Biopharmaceutical System with UNIFI Sc ientific Information … · 2018. 10. 10. · Amino acid...
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©2018 Waters Corporation MKT18144 TO DOWNLOAD A COPY OF THIS POSTER, VISIT WWW.WATERS.COM/POSTERS Biopharmaceutical System with UNIFI Scientific Information System for the Evaluation and Characterization of Peptide Catabolism Using Ion Mobility Enabled High Resolution Mass Spectrometry ٳKenji Hirose 1 , Thanai Paxton 1 , Jayne Kirk 2 , Francesco Lanucara 2 , Laetitia Denbigh 2 , Russell Mortishire-Smith 2 , and Mark Wrona 3 1 Nihon Waters K.K., Tokyo, Japan; 2 Waters Corporation, Wilmslow, UK; 3 Waters Corporation, Milford, MA, USA UNIFI WORKFLOW STEPS FOR PEPTIDE METABOLISM STUDIES Abstract In recent years, the number of biotherapeutic drugs approved has been higher than the number of small molecule compounds. The same need exists, however, to characterize and optimize the absorption, distribution, metabolism, and excretion (ADME) properties of biotherapeutics, and DMPK groups are looking to translate their knowledge of small molecule drug metabolism to the catabolism of biotherapeutics. The challenge is that there are few software tools available to characterize the clearance and metabolic fate of biotherapeutics. In this study salmon calcitonin (sCT), a 32 residue polypeptide and FDA approved treatment for osteoporosis in post menopausal women, was incubated with rat kidney homogenates over a time course and the resulting metabolites analyzed using ion mobility enabled high resolution mass spectrometry. Intelligent software tools were then used to accurately identify and characterize the primary sites of sCT catabolism and help predict metabolic routes. Table 1. Peptide metabolism workflow steps with descriptions of each view for data analysis Figure 2. UNIFI review window showing identification of the parent compound, sCT. The associated workflow step is also shown (inset). Figure 1. Peptide sequence for salmon calcitonin (sCT). Method conditions System: ACQUITYR UPLCR I-Class (FTN) Column: ACQUITY UPLC BEH C18 [ PP ȝP Run time: 8 minutes Vials: Waters Maximum Recovery Column temp.: 45 ഒ Sample temp.: 8 ഒ Injection vol.: 1 ȝL Flow rate: 0.4 mL/min Mobile phase A: Water + 0.1 % formic acid Mobile phase B: Acetonitrile + 0.1 % formic acid Gradient: Time %A %B Curve 0.0 95 5 - 5.0 50 50 6 6.0 50 50 6 6.1 0 100 6 6.5 95 5 6 8.0 95 5 6 HDMS E conditions MS system: VionR IMS ToF Ionization mode: ESI+ Source temp.: 120 ഒ Desolvation temp.: 450 ഒ Desolvation gas: 800 L/hr Reference mass: Leucine enkephalin [M+H]+ m/z 556.27658 Acquisition range: m/z 50–2000 Scan time: 0.2 sec Capillary voltage: 0.8 kV Cone voltage: 25 V Collision energy: Function 1: 6 eV Function 2: Ramped 20-45 eV UNIFI data management, workflow, and processing method Peptide mapping: UNIFI v1.8.2 EXPERIMENTAL Sample description Kidney homogenate and buffer were pre-incubated at 37 ഒ for 15 min prior to addition of salmon calcitonin (final substrate FRQFHQWUDWLRQ ȝ0 WR LQLWLDWH WKH UHDFWLRQ (DFK FRPSRXQG ZDV LQFXEDWHG IRU DQG PLQ 7KH UHDFWLon was stopped by addition of acetonitrile. Following protein precipitation, the sample supernatants were removed and submitted for analysis. Parent compound review step This step shows sequence information in the top panel (Component Summary), the fate of the parent peptide drug over time (left panel, Trend Plot) and the Fragmentation Viewer (right panel), which automatically assigns fragment ions, a critical step in pinpointing the cleavage sites (Figure 2). The first step within the workflow provides a clear and visual assessment of turnover of parent, which can be viewed over the time course along with confirmation of identification from the Fragmentation Viewer. Metabolites N- and C-termini review step Referencing the second step of the workflow step, those metabolites formed as a result of catabolism from the N- and C-termini are summarized, along with an annotated chromatogram and a component plot (Figure 3). Within the component summary information, the position of the cleavage site and extent of modification are shown. Figure 5. sCT metabolism scheme. The oxidation and deamidation products are highlighted as separate steps within the workflow (Figure 4). This allows for amino acid oxidation, and asparagine and glutamine deamination to be independently assessed. The peptide sequence, modifiers, mass error, response, and charge are shown within the Component Summary and allow the user to validate identification. These data were filtered on the ‘modifiers’ column with ‘amino acid oxidation’ or ‘deamid’ selected in order to sort the list on metabolism products in their respective workflow steps. Based on the results within the metabolites (N- and C-termini degradation), oxidation, and deamidation workflows, a