[Dedicated to Prof. T. Okada and Prof. T. Nishioka: data science in chemistry]The Contribution of Lipid Identification Tools Powered by In Silico MS/MS Spectral Libraries to Lipidomics

Abstract

Lipidomics is an important research field that studies lipid species in various experimental materials. The chromatographic separation and detection of lipid species are often carried out by liquid chromatography-mass spectrometry, but the identification and structural estimation of lipid species are not easy because the available authentic standard compounds and reference mass spectra are limited. This constitutes a major bottleneck in gaining insights into the roles of each of the lipid species involved in biological processes. In order to overcome this problem, artificial (in silico) tandem mass spectral libraries containing a broad range of lipid species have been constructed with the aid of the fragmentation and rearrangement rules of individual lipid classes. Here, we introduce lipid identification tools powered by in silico tandem mass spectral libraries for lipid research.