Generative Algorithm for Molecular Graphs Uncovers Products of Oil Oxidation

The autoxidation of triglyceride (or triacylglycerol, TAG) is a poorly understood complex system. It is known from mass spectrometry measurements that, although initiated by a single molecule, this system involves an abundance of intermediate species and a complex network of reactions. For this reason, the attribution of the mass peaks to exact molecular structures is difficult without additional information about the system. We provide such information using a graph theory-based algorithm. Our algorithm performs an automatic discovery of the chemical reaction network that is responsible for the complexity of the mass spectra in drying oils. This knowledge is then applied to match experimentally measured mass spectra with computationally predicted molecular graphs. We demonstrate this methodology on the autoxidation of triolein as measured by electrospray ionization-mass spectrometry (ESI-MS). Our protocol can be readily applied to investigate other oils and their mixtures.

Automated summary

The autoxidation of triglyceride is a complex system involving numerous intermediate species and a complex network of reactions. A graph theory-based algorithm is used to automatically discover the chemical reaction network responsible for the complexity of mass spectra, which is then applied to match experimental mass spectra with computationally predicted molecular graphs. This methodology can be easily applied to study other oils and their mixtures.