Rapid Metabolite Identification using MetabolitePilot™
Software and TripleTOF™ 5600 System
Easily Find, Identify and Confirm Metabolites in Accurate Mass DataCarmai Seto, Tanya Gamble and Hesham Ghobarah
AB SCIEX, Concord, Ontario, Canada
The ability to find, identify and confirm metabolites as quickly as
possible is critical at multiple stages of drug discovery anddevelopment. Advancements in instrumentation have enabled
the generation of very information rich raw data. New software toautomate parts of the metabolite identification workflow holds thepotential for considerable benefits to drug metabolism
researchers. For example, accurate mass instruments such as
Time of Flight (TOF) have the capability to provide both
qualitative and quantitative information in a single analysis.
However, the data analysis can be quite complicated and verytime consuming if performed manually, especially if analog data
was acquired along with MS and MS/MS data. Software canautomate the process of finding, identifying and confirming
metabolites in accurate mass data. In this technical note, we will
describe how MetabolitePilot™ software and the AB SCIEXTripleTOF™ 5600 system can make the process of identifying
and confirming metabolites more efficient than ever before.

MetabolitePilot™ Software: Automated
Identification and Confirmation of
Metabolites
MetabolitePilot software employs multiple powerful dataprocessing algorithms to perform both non-targeted and targeted
processing in parallel. In addition to generic peak finding,multiple mass defect filtering, isotope pattern matching, andfinding metabolites based on common product ions or neutral
losses can all be used simultaneously to efficiently find andidentify metabolites. To harness the power of these algorithms,
the software automatically calculates the most appropriatecompound-specific processing parameters for a givencompound. MetabolitePilot software automatically predicts
potential cleavage metabolites based on the structure of theparent compound. It also automatically calculates mass defectfilters for Phase I metabolites, including the parent drug, as wellas Phase II and potential cleavage metabolites (Figure 1).
MetabolitePilot software makes the work of identifying andconfirming metabolites more efficient with an easy to useintegrated workspace that displays all relevant information. Thesoftware displays the analog, MS and MS/MS data associatedFigure 1. Multiple mass defect filtering setup in the processing
parameters. MetabolitePilot™ software automatically calculates themass defect filters for multiple metabolite classes using the parentstructure.

with each metabolite in a single view (Figure 2). A confirmation
score is also provided to help determine if a peak is a metabolite(Figure 3). To aid with confirmation of metabolites, the software
enables faster comparison of metabolite and parent product ion
spectra with a simple and effective display. The product ion
spectrum of the parent drug is automatically compared with eachmetabolite and the results of the comparison are displayed in theMS/MS panel of the results workspace.

Key Features of MetabolitePilot Software for
Metabolite Identification• Intuitively supports the TripleTOF™ 5600 LC/MS/MS system’shigh resolution accurate mass metabolite identification
1,2workflows• Metabolites are detected through a combination of powerfulpeak finding algorithms• Automatic structure driven processing parameters• Integrated MS/MS fragment interpretation and structure editor• Multiple sample correlation function for time course studies
and inter-species comparison of metabolites• Simple, clear data reviewing enabled by the Results
Workspacep1

coupled to TripleTOF™ 5600 system. All analyses wereperformed using an Imtakt Cadenza CD-C18 (2 x 50 mm) 3µ,ODS column that was held at 40°C. Solvent A contained waterwith 0.1% formic acid and solvent B contained acetonitrile with
0l.1% formic acid and the flow rate was set at 600 µL/min. The
gradient is summarized in Table 1.
Table 1. Summary of LC gradient used to analyze the incubations
Time(minutes)

Composition ofGradient (%B)

0.0

10

0.5

100.75

205.5

40

6.560

6.890

6.990

7.0

10Figure 2. Results workspace of MetabolitePilot™ software All data isdisplayed in a single workspace for efficient data review.

Analog Data: The Shimadzu UV dual wavelength detector
was set to 302 nm.

Mass Spectrometry: The TripleTOF 5600 system method
used for data acquisition consisted of a TOF MS survey scanfollowed by two IDA TOF MS/MS scans. Mass Defect triggered
IDA with Dynamic Background Subtraction™ algorithm was used
to collect the MS/MS data. External mass calibration wasperformed automatically using a calibrant delivery system.
Figure 3. Detailed information about a confirmation score. Eachpotential metabolite is given a confirmation score to help determine if thepeak is likely to be a metabolite.

