Mass spectrometry for compound identification relies on established databases. Once MS spectral prediction algorithms are validated, there is a critical need for comprehensive libraries of predicted spectra for unknown and theoretical molecules (amino acids). Wherever reliable theoretical databases of predicted mass spectra can be formed, they will allow for greater expansion of potential search space for an unknown molecule in a sample. Such tools would have broad uses from informing NASA mission data (e.g. Mars Sample Return ) to expanding public health surveillance 29 . For instance, the Robert Koch Institute has designed a MALDI-TOF MS database specifically to identify pathogenic bacteria (ibid) and the National Institute of Standards and Technology (NIST) has begun modelling fragmentation energetics to enable unknown compound identification through theoretical spectra . Beyond amino acids, predictions that allow us to extend to other classes of biomolecules (e.g. lipids, sugars, or nucleic acid derivatives) would further advance many disciplines.