Dissociation induced
by the accumulation of internal energy via
collisions of ions with neutral molecules is one of the most important
fragmentation techniques in mass spectrometry (MS), and the identification
of small singly charged molecules is based mainly on the consideration
of the fragmentation spectrum. Many research studies have been dedicated
to the creation of databases of experimentally measured tandem mass
spectrometry (MS/MS) spectra (such as MzCloud, Metlin, etc.) and developing
software for predicting MS/MS fragments in silico from the molecular
structure (such as MetFrag, CFM-ID, CSI:FingerID, etc.). However,
the fragmentation mechanisms and pathways are still not fully understood.
One of the limiting obstacles is that protomers (positive ions protonated
at different sites) produce different fragmentation spectra, and these
spectra overlap in the case of the presence of different protomers.
Here, we are proposing to use a combination of two powerful approaches:
computing fragmentation trees that carry information of all consecutive
fragmentations and consideration of the MS/MS data of isotopically
labeled compounds. We have created PyFragMS—a web tool consisting
of a database of annotated MS/MS spectra of isotopically labeled molecules
(after H/D and/or
16
O/
18
O exchange) and a collection
of instruments for computing fragmentation trees for an arbitrary
molecule. Using PyFragMS, we investigated how the site of protonation
influences the fragmentation pathway for small molecules. Also, PyFragMS
offers capabilities for performing database search when MS/MS data
of the isotopically labeled compounds are taken into account.