schematic for the metabolism of sCT is shown in Figure 5. The primary catabolic events involved hydrolytic cleavage of peptide bonds. The most abundant cleavage products are depicted for each cleavage site. Amino acid deamidation and oxidation products are also identified as summarized in the previous workflow steps. Figure 3. Identification of the metabolites as a result of hydrolysis from the N- and C-terminus. The associated workflow step is also shown (inset). Figure 4. Amino acid oxidation and deamidation products are filtered on according to the ‘modifiers’ column. The associated workflow step is also shown (inset). Trend Plot review step To modulate clearance of the parent in subsequent compounds, we need to know the earliest metabolic event, which can be viewed using the Summary Plot as shown in Figure 6. Assessment of the results from the incubation of sCT suggests that this is cleavage of the bond between residues 18 and 19, Lys-Leu (1:H1c14+H+). Trend plotting enables the visualization of detected catabolites/peptides across a sample set compared to a single sample (and typically not the t=0 min or a starting condition sample). To utilize this tool effectively, a reference injection must be chosen, and should be the sample that contains all (or most) of the species of interest. If critical catabolites appear at a late time point, it may be appropriate to choose a later time point as the reference injection. Figure 6. Trend view showing turnover of the parent compound sCT and increase in the formation of metabolites across the time course. The workflow step is also shown (insert). Binary Comparison review step The Binary Comparison workflow step provides a visual inspection of the results, with a component plot showing the increased number of metabolites over the selected time point compared with those in the control, in the case of sCT, t = 0 min (Figure 7). sCT is rapidly metabolised with the intensity in the base peak chromatogram significantly decreased in the t = 5 min sample. The workflow steps shown have been designed so that the user can easily navigate through a peptide metabolism study. It is important to note, however, that this workflow can be modified and customized in order to suit the user. Figure 7. Binary comparison mode allows two injections to be compared and reflection plots for both the chromatogram and component plot to be displayed. Also shown is the workflow step associated with this view (inset). Setting up the Analysis Method for peptide metabolism studies For setting up an analysis method appropriate for peptide metabolism, the Peptide Mapping analysis method was selected (Figure 8a). Non-native chemical linkers and custom amino acids can be created in the Scientific Library. Here a .mol file, created within a chemical structure drawing package, can be uploaded and a 1 and 3 letter code assigned. For sCT, the C- terminal proline residue is amidated, thus to demonstrate addition of a custom amino acid to the Scientific Library proline was entered as an amidated synthetic amino acid and labelled X (Figure 8b). Figure 8. (a) For processing, the analysis method for Peptide Mapping is selected and (b) custom amino acids created within the Scientific Library. Depending on the peptide drug and experimental conditions, the modifications list to consider during processing can be adapted accordingly (Figure 9a). Searches can be enabled for any amino acid residue. To do this, a modifier was added to the Scientific Library, through the Amino Acid Modifications Editor, as shown in Figure 9b. These were also created for acetylation and C-terminal deamidation. Figure 9. (a) Within the analysis method, the amino acid modifiers can be selected. (b) It is also possible to add new modifiers within the Scientific Library appropriate for biotherapeutic metabolism. The application of peptide catabolism is not subjected to typical enzymatic digestion; however, the peptide mapping workflow requires that an enzyme be specified. An enzyme, labelled as a digest reagent within UNIFI, was created to mimic non-digestion. This specifies cleavage at a non-existing amino acid within the peptide sequence. The N- and C-termini hydrolysis products were then generated in silico by enabling the semi-digest option within the analysis method. This is shown within Figure 10 for (a) the creation of a non-natural amino acid, (b) creation of a digest reagent within the editor of the Scientific Library and (c) selection of the reagent and semi-digest option within the analysis method. Under the protein digest tab, within the analysis method, there is also the possibility to use the non-specific digest option. This can be required when double and triple cleavages are expected, however, this will increase the number of false positives within the dataset and increase