An approach that has been developed to address the problem of limited amount of experimental spectra data is in silico fragmentation which essentially attempts to solve the inverse problem. This approach aims at enhancing the content of existing spectra databases with computed spectra of known molecular structures which have no available experimental spectra. Essentially this approach seeks to close the gap between spectral and structural databases. In silico fragmentation tools predict the fragmentation process either relying on fragmentation rules or using combinatorial/optimization-based approaches or employing machine learning methodologies . Fragment prediction methods have been especially successful for predicting spectra of peptides, however, fragmentation of small molecules into ions is a more stochastic process that is especially challenging to predict .