Infrared ion spectroscopy (IRIS) continues to see increasing
use
as an analytical tool for small-molecule identification in conjunction
with mass spectrometry (MS). The IR spectrum of anm/zselected population of ions constitutes a unique
fingerprint that is specific to the molecular structure. However,
direct translation of an IR spectrum to a molecular structure remains
challenging, as reference libraries of IR spectra of molecular ions
largely do not exist. Quantum-chemically computed spectra can reliably
be used as reference, but the challenge of selecting the candidate
structures remains. Here, we introduce anin silicolibrary of vibrational spectra of common MS adducts of over 4500
compounds found in the human metabolome database. In total, the library
currently contains more than 75,000 spectra computed at the DFT level
that can be queried with an experimental IR spectrum. Moreover, we
introduce a database of 189 experimental IRIS spectra, which is employed
to validate the automated spectral matching routines. This demonstrates
that 75% of the metabolites in the experimental data set are correctly
identified, based solely on their exactm/zand IRIS spectrum. Additionally, we demonstrate an approach
for specifically identifying substructures by performing a search
withoutm/zconstraints to find
structural analogues. Such an unsupervised search paves the way toward
thede novoidentification of unknowns that are absent
in spectral libraries. We apply thein silicospectral
library to identify an unknown in a plasma sample as 3-hydroxyhexanoic
acid, highlighting the potential of the method.