Identification of small molecules using accurate mass MS/MS search

Abstract

Tandem mass spectral library search (MS/MS) is the fastest way to correctly annotate MS/MS spectra from screening small molecules in fields such as environmental analysis, drug screening, lipid analysis, and metabolomics. The confidence in MS/MS-based annotation of chemical structures is impacted by instrumental settings and requirements, data acquisition modes including data-dependent and data-independent methods, library scoring algorithms, as well as post-curation steps. We critically discuss parameters that influence search results, such as mass accuracy, precursor ion isolation width, intensity thresholds, centroiding algorithms, and acquisition speed. A range of publicly and commercially available MS/MS databases such as NIST, MassBank, MoNA, LipidBlast, Wiley MSforID, and METLIN are surveyed. In addition, software tools including NIST MS Search, MS-DIAL, Mass Frontier, SmileMS, Mass++, and XCMS² to perform fast MS/MS search are discussed. MS/MS scoring algorithms and challenges during compound annotation are reviewed. Advanced methods such as the in silico generation of tandem mass spectra using quantum chemistry and machine learning methods are covered. Community efforts for curation and sharing of tandem mass spectra that will allow for faster distribution of scientific discoveries are discussed.

Keywords: compound identification; high-resolution mass spectrometry; library search; tandem mass spectrometry.

FIGURE 1

(A) During data-dependent MS/MS spectra acquisition, the instrument selects a highly abundant MS¹ peak and discards all other peaks outside the selected precursor isolation window. The ions are fragmented during collision-induced dissociation (CID) or higher energy collisional dissociation (HCD) processes. The MS/MS contains information about the precursor ion. (B) During all-ion fragmentation or SWATH mode the instrument fragments all peaks indiscriminately of peak height. The spectra are information-rich collections but lack the precursor information. In order to perform MS/MS database search deconvolution software such as MS-DIAL has to be used to reconstruct the correct precursor ion

FIGURE 2

(A) MS/MS database creation: a MS¹ ion (precursor) is picked from an LC-MS/MS run and undergoes fragmentation in the tandem mass spectrometer under different collision energies to cover a broad range of characteristic fragments (product ions). (B) MS/MS search: the precursor filter (from 0.1 to 0.001 Da) removes most of the candidates outside a mass accuracy search window. The similarity algorithm ranks the remaining spectra against all database spectra and creates a similarity score

FIGURE 3

Modern mass spectrometers can record multiple CID voltages for each scan event. Therefore modern MS/MS libraries are now created with multiple distinct CID voltages, such as 10, 20, and 40 eV to increase compound identification probabilities. An example of matching an experimental MS/MS spectrum of catechin acquired in negative ionization mode ESI(−). It is matched against the 10, 20, and 40 eV reference spectra. If the library would only contain 40 eV spectra or single voltages a very low hit score would be obtained

FIGURE 4

GC-EI-MS and GC-EI-MS/MS of malic acid (3-TMS, trimethylsilyl) with precursor ion m/z 350.142. Different ionization voltages (5 and 30 eV) for product ion spectra can create specific fragments. Such information is important for neutral loss and substructure analysis. Current GC-MS/MS databases currently contain only a small number of compounds in comparison to LC-MS/MS databases