Generative Algorithm for Molecular Graphs Uncovers Products of Oil Oxidation

• Published in: Journal of chemical information and modeling Vol. 61; no. 3; pp. 1457 - 1469
• Main Authors: Orlova, Yuliia, Gambardella, Alessa A, Kryven, Ivan, Keune, Katrien, Iedema, Piet D
• Format: Journal Article
• Language: English
• Published: United States American Chemical Society 22.03.2021
• Subjects: Algorithms; Autoxidation; Bioinformatics; Chemical reactions; Complex systems; Complexity; Drying oils; Graph theory; Graphs; Ions; Mass spectra; Mass spectrometry; Mass spectroscopy; Molecular structure; Oils; Oxidation; Oxidation-Reduction; Scientific imaging; Spectrometry, Mass, Electrospray Ionization; Triglycerides
• ISSN: 1549-9596; 1549-960X; 1549-960X
• DOI: 10.1021/acs.jcim.0c01163

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.