processing. Figure 10. Creating non-specific cleavages appropriate for peptide hydrolysis: (a) custom amino acid entry in the Scientific Library (b) digest condition entered as a reagent and (c) digest settings applied to the analysis method along with enabling the semi digest option. Although not necessary for sCT, the software is capable of identifying scrambling of disulphide bonds wherever two or more cysteine residues are present. In addition, for unexpected metabolite identification, the use of de novo searching is possible. The tool will annotate the high energy data containing fragment ion information, and requires no prior knowledge of the amino acid sequence or digestion enzyme. As the catabolism of biotherapeutics is a relatively new field of research, instances could arise where their metabolism may generate unexpected or unpredicted metabolites requiring use of these investigative tools. We have successfully demonstrated how the Waters Biopharmaceutical Peptide Mapping solution enables the acquisition and processing of results from the calcitonin incubation with rat kidney homogenates. Using the dedicated workflow, primary sites of catabolism for calcitonin were successfully identified and characterized. We have described both the workflow and the set up of the analysis method, including how to customize the cleavage rules appropriate for peptide metabolism. An in vitro incubation of calcitonin revealed a number of metabolites, and identified the main cleavage site as 18–19 (Lys-Leu). The use of UNIFI workflow steps, appropriate for peptide metabolism, allowed data analysis to be performed easily and efficiently. In addition, non-native chemical linkers and custom amino acids could be readily stored and retrieved from the UNIFI Scientific Library. The relationships between a peptide and its metabolites were easily visualized using the workflow steps and data evaluation tools present within UNIFI. The workflow has been configured so that results can be viewed in a logical and stepwise process. Here, the clearance and metabolic fate of sCT using a generic, data- independent, acquisition method (HDMS E ) will be discussed. The peptide catabolism workflow tracks the disappearance of the parent drug and identification of downstream products. Table 1 outlines the workflow steps and what is incorporated into each of the different views. References 1. T Katsila, A P Siskos, and C Tamvakopoulos. Peptide and protein drugs: The study of their metabolism and catabolism by mass spectrometry. Mass Spectrometry Reviews. 31: 110–133: 2012. 2. M Hall. Biotransformation and in vivo stability of protein biotherapeutics: Impact on candidate selection and pharmacokinetic profiling. 42: 1873–1880: 2014. 3. S Liao, ZQ Zhang, JX Ruan, JK Qi, and KL Liu. Degradation of salmon calcitonin in rat kidney and liverhomogenates. Pharmazie. 63: 743–747: 2008. CONCLUSION
Transcript of Biopharmaceutical System with UNIFI Sc ientific Information … · 2018. 10. 10. · Amino acid...
©2018 Waters Corporation MKT18144 TO DOWNLOAD A COPY OF THIS POSTER, VISIT WWW.WATERS.COM/POSTERS
Biopharmaceutical System with UNIFI Scientific Information System for the Evaluation and Characterization of Peptide Catabolism Using Ion Mobility Enabled High Resolution Mass Spectrometry
Kenji Hirose1 , Thanai Paxton1, Jayne Kirk2, Francesco Lanucara2, Laetitia Denbigh2, Russell Mortishire-Smith2, and Mark Wrona3
1Nihon Waters K.K., Tokyo, Japan; 2 Waters Corporation, Wilmslow, UK; 3 Waters Corporation, Milford, MA, USA
UNIFI WORKFLOW STEPS FOR PEPTIDE METABOLISM STUDIES
Abstract
In recent years, the number of biotherapeutic drugs approved has been higher than the number of small molecule compounds. Thesame need exists, however, to characterize and optimize the absorption, distribution, metabolism, and excretion (ADME) propertiesof biotherapeutics, and DMPK groups are looking to translate their knowledge of small molecule drug metabolism to the catabolismof biotherapeutics. The challenge is that there are few software tools available to characterize the clearance and metabolic fate of biotherapeutics. In this study salmon calcitonin (sCT), a 32 residue polypeptide and FDA approved treatment for osteoporosis in post menopausalwomen, was incubated with rat kidney homogenates over a time course and the resulting metabolites analyzed using ion mobilityenabled high resolution mass spectrometry. Intelligent software tools were then used to accurately identify and characterize theprimary sites of sCT catabolism and help predict metabolic routes.
Table 1. Peptide metabolism workflow steps with descriptions of each view for data analysis
Figure 2. UNIFI review window showing identification of the parent compound, sCT. The associated workflow step is also shown (inset).
Figure 1. Peptide sequence for salmon calcitonin (sCT).
