De Novo peptide sequencing (Dancik et al., 1999 and Frank, 2009)

Peptide sequencing via tandem mass spectrometry (MS/MS) is one of the
most powerful tools in proteomics for identifying proteins. Because
complete genome sequences are accumulating rapidly, the recent trend
in interpretation of MS/MS spectra has been database search. However,
de novo MS/MS spectral interpretation remains an open problem
typically involving manual interpretation by expert mass
spectrometrists. We discuss the SHERENGA algorithm for de novo
interpretation that automatically learns fragment ion types and
intensity thresholds from a collection of test spectra generated from
any type of mass spectrometer. The test data are used to construct
optimal path scoring in the graph representations of MS/MS spectra. A
ranked list of high scoring paths corresponds to potential peptide
sequences. SHERENGA is most useful for interpreting sequences of
peptides resulting from unknown proteins and for validating the
results of database search algorithms in fully automated,
high-throughput peptide sequencing. The talk is based on the paper
(Dancik et al., 1999) and references therein.