Vorhersage von Spektren für die Identifikation von Metaboliten und kleinen Molekülen

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, the latter cover only a small portion of the vast chemical space. The key objective of this project is to search general purpose compound libraries with tandem MS spectra. Because a mechanistic simulation of the process is computationally infeasable, we develop simplified models and machine learning. 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 calculate bond energies and bond strain upon protonation. In a separate project, Dr. Steinbeck (EBI, Hinxton) will develop methods for structure elucidation base on the complementary NMR technology. In a joint work package, we will combine the power of NMR and MS for computer aided structure elucidation.