Method conditionsSystem: ACQUITYR UPLCR I-Class (FTN)Column: ACQUITY UPLC BEH C18 Run time: 8 minutesVials: Waters Maximum RecoveryColumn temp.: 45 Sample temp.: 8 Injection vol.: 1 LFlow rate: 0.4 mL/minMobile phase A: Water + 0.1 % formic acidMobile phase B: Acetonitrile + 0.1 % formic acidGradient:Time %A %B Curve0.0 95 5 -5.0 50 50 66.0 50 50 66.1 0 100 66.5 95 5 68.0 95 5 6
HDMSE conditionsMS system: VionR IMS ToFIonization mode: ESI+Source temp.: 120 Desolvation temp.: 450 Desolvation gas: 800 L/hrReference mass: Leucine enkephalin [M+H]+ m/z 556.27658Acquisition range: m/z 50–2000Scan time: 0.2 secCapillary voltage: 0.8 kVCone voltage: 25 VCollision energy: Function 1: 6 eVFunction 2: Ramped 20-45 eV
UNIFI data management, workflow, and processing methodPeptide mapping: UNIFI v1.8.2
EXPERIMENTALSample descriptionKidney homogenate and buffer were pre-incubated at 37 for 15 min prior to addition of salmon calcitonin (final substrate
onwas stopped by addition of acetonitrile. Following protein precipitation, the sample supernatants were removed and submitted foranalysis.
Parent compound review stepThis step shows sequence information in the top panel (Component Summary), the fate of the parent peptide drug over time (left panel, Trend Plot) and the Fragmentation Viewer (right panel), which automatically assigns fragment ions, a critical step in pinpointing the cleavage sites (Figure 2). The first step within the workflow provides a clear and visual assessment of turnover of parent, which can be viewed over the time course along with confirmation of identification from the Fragmentation Viewer.
Metabolites N- and C-termini review stepReferencing the second step of the workflow step, those metabolites formed as a resultof catabolism from the N- and C-termini are summarized, along with an annotatedchromatogram and a component plot (Figure 3). Within the component summary information,the position of the cleavage site and extent of modification are shown.
Figure 5. sCT metabolism scheme.
The oxidation and deamidation products are highlighted as separate steps within the workflow(Figure 4). This allows for amino acid oxidation, and asparagine and glutamine deamination to beindependently assessed. The peptide sequence, modifiers, mass error, response, and charge areshown within the Component Summary and allow the user to validate identification. These data were filtered on the ‘modifiers’ column with ‘amino acid oxidation’ or ‘deamid’ selected in order to sort the list on metabolism products in their respective workflow steps.
Based on the results within the metabolites (N-and C-termini degradation), oxidation, and deamidation workflows, a schematic for the metabolism of sCT is shown in Figure 5. The primary catabolic events involved hydrolytic cleavage of peptide bonds. The most abundant cleavage products are depicted for each cleavage site. Amino acid deamidation and oxidation products are also identified as summarized in the previous workflow steps.
Figure 3. Identification of the metabolites as a result of hydrolysis from the N- and C-terminus. The associated workflow step is also shown (inset).
Figure 4. Amino acid oxidation and deamidation products are filtered on according to the ‘modifiers’ column. The associated workflow step is also shown (inset).
Trend Plot review stepTo modulate clearance of the parent in subsequent compounds, we need to know the earliest metabolic event, which can be viewed using the Summary Plot as shown in Figure 6.Assessment of the results from the incubation of sCT suggests that this is cleavage of the bond between residues 18 and 19, Lys-Leu (1:H1c14+H+).Trend plotting enables the visualization of detected catabolites/peptides across a sample set compared to a single sample (and typically not the t=0 min or a starting condition sample). To utilize this tool effectively, a reference injection must be chosen, and should be the sample that contains all (or most) of the species of interest. If critical catabolites appear at a late time point, it may be appropriate to choose a later time point as the reference injection.
Figure 6. Trend view showing turnover of the parent compound sCT and increase in the formation of metabolites across the time course. The workflow step is also shown (insert).
Binary Comparison review stepThe Binary Comparison workflow step provides a visual inspection of the results, with a component plot showing the increased number of metabolites over the selected time point compared with those in the control, in the case of sCT, t = 0 min (Figure 7). sCT is rapidly metabolised with the intensity in the base peak chromatogram significantly decreased in the t = 5 min sample.The workflow steps shown have been designed so that the user can easily navigate through a peptide metabolism study. It is important to note, however, that this workflow can be modified and customized in order to suit the user.
Figure 7. Binary comparison mode allows two injections to be compared and reflection plots for both the chromatogram and component plot to be displayed. Also shown is the workflow step associated with this view (inset).
