TY - JOUR
T1 - Generative Algorithm for Molecular Graphs Uncovers Products of Oil Oxidation
AU - Orlova, Yuliia
AU - Gambardella, Alessa A.
AU - Kryven, Ivan
AU - Keune, Katrien
AU - Iedema, Piet D.
N1 - Funding Information:
Y.O. gratefully acknowledges financial support for PREDAGIO project from The Netherlands Organisation for Scientific Research (NWO). Andrea Gargano is acknowledged for his constructive criticism on the manuscript. A.A.G. thanks AkzoNobel (The Netherlands) for funding; Rob Erdmann of the Rijksmuseum for support in Python; The Cultural Heritage Agency of the Netherlands (RCE) for providing the ESI-MS and the automatic muller (on permanent loan from Old Holland); and Art Ness Proaño Gaibor, Klaas Jan van den Berg, Federica Parlanti, and Fabiana Di Gianvincenzo of the RCE for assistance during experiments.
Publisher Copyright:
©
PY - 2021/3/22
Y1 - 2021/3/22
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85101841431&partnerID=8YFLogxK
U2 - 10.1021/acs.jcim.0c01163
DO - 10.1021/acs.jcim.0c01163
M3 - Article
C2 - 33615781
SN - 1549-9596
VL - 61
SP - 1457
EP - 1469
JO - Journal of Chemical Information and Modeling
JF - Journal of Chemical Information and Modeling
IS - 3
ER -