Please use this identifier to cite or link to this item: http://dx.doi.org/10.14279/depositonce-11582
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Main Title: Peptide retention in hydrophilic strong anion exchange chromatography is driven by charged and aromatic residues
Author(s): Giese, Sven H.
Ishihama, Yasushi
Rappsilber, Juri
Type: Article
URI: https://depositonce.tu-berlin.de/handle/11303/12782
http://dx.doi.org/10.14279/depositonce-11582
License: https://creativecommons.org/licenses/by/4.0/
Abstract: Hydrophilic strong anion exchange chromatography (hSAX) is becoming a popular method for the prefractionation of proteomic samples. However, the use and further development of this approach is affected by the limited understanding of its retention mechanism and the absence of elution time prediction. Using a set of 59 297 confidentially identified peptides, we performed an explorative analysis and built a predictive deep learning model. As expected, charged residues are the major contributors to the retention time through electrostatic interactions. Aspartic acid and glutamic acid have a strong retaining effect and lysine and arginine have a strong repulsion effect. In addition, we also find the involvement of aromatic amino acids. This suggests a substantial contribution of cation−π interactions to the retention mechanism. The deep learning approach was validated using 5-fold cross-validation (CV) yielding a mean prediction accuracy of 70% during CV and 68% on a hold-out validation set. The results of this study emphasize that not only electrostatic interactions but rather diverse types of interactions must be integrated to build a reliable hSAX retention time predictor.
Subject(s): bioinformatics
proteomics
deep learning
Issue Date: 12-Mar-2018
Date Available: 11-Mar-2021
Is Part Of: 10.14279/depositonce-12031
Language Code: en
DDC Class: 570 Biowissenschaften; Biologie
Journal Title: Analytical Chemistry
Publisher: American Chemical Society (ACS)
Volume: 90
Issue: 7
Publisher DOI: 10.1021/acs.analchem.7b05157
Page Start: 4635
Page End: 4640
EISSN: 1520-6882
ISSN: 0003-2700
TU Affiliation(s): Fak. 3 Prozesswissenschaften » Inst. Biotechnologie » FG Bioanalytik
Appears in Collections:Technische Universität Berlin » Publications

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