Setting up the Analysis Method for peptide metabolism studiesFor setting up an analysis method appropriate for peptide metabolism, the Peptide Mapping analysis method was selected (Figure 8a). Non-native chemical linkers and custom amino acids can be created in the Scientific Library. Here a .mol file, created within a chemical structure drawing package, can be uploaded and a 1 and 3 letter code assigned. For sCT, the C-terminal proline residue is amidated, thus to demonstrate addition of a custom amino acid to the Scientific Library proline was entered as an amidated synthetic amino acid and labelled X (Figure 8b).
Figure 8. (a) For processing, the analysis method for Peptide Mapping is selected and (b) custom amino acids created within the Scientific Library.
Depending on the peptide drug and experimental conditions, the modifications list to considerduring processing can be adapted accordingly (Figure 9a). Searches can be enabled for any amino acid residue. To do this, a modifier was added to the Scientific Library, through the AminoAcid Modifications Editor, as shown in Figure 9b. These were also created for acetylation and C-terminal deamidation.
Figure 9. (a) Within the analysis method, the amino acid modifiers can be selected. (b) It is also possible to add new modifiers within the Scientific Library appropriate for biotherapeutic metabolism.
The application of peptide catabolism is not subjected to typical enzymatic digestion; however, the peptide mapping workflow requires that an enzyme be specified. An enzyme, labelled as a digest reagent within UNIFI, was created to mimic non-digestion. This specifies cleavage at a non-existing amino acid within the peptide sequence. The N- and C-termini hydrolysisproducts were then generated in silico by enabling the semi-digest option within the analysis method. This is shown within Figure 10 for (a) the creation of a non-natural amino acid, (b) creation of a digest reagent within the editor of the Scientific Library and (c) selection of the reagent and semi-digest option within the analysis method. Under the protein digest tab, within the analysismethod, there is also the possibility to use the non-specific digest option. This can be required when double and triple cleavages are expected, however, this will increase the number of false positives within the dataset and increase processing.
Figure 10. Creating non-specific cleavages appropriate for peptide hydrolysis: (a) custom amino acid entry in the Scientific Library (b) digest condition entered as a reagent and (c) digest settings applied to the analysis method along with enabling the semi digest option.
Although not necessary for sCT, the software is capable of identifying scrambling of disulphide bonds wherever two or more cysteine residues are present. In addition, for unexpected metabolite identification, the use of de novo searching is possible. The tool will annotate the high energy data containing fragment ion information, and requires no prior knowledge of the amino acidsequence or digestion enzyme. As the catabolism of biotherapeutics is a relatively new field of research, instances could arise where their metabolism may generate unexpected or unpredicted metabolites requiring use of these investigative tools.
We have successfully demonstrated how the Waters Biopharmaceutical Peptide Mapping solution enables the acquisition and processing of results from the calcitonin incubation with rat kidney homogenates. Using the dedicated workflow, primary sites ofcatabolism for calcitonin were successfully identified and characterized. We have described both the workflow and the set up of the analysis method, including how to customize the cleavage rules appropriate for peptide metabolism.An in vitro incubation of calcitonin revealed a number of metabolites, and identified the main cleavage site as 18–19 (Lys-Leu). The use of UNIFI workflow steps, appropriate for peptide metabolism, allowed data analysis to be performed easily and efficiently. In addition, non-native chemical linkers and custom amino acids could be readily stored and retrieved from the UNIFIScientific Library. The relationships between a peptide and its metabolites were easily visualized using the workflow steps anddata evaluation tools present within UNIFI.
The workflow has been configured so that results can be viewed in a logical and stepwise process. Here, the clearance and metabolic fate of sCT using a generic, data-independent, acquisition method (HDMSE) will be discussed. The peptide catabolism workflow tracks the disappearance of the parent drug and identification of downstream products. Table 1 outlines the workflow steps and what is incorporated into each of the different views.
References1. T Katsila, A P Siskos, and C Tamvakopoulos. Peptide and protein drugs: The study of their metabolism and catabolism by mass spectrometry. Mass Spectrometry Reviews. 31: 110–133: 2012.2. M Hall. Biotransformation and in vivo stability of protein biotherapeutics: Impact on candidate selection and pharmacokinetic profiling. 42: 1873–1880: 2014.3. S Liao, ZQ Zhang, JX Ruan, JK Qi, and KL Liu. Degradation of salmon calcitonin in rat kidney and liverhomogenates. Pharmazie. 63: 743–747: 2008.
CONCLUSION