Experimental Conditions
Sample Preparation: Bromocriptine was incubated in rat
liver microsomes under oxidative conditions at 37° C for 1 hour,along with a control. The reactions were quenched by theaddition of an equal volume of acetonitrile to the microsomalsolutions then centrifuged at 14,000 rpm for 5 minutes.

Chromatography: The incubations were analyzed using a
Shimadzu Prominence UFLC-XR LC system with UV detector

Results
MetabolitePilot software was used to process the data acquired
for the incubation. The software correlated the MS and UV data
together in the results workspace, with the potential metabolites
table indicating if a MS peak has a corresponding analog peak(Figure 2).
Figure 4 illustrates some of the structures proposed for some of
the metabolites that were identified by the software. Theidentified peaks were confirmed as metabolites using theconfirmation score provided by the software, the exact mass
product ion spectra and the UV data.

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Figure 4. Proposed structures for some bromocriptine metabolites
identified in a rat microsomal incubation.

Along with the interpreted spectrum of bromocriptine, structural
elucidation of the metabolites was quickly achieved using theexcellent mass accuracies achieved by the TripleTOF™ 5600
system. When comparing product ion spectra, common productions between metabolites and parent drug (bromocriptine)
indicate where metabolism has not occurred, while common
neutral losses indicate where metabolism has occurred. The
comparison process is made more efficient by the automatedproduct ion comparisons and fully integrated automatic MS/MS
fragment interpretation and assignment performed by
MetabolitePilot™ software. Editing and storage of metabolite
structures can be performed directly within the software.
Interpretation and inter-sample correlation capabilities arecovered in detail in reference (3).
An example of the product ion spectra used for structural
elucidation in this study is shown in Figure 5; the spectrum for anoxidation metabolite (M6), a desaturation metabolite (M23) andbromocriptine are shown. Due to the presence of the common
product ion m/z 426.0809, the sites of metabolites weredetermined not to be localized on the substructure represented
by m/z 426.0809. There is no ambiguity in the elemental
composition of the product ion due to the mass accuracies
achieved by the TripleTOF 5600 system for this experiment.
Figure 5. Product ion spectra of two metabolites and bromocriptine.
Automated MS/MS comparisons and excellent mass accuracies allowed
for rapid structural elucidation of metabolites.

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Conclusions

References

The TripleTOF™ 5600 system with MetabolitePilot™ software
effectively address the data analysis bottleneck in metabolite
identification, from peak detection to structural elucidation.

1.

“Breakthrough Productivity for ADME Studies Using the AB
SCIEX TripleTOF™ 5600 System”, AB SCIEX TechnicalNote, Publication 0480110-01• Efficiently find metabolites using powerful multiple peakfinding strategies applied in parallel, such as non-targeted
generic peak finding and mass defect filtering.

2.

“Simultaneous Pharmacokinetic Profiling and AutomatedMetabolite Identification using the AB SCIEX TripleTOF™
5600 System and MetabolitePilot™ Software”, AB SCIEXTechnical Note, Publication 1270210-01

3.

“Solving Bottlenecks in Metabolite ID Data Analysis With
MetabolitePilot™ Software”, AB SCIEX Technical Note,
Publication 3610211-01

4.

To download a trial version of MetabolitePilot™ software,please visit:
http://www.absciex.com/Products/Software/MetabolitePilotSoftware• Automatic generation of structure based processing
parameters such as multiple mass defect ranges and potential
cleavage metabolites.
• Efficient processing of multiple sample sets together in theBatch Workspace.
• Rapidly perform structural elucidation using integrated MS/MS
fragment interpretation and assignment, all in a single user
friendly workspace.
• Automatic multiple sample correlation of UV, MS, and MS/MS
data, and plotting of response across samples for faster andeasier evaluation of time course studies and inter-species
comparison.

For Research Use Only. Not for use in diagnostic procedures.
© 2011 AB SCIEX. The trademarks mentioned herein are the property of AB Sciex Pte. Ltd. or their respective owners. AB SCIEX™ is being used under license.
Publication number: 2490211-02

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