A potential golden age to come—current tools, recent use cases, and future avenues for de novo sequencing in proteomics

peer-reviewed · Proteomics · 2018

peer-reviewed · Proteomics · 2018. Thilo Muth et al. In shotgun proteomics, peptide and protein identification is most commonly conducted using database search…
Date 2018-09-01
Type peer-reviewed
Venue Proteomics
Publisher Wiley
Contribution review
DOI 10.1002/pmic.201700150
Citations (OpenAlex) 55
Venue 2-year citedness 2.96

Abstract

In shotgun proteomics, peptide and protein identification is most commonly conducted using database search engines, the method of choice when reference protein sequences are available. Despite its widespread use the database-driven approach is limited, mainly because of its static search space. In contrast, de novo sequencing derives peptide sequence information in an unbiased manner, using only the fragment ion information from the tandem mass spectra. In recent years, with the improvements in MS instrumentation, various new methods have been proposed for de novo sequencing. This review article provides an overview of existing de novo sequencing algorithms and software tools ranging from peptide sequencing to sequence-to-protein mapping. Various use cases are described for which de novo sequencing was successfully applied. Finally, limitations of current methods are highlighted and new directions are discussed for a wider acceptance of de novo sequencing in the community.

Authors

  1. Thilo Muth · Federal Institute for Materials Research and Testing (BAM), Max Planck Institute for Dynamics of Complex Technical Systems, Robert Koch Institute, glyXera GmbH
  2. Felix Hartkopf · Federal Institute for Materials Research and Testing (BAM)
  3. Marc Vaudel · Haukeland University Hospital, University of Bergen
  4. Bernhard Y. Renard · Hasso Plattner Institute, Robert Koch Institute

Methods and tools

  • Golden age of de novo review: Muth, Hartkopf, Vaudel & Renard 2018 review essay in Proteomics: state of the current de novo sequencing tool landscape, recent applied use cases, and outlook on where the field is heading.

Cites (57)

Cited by (24)

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