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Exploring skyline for both MS E ‐based label‐free proteomics and HRMS quantitation of small molecules
Author(s) -
Liu Shanshan,
Chen Xin,
Yan Zhihui,
Qin Shanshan,
Xu Jinhua,
Lin Jianping,
Yang Cheng,
Shui Wenqing
Publication year - 2014
Publication title -
proteomics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.26
H-Index - 167
eISSN - 1615-9861
pISSN - 1615-9853
DOI - 10.1002/pmic.201300352
Subject(s) - skyline , workflow , quantitative proteomics , computer science , proteomics , data mining , software , label free quantification , computational biology , chemistry , database , biology , operating system , biochemistry , gene
The MS E (where MS E is low energy ( MS ) and elevated energy ( E ) mode of acquisition) acquisition method commercialized by Waters on its Q ‐ TOF instruments is regarded as a unique data‐independent fragmentation approach that improves the accuracy and dynamic range of label‐free proteomic quantitation. Due to its special format, MS E acquisition files cannot be independently analyzed with most widely used open‐source proteomic software specialized for processing data‐dependent acquisition files. In this study, we established a workflow integrating S kyline, a popular and versatile peptide‐centric quantitation program, and a statistical tool DiffProt to fulfill MS E ‐based proteomic quantitation. Comparison with the vendor software package for analyzing targeted phosphopeptides and global proteomic datasets reveals distinct advantages of Skyline in MS E data mining, including sensitive peak detection, flexible peptide filtering, and transparent step‐by‐step workflow. Moreover, we developed a new procedure such that S kyline MS 1 filtering was extended to small molecule quantitation for the first time. This new utility of Skyline was examined in a protein–ligand interaction experiment to identify multiple chemical compounds specifically bound to NDM ‐1 (where NDM is N ew D elhi metallo‐β‐lactamase 1), an antibiotics‐resistance target. Further improvement of the current weaknesses in S kyline MS 1 filtering is expected to enhance the reliability of this powerful program in full scan‐based quantitation of both peptides and small molecules.