EXPRESS: Identification of Unknown Peaks in Mass Spectra Based on the Characteristic Isotopic Pattern via the Hilbert-Noda Matrix.

Mass spectrometry (MS) is a powerful chemical analysis technique and one of the leading approaches that allows the identification and quantification of thousands of different components via a highly sensitive manner. However, assignment of unknown peaks in a mass spectrum to specific fragments is still a labour-intensive and costly task. Although various approaches and numerous software platforms have been developed, the automatic assignment of unknown peaks remains an unsolved problem. Based on the self-orthogonality of the Hilbert-Noda matrix extensively used in the field of 2D correlation spectroscopy, we develop a new method to generate an auxiliary spectrum to highlight peaks for the fragments containing stable isotopes via the characteristic pattern of the peaks for the isotopologues in the mass spectra. To address the problem of coincidental orthogonality, a modified approach using the second-order Hilbert-Noda matrix is proposed. Moreover, a statistical approach is adopted to suppress the appearance of false-positively highlighted peaks in the auxiliary spectra. The effectiveness of the approach has been showcased in the analysis of the mass spectra of 1,2-dibromoethane and chloroform. Unknown peaks of fragments containing different numbers of bromine or chlorine atoms can be successfully identified.