Prediction of Posttranslational Modifications Using Intact-Protein Mass Spectrometric Data

We present a Web-based application that uses whole-protein masses determined by mass spectrometry to
identify putative co- and posttranslational proteolytic
cleavages and chemical modifications. The protein cleavage and modification engine (PROCLAME) requires as
input an intact mass measurement and a precursor
identification based on peptide mass fingerprinting or
tandem mass spectrometry. This approach predicts mass-modifying events using a depth-first tree search, bounded
by a set of rules controlled by a custom-built fuzzy logic
engine, to explore a large number of possible combinations of modifications accounting for the experimental
mass. Candidates are saved during a search if they are
within a user-specified instrument mass accuracy; the
total number of possible candidates searched is based on
a specified fuzzy cutoff score. Candidates are scored and
ranked using a simple probabilistic model. There is
generally not enough information in an intact mass
measurement to determine a single unique protein characterization; however, the program provides utility by
expediting the identification of sets of putative events
consistent with the mass data and ranking them for further
investigation. This approach uses a simple, intuitive rule
base and lends itself to discovery of unannotated posttranslational events. We have assessed the program with
both in silico-generated test data and with published data
from an analysis of large ribosomal subunit proteins, both
from the yeast S. cerevisiae. Results indicate a high
degree of sensitivity and specificity in characterizing
proteins whose masses resulted from reasonable proteolysis and covalent modification scenarios. The application is available on the web at http://proclame.unc.edu.