Analysis of Polycyclic Aromatic Hydrocarbons (PAH), Alkylated Derivatives, and Photo-degradation Products in Environmental and Food Samples using LC-FLD-MS/MS with QTRAP Technology
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Rapid Metabolite Identification using MetabolitePilot™ Software and TripleTOF™ 5600 System Easily Find, Identify and Confirm Metabolites in Accurate Mass Data Carmai 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 and development. Advancements in instrumentation have enabled the generation of very information rich raw data. New software to automate parts of the metabolite identification workflow holds the potential 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 very time consuming if performed manually, especially if analog data was acquired along with MS and MS/MS data. Software can automate 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 SCIEX TripleTOF™ 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 data processing algorithms to perform both non-targeted and targeted processing in parallel. In addition to generic peak finding, multiple mass defect filtering, isotope pattern matching, and finding metabolites based on common product ions or neutral losses can all be used simultaneously to efficiently find and identify metabolites. To harness the power of these algorithms, the software automatically calculates the most appropriate compound-specific processing parameters for a given compound. MetabolitePilot software automatically predicts potential cleavage metabolites based on the structure of the parent compound. It also automatically calculates mass defect filters for Phase I metabolites, including the parent drug, as well as Phase II and potential cleavage metabolites (Figure 1). MetabolitePilot software makes the work of identifying and confirming metabolites more efficient with an easy to use integrated workspace that displays all relevant information. The software displays the analog, MS and MS/MS data associated Figure 1. Multiple mass defect filtering setup in the processing parameters. MetabolitePilot™ software automatically calculates the mass defect filters for multiple metabolite classes using the parent structure. 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 each metabolite and the results of the comparison are displayed in the MS/MS panel of the results workspace. Key Features of MetabolitePilot Software for Metabolite Identification • Intuitively supports the TripleTOF™ 5600 LC/MS/MS system’s high resolution accurate mass metabolite identification 1,2 workflows • Metabolites are detected through a combination of powerful peak 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 Workspace p1

coupled to TripleTOF™ 5600 system. All analyses were performed using an Imtakt Cadenza CD-C18 (2 x 50 mm) 3µ, ODS column that was held at 40°C. Solvent A contained water with 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 of Gradient (%B) 0.0 10 0.5 10 0.75 20 5.5 40 6.5 60 6.8 90 6.9 90 7.0 10 Figure 2. Results workspace of MetabolitePilot™ software All data is displayed in a single workspace...

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 the excellent mass accuracies achieved by the TripleTOF™ 5600 system. When comparing product ion spectra, common product ions 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 automated product ion...

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 Technical Note, Publication 0480110-01 • Efficiently find metabolites using powerful multiple peak finding strategies applied in parallel, such as non-targeted generic peak finding and mass defect filtering. 2. “Simultaneous Pharmacokinetic Profiling and Automated Metabolite Identification...