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Purple: A Computational Workflow for Strategic Selection of Peptides for Viral Diagnostics Using MS-Based Targeted Proteomics

1
Bioinformatics Unit (MF 1), Department for Methods Development and Research Infrastructure, Robert Koch Institute, 13353 Berlin, Germany
2
Centre for Biological Threats and Special Pathogens, Highly Pathogenic Viruses (ZBS1), Robert Koch Institute, 13353 Berlin, Germany
3
Centre for Biological Threats and Special Pathogens, Proteomics and Spectroscopy (ZBS 6), Robert Koch Institute, 13353 Berlin, Germany
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Viruses 2019, 11(6), 536; https://doi.org/10.3390/v11060536
Received: 19 March 2019 / Revised: 3 June 2019 / Accepted: 4 June 2019 / Published: 8 June 2019
(This article belongs to the Special Issue Virus Bioinformatics)
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Abstract

Emerging virus diseases present a global threat to public health. To detect viral pathogens in time-critical scenarios, accurate and fast diagnostic assays are required. Such assays can now be established using mass spectrometry-based targeted proteomics, by which viral proteins can be rapidly detected from complex samples down to the strain-level with high sensitivity and reproducibility. Developing such targeted assays involves tedious steps of peptide candidate selection, peptide synthesis, and assay optimization. Peptide selection requires extensive preprocessing by comparing candidate peptides against a large search space of background proteins. Here we present Purple (Picking unique relevant peptides for viral experiments), a software tool for selecting target-specific peptide candidates directly from given proteome sequence data. It comes with an intuitive graphical user interface, various parameter options and a threshold-based filtering strategy for homologous sequences. Purple enables peptide candidate selection across various taxonomic levels and filtering against backgrounds of varying complexity. Its functionality is demonstrated using data from different virus species and strains. Our software enables to build taxon-specific targeted assays and paves the way to time-efficient and robust viral diagnostics using targeted proteomics. View Full-Text
Keywords: virus proteomics; mass spectrometry; virus diagnostics; data analysis; targeted proteomics; peptide selection; parallel reaction monitoring virus proteomics; mass spectrometry; virus diagnostics; data analysis; targeted proteomics; peptide selection; parallel reaction monitoring
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Lechner, J.; Hartkopf, F.; Hiort, P.; Nitsche, A.; Grossegesse, M.; Doellinger, J.; Renard, B.Y.; Muth, T. Purple: A Computational Workflow for Strategic Selection of Peptides for Viral Diagnostics Using MS-Based Targeted Proteomics. Viruses 2019, 11, 536.

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