Identification of metabolites and small compounds using mass spectrometry

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Mass spectrometry is a key technology for the identification of small molecules. Today, the identification of metabolites from mass spectra relies on the comparison with authentic compounds or reference spectra. The first are often expensive to obtain, the latter cover only a small portion of the vast chemical space. The key objective of the ChemFrag project is to identify compounds with tandem mass spectrometry in candidates obtained from general purpose compound libraries. Because a mechanistic simulation of the process is computationally infeasible, we develop simplified in-silico fragmentation methods, statistical models and apply machine learning to a large set of training spectra. Our approach screens a set of candidate molecules, to find molecular fragments which explain the experimentally measured peaks. In addition to a simple bond disconnection approach on the molecular graph, we incorporate the chemical context and precalculated bond energies and bond strain upon protonation.