Combining fragment ion and neutral loss matching during mass spectral library searching: A new general-purpose algorithm applicable to illicit drug identification

Published

November 20, 2017

Author(s)

Arun S. Moorthy, William E. Wallace, Anthony J. Kearsley, Dmitrii V. Tchekhovskoi, Stephen E. Stein

Abstract

A mass spectral library search algorithm that identifies compounds that differ from library compounds by a single ‘inert’ structural component is described. This algorithm, the Hybrid Similarity Search, generates a similarity score based on matching both fragment ions and neutral losses. It employs the parameter ΔMass, defined as the mass difference between query and library compounds, to shift neutral loss peaks in the library spectrum to match corresponding neutral loss peaks in the query spectrum. When the spectra being compared differ by a single structural feature, these matching neutral loss peaks should contain that structural feature. This method, in effect, extends the scope of the library to include spectra of ‘nearest-neighbor’ compounds that differ from library compounds by a single chemical moiety. Additionally, determination of the structural origin of the shifted peaks can aid in the determination of elucidation of the chemical structure and fragmentation mechanism of the query compound. A variety of examples are presented, including the identification of designer drugs and chemical derivatives not present in the library.

Citation

Analytical Chemistry

Volume

89

Issue

24

Pub Type

Journals

Download Paper

https://doi.org/10.1021/acs.analchem.7b03320

Keywords

Electron Ionization Mass Spectrometry, Gas Chromatography Mass Spectrometry, Fentanyl, Hybrid Search

Citation

Moorthy, A. , Wallace, W. , Kearsley, A. , Tchekhovskoi, D. and Stein, S. (2017), Combining fragment ion and neutral loss matching during mass spectral library searching: A new general-purpose algorithm applicable to illicit drug identification, Analytical Chemistry, [online], https://doi.org/10.1021/acs.analchem.7b03320 (Accessed November 21, 2024)