Shortlisting SARS‐CoV‐2 Peptides for Targeted Studies from Experimental Data‐Dependent Acquisition Tandem Mass Spectrometry Data
Abstract: Detection of severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) is a crucial tool for fighting the COVID‐19 pandemic. This dataset brief presents the exploration of a shotgun proteomics dataset acquired on SARS‐CoV‐2 infected Vero cells. Proteins from inactivated virus samples were extracted, digested with trypsin, and the resulting peptides were identified by data‐dependent acquisition tandem mass spectrometry. The 101 peptides reporting for six viral proteins were specifically analyzed in terms of their analytical characteristics, species specificity and conservation, and their proneness to structural modifications. Based on these results, a shortlist of 14 peptides from the N, S, and M main structural proteins that could be used for targeted mass‐spectrometry method development and diagnostic of the new SARS‐CoV‐2 is proposed and the best candidates are commented.
- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
-
Online-Ressource
- Sprache
-
Englisch
- Erschienen in
-
Shortlisting SARS‐CoV‐2 Peptides for Targeted Studies from Experimental Data‐Dependent Acquisition Tandem Mass Spectrometry Data ; volume:20 ; number:14 ; year:2020 ; extent:7
Proteomics ; 20, Heft 14 (2020) (gesamt 7)
- Urheber
-
Gouveia, Duarte
Grenga, Lucia
Gaillard, Jean‐Charles
Gallais, Fabrice
Bellanger, Laurent
Pible, Olivier
Armengaud, Jean
- DOI
-
10.1002/pmic.202000107
- URN
-
urn:nbn:de:101:1-2022061708183958364124
- Rechteinformation
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
15.08.2025, 07:28 MESZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Gouveia, Duarte
- Grenga, Lucia
- Gaillard, Jean‐Charles
- Gallais, Fabrice
- Bellanger, Laurent
- Pible, Olivier
- Armengaud, Jean
Ähnliche Objekte (12)
A machine learning approach to explore the spectra intensity pattern of peptides using tandem mass spectrometry data
Data-independent acquisition improves quantitative cross-linking mass spectrometry
Tandem mass spectrometry data quality assessment by self-convolution
Data acquisition methods for next-generation mass spectrometry-based proteomics
Combining data acquisition modes in liquid-chromatography–tandem mass spectrometry for comprehensive determination of acylcarnitines in human serum
Automating data analysis for hydrogen/deuterium exchange mass spectrometry using data-independent acquisition methodology
Author Correction: Automating data analysis for hydrogen/deuterium exchange mass spectrometry using data-independent acquisition methodology
Harnessing data science to improve molecular structure elucidation from tandem mass spectrometry
Citrulline Effect Is a Characteristic Feature of Deiminated Peptides in Tandem Mass Spectrometry
Mass spectrometry data mining
Multimodal FTIR Microscopy-guided Acquisition and Interpretation of MALDI Mass Spectrometry Imaging Data
Chromatogram libraries improve peptide detection and quantification by data independent acquisition mass spectrometry
A machine learning approach to explore the spectra intensity pattern of peptides using tandem mass spectrometry data
Data-independent acquisition improves quantitative cross-linking mass spectrometry
Tandem mass spectrometry data quality assessment by self-convolution
Data acquisition methods for next-generation mass spectrometry-based proteomics
Combining data acquisition modes in liquid-chromatography–tandem mass spectrometry for comprehensive determination of acylcarnitines in human serum
Automating data analysis for hydrogen/deuterium exchange mass spectrometry using data-independent acquisition methodology
Author Correction: Automating data analysis for hydrogen/deuterium exchange mass spectrometry using data-independent acquisition methodology
Harnessing data science to improve molecular structure elucidation from tandem mass spectrometry
Citrulline Effect Is a Characteristic Feature of Deiminated Peptides in Tandem Mass Spectrometry
Mass spectrometry data mining
Multimodal FTIR Microscopy-guided Acquisition and Interpretation of MALDI Mass Spectrometry Imaging Data
Chromatogram libraries improve peptide detection and quantification by data independent acquisition mass spectrometry
A machine learning approach to explore the spectra intensity pattern of peptides using tandem mass spectrometry data
Data-independent acquisition improves quantitative cross-linking mass spectrometry
Tandem mass spectrometry data quality assessment by self-convolution
Data acquisition methods for next-generation mass spectrometry-based proteomics
Combining data acquisition modes in liquid-chromatography–tandem mass spectrometry for comprehensive determination of acylcarnitines in human serum
Automating data analysis for hydrogen/deuterium exchange mass spectrometry using data-independent acquisition methodology
Author Correction: Automating data analysis for hydrogen/deuterium exchange mass spectrometry using data-independent acquisition methodology
Harnessing data science to improve molecular structure elucidation from tandem mass spectrometry
Citrulline Effect Is a Characteristic Feature of Deiminated Peptides in Tandem Mass Spectrometry
Mass spectrometry data mining
Multimodal FTIR Microscopy-guided Acquisition and Interpretation of MALDI Mass Spectrometry Imaging Data