of commonly encountered modifications. Our results show that Elude now yields equally good prediction performances for modified and unmodified peptides, with correlation coefficients between predicted and observed retention times ranging from 0.93 to 0.98 for all the investigated datasets. Furthermore, we show that our predictor handles peptides carrying multiple modifications as well. This latest version of Elude is fully portable to new chromatographic conditions and can readily be applied to other types of posttranslational modifications. Elude is available under the permissive Apache2 open source License at or can be run via a web-interface at .

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