Ab Initio Prediction of Molecular Fragments from Tandem Mass Spectrometry Data

Mass spectrometry is one of the key enabling measurement technologies for systems biology, due to its ability to quantify molecules in small concentrations. Tandem mass spectrometers tackle the main shortcoming of mass spectrometry, the fact that molecules with an equal mass-to-charge ratio are not separated. In tandem mass spectrometer molecules can be fragmented and the intensities of these fragments measured as well. However, this creates a need for methods for identifying the generated fragments. In this paper, we introduce a novel combinatorial approach for predicting the structure of molecular fragments that first enumerates all possible fragment candidates and then ranks them according the cost of cleaving a fragment from a molecule. Unlike many existing methods, our method does not rely on hand-coded fragmentation rule databases. Our method is able to predict the correct fragmentation of small-to-medium sized molecules with high accuracy.