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2021-02-22Zeitschriftenartikel DOI: 10.25646/8796
Application of spectral library prediction for parallel reaction monitoring of viral peptides
dc.contributor.authorGrossegesse, Marica
dc.contributor.authorNitsche, Andreas
dc.contributor.authorSchaade, Lars
dc.contributor.authorDöllinger, Jörg
dc.date.accessioned2021-07-13T05:51:58Z
dc.date.available2021-07-13T05:51:58Z
dc.date.issued2021-02-22none
dc.identifier.other10.1002/pmic.202000226
dc.identifier.urihttp://edoc.rki.de/176904/8521
dc.description.abstractA major part of the analysis of parallel reaction monitoring (PRM) data is the comparison of observed fragment ion intensities to a library spectrum. Classically, these libraries are generated by data-dependent acquisition (DDA). Here, we test Prosit, a published deep neural network algorithm, for its applicability in predicting spectral libraries for PRM. For this purpose, we targeted 1529 precursors derived from synthetic viral peptides and analyzed the data with Prosit and DDA-derived libraries. Viral peptides were chosen as an example, because virology is an area where in silico library generation could significantly improve PRM assay design. With both libraries a total of 1174 precursors were identified. Notably, compared to the DDA-derived library, we could identify 101 more precursors by using the Prosit-derived library. Additionally, we show that Prosit can be applied to predict tandem mass spectra of synthetic viral peptides with different collision energies. Finally, we used a spectral library predicted by Prosit and a DDA library to identify SARS-CoV-2 peptides from a simulated oropharyngeal swab demonstrating that both libraries are suited for peptide identification by PRM. Summarized, Prosit-derived viral spectral libraries predicted in silico can be used for PRM data analysis, making DDA analysis for library generation partially redundant in the future.eng
dc.language.isoengnone
dc.publisherRobert Koch-Institut
dc.rights(CC BY 3.0 DE) Namensnennung 3.0 Deutschlandger
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/de/
dc.subject.ddc610 Medizin und Gesundheitnone
dc.titleApplication of spectral library prediction for parallel reaction monitoring of viral peptidesnone
dc.typearticle
dc.identifier.urnurn:nbn:de:kobv:0257-176904/8521-5
dc.identifier.doihttp://dx.doi.org/10.25646/8796
dc.type.versionupdatedVersionnone
local.edoc.container-titleProteomicsnone
local.edoc.container-issn1615-9861none
local.edoc.pages5none
local.edoc.type-nameZeitschriftenartikel
local.edoc.container-typeperiodical
local.edoc.container-type-nameZeitschrift
local.edoc.container-urlhttps://analyticalsciencejournals.onlinelibrary.wiley.com/doi/10.1002/pmic.202000226none
local.edoc.container-publisher-nameWiley Online Librarynone
local.edoc.container-volume21none
local.edoc.container-issue7-8none
local.edoc.rki-departmentZentrum für Biologische Gefahren und Spezielle Pathogenenone
dc.description.versionPeer Reviewednone

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