Literature DB >> 22577017

Chromatographic retention time prediction for posttranslationally modified peptides.

Luminita Moruz1, An Staes, Joseph M Foster, Maria Hatzou, Evy Timmerman, Lennart Martens, Lukas Käll.   

Abstract

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 http://per-colator.com or can be run via a web-interface at http://elude.sbc.su.se.

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Year:  2012        PMID: 22577017     DOI: 10.1002/pmic.201100386

Source DB:  PubMed          Journal:  Proteomics        ISSN: 1615-9853            Impact factor:   3.984


  12 in total

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3.  Mass fingerprinting of complex mixtures: protein inference from high-resolution peptide masses and predicted retention times.

Authors:  Luminita Moruz; Michael R Hoopmann; Magnus Rosenlund; Viktor Granholm; Robert L Moritz; Lukas Käll
Journal:  J Proteome Res       Date:  2013-10-11       Impact factor: 4.466

4.  Protein Methionine Sulfoxide Dynamics in Arabidopsis thaliana under Oxidative Stress.

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Journal:  Mol Cell Proteomics       Date:  2015-02-18       Impact factor: 5.911

5.  DeepLC can predict retention times for peptides that carry as-yet unseen modifications.

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Journal:  Nat Methods       Date:  2021-10-28       Impact factor: 28.547

6.  Evaluation of Machine Learning Models for Proteoform Retention and Migration Time Prediction in Top-Down Mass Spectrometry.

Authors:  Wenrong Chen; Elijah N McCool; Liangliang Sun; Yong Zang; Xia Ning; Xiaowen Liu
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7.  Reliable determination of site-specific in vivo protein N-glycosylation based on collision-induced MS/MS and chromatographic retention time.

Authors:  Benlian Wang; Yaroslav Tsybovsky; Krzysztof Palczewski; Mark R Chance
Journal:  J Am Soc Mass Spectrom       Date:  2014-02-19       Impact factor: 3.109

Review 8.  Proteomics and the analysis of proteomic data: 2013 overview of current protein-profiling technologies.

Authors:  Can Bruce; Kathryn Stone; Erol Gulcicek; Kenneth Williams
Journal:  Curr Protoc Bioinformatics       Date:  2013-03

9.  Peptide Retention in Hydrophilic Strong Anion Exchange Chromatography Is Driven by Charged and Aromatic Residues.

Authors:  Sven H Giese; Yasushi Ishihama; Juri Rappsilber
Journal:  Anal Chem       Date:  2018-03-21       Impact factor: 6.986

10.  Optimized nonlinear gradients for reversed-phase liquid chromatography in shotgun proteomics.

Authors:  Luminita Moruz; Peter Pichler; Thomas Stranzl; Karl Mechtler; Lukas Käll
Journal:  Anal Chem       Date:  2013-07-24       Impact factor: 6.986

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