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Tutorials : Feb 15, 2009 ( )
Tools That Facilitate Metabolite Identification
Mass Spec Technology Drives Drug Metabolism Studies Forward
Information is power and never more so than in the world of drug development. For a pharmaceutical company, having detailed knowledge of how a drug candidate is metabolized as early as possible in the drug development process is crucial. It can save time, precious resources, and maximize return-on-investment. The final selection of a successful drug candidate relies enormously on the metabolism studies that are performed in vitro and in vivo.
Mass spectrometry is a key analytical tool used for metabolism studies because it can identify the metabolites and the sites at which metabolism occurs. Liquid chromatography coupled with mass spectrometry (LC-MS/MS) has become the technique of choice for drug metabolite identification because of its sensitivity and ability to analyze complex mixtures. But while analytical sensitivity has improved over the past decade, detecting and identifying metabolites in the presence of complex biological matrices remains a challenge.
Recent advances in both mass spectrometry hardware and software have helped in this ongoing challenge. Coupling a Thermo Scientific Orbitrap mass analyzer (www. thermo.com) to a linear ion trap mass spectrometer, for example, simplifies metabolite identification, making it faster, more sensitive, more precise (with resolution higher than 100K and mass accuracies better than three ppm) and capable of revealing rich structural information.
With high-resolution and accurate mass data, researchers can resolve and identify metabolite peaks from background matrix ions. New data-processing techniques, such as mass defect filtering, can be used to remove the vast majority of matrix-related background ions and reduce the number of false-positives, providing a more confident result.
This tutorial describes how the combination of innovative mass spectrometry with mass defect filtering software leads to fast and accurate metabolite identification.
High-resolution mass spectrometry enables post-acquisition data-refinement techniques that are otherwise not possible with nominal-resolution instruments. One of them is mass defect filtering (MDF), which is remarkably successful in improving the signal-to-noise ratio by cleaning up metabolite spectra and filtering out the vast majority of background ions.
Mass defect refers to the difference between the exact mass of an element (or a compound) and its closest integer value (Table). The mass defect of metabolites usually lies within a relatively narrow range. Based on the molecular weight of the parent drug, researchers can estimate the range of molecular weight and the range of mass defect in which these metabolites will fall. An MDF is then used to exclude all ions that fall outside the expected range.
This data-reduction technique allows users to focus solely on the analysis of species that are potential drug metabolite candidates. It is also a powerful and sophisticated way of using high-resolution mass data to obtain a smaller, more refined data set for review. The method can also be extended to include multiple mass defect filters (MMDFs), in which several filters are used to identify metabolites of interest over a wide range of mass defects.
Metabolite identification was performed by applying MMDFs to data collected with an LTQ Orbitrap XL™ hybrid mass spectrometer from Thermo Fisher Scientific. The mass spectrometer features a collision cell in which fragmentation is performed using higher-energy collisional dissociation (HCD; Figure 1), which provides complementary fragmentation pathways in addition to the collision-induced dissociation available in the linear ion trap.
Ions are accelerated as they leave the C-trap (Figure 1) and then fragmented in a nitrogen-filled HCD collision cell. The resulting fragments are returned to the C-trap and then detected in the instrument’s mass analyzer. This technique produces rich triple-quadrupole-like fragmentation patterns, including fragments in the low m/z range that are useful for elucidating the structure of metabolites.
Rat hepatocyte incubation samples of Irinotecan—a drug that is approved for use in the treatment of colon and rectum cancer—were analyzed using an LTQ Orbitrap XL with HCD functionality. Both collision-induced dissociation (CID) and high-energy collision-induced dissociation (HCD) mass spectra were collected for the potential metabolites and MMDFs were then used to process the raw data.
Incubation was carried out using hepatocytes pooled from one male and one female rat, with a cell density of 0.5 million/mL and 10 µM of Irinotecan in the final 1 mL incubation solution. The solution was shaken overnight and quenched using dry ice, after which 200 µL of chilled acetonitrile was added and the solution was vortexed and centrifuged. From the 1 mL of supernatant, 10 µL was directly injected for each LC-MS/MS run.
Using MMDF in combination with HCD and CID MS/MS (Figure 2), 13 Irinotecan metabolites were identified from the incubation samples with an accuracy of greater than three ppm. All 13 metabolites were found with peak areas less than 1% of that of the parent and are well buried in the original chromatogram (Figure 3A).
The most abundant metabolite peaks become visible after applying a single MDF (Figure 3B), however, at this stage peaks from background matrix ions that are unrelated to the metabolite are still prominent. This is due to the fact that in order to use only one MDF to capture all of the metabolites, a relatively wide mass defect range has to be used. As such, a portion of the background ions remains after a single filter.
Figure 4 further illustrates how the full MS spectrum changed after mass defect filtering. The peak at 603.2805 m/z is a hydroxylation metabolite (M3) that elutes at 8.45 minutes. The original full scan MS is dominated by background ions and the M3 peak has less than 15% relative abundance (Figure 3A). After a single MDF was applied, the M3 peak becomes the base peak; however, there are still a lot of background peaks remaining in the spectrum (Figure 3B). After MMDFs were applied, only the M3 peak and trace of the parent remain in the spectrum while almost all the background ions are gone (Figure 4C).
The combination of HCD and CID provides fragmentation information. MMDF offers superior background discrimination as compared to a single filter and enables metabolites with peak areas less than 1% of that of the parent drug to be identified.
Mass spectrometry has undergone major advances in recent years and is reshaping the landscape in which drug companies perform their metabolite identification studies. Pharmaceutical organizations have come to expect instruments that require minimal user intervention, offer high-throughput analysis and provide high-quality data. With the bottleneck in the process shifting to data processing, data-reduction techniques must continue to evolve to meet this challenge.
Yingying Huang, Ph.D. (firstname.lastname@example.org), is strategic marketing specialist at Thermo Fisher Scientific. Web: www.thermo.com.
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