New Approach for Compound Identification Using Fine Isotopic Pattern SearchCaroline Ding,1 Tim Stratton,1 Hans Pfaff,2 Hans Grensemann,2 Christoph Henrich,2 1Thermo Fisher Scientific, San Jose, USA; 2Thermo Fisher Scientific, Bremen, Germany

2 New Approach for Compound Identification Using Fine Isotopic Pattern Search

New Approach for Compound Identification Using Fine Isotopic Pattern SearchNew Approach for Compound Identification Using Fine Isotopic Pattern SearchCaroline Ding1, Tim Stratton1, Hans Pfaff2, Hans Grensemann2, Christoph Henrich2, 1Thermo Fisher Scientific, San Jose, USA; 2Thermo Fisher Scientific, Bremen, GermanyThermo Fisher Scientific, San Jose, USA; Thermo Fisher Scientific, Bremen, Germany

OverviewPurpose: To demonstrate the use of very high resolution accurate mass full scan data with novel data processing software for fine isotopic pattern recognition to aid in small molecule identification

FIGURE 1. Compound Discoverer Workflow Editor. FIGURE 3. Isotope Search Interface – One-Sulfur Trace. FIGURE 5. Two-Sulfur Trace vs. Metabolites for Omeprazole Urine (0–3 hr).

300

350 Two 34S Trace

An initial search using a classic chlorine approach was performed looking for the abundant 37Cl signal in A2. Subsequent searches were refined first by requiring both the 37Cl and 2X 13C signal in A2 and then by requiring the 15N A1 as well as the 37Cl and 2X 13C in A2. The results of these searches are shown in Figure 8 with the known metabolites labeledmolecule identification.

Methods: Samples analyzed consisted of human urine samples acquired post-dose with omeprazole and human liver microsomal incubates of clozapine. Samples were analyzed by LC-MS using very high resolution on either a Thermo Scientific™ Q Exactive™ hybrid quadrupole-Orbitrap mass spectrometer or a Thermo Scientific™ 100

150

200

250

300 metabolites labeled.

FIGURE 8. Comparison of Clozapine Searches

Inte

nsity

[cou

nts]

(10^

6)

4.67146̂) Simple Cl Search0^

6)

Orbitrap Fusion™ Tribrid™ mass spectrometer. Data processing was performed using a novel processing platform, Thermo Scientific™ Compound Discoverer™ software, specifically for fine isotope pattern detection of related components to determine the ability to specifically detect related peaks with increasing isotope pattern options. Briefly, related peaks were found by detecting the 34S/13C patterns in different formats f l th 15N/37Cl/13C tt f l i

2 3 4 5 6 7 8RT [min]

0

50

4 550

7.1694.455 4.913

0

1

2

3

4

Inten

sity[

coun

ts](1

0̂ Simple Cl Search

Inte

nsity

[cou

nts]

(10

for omeprazole or the 15N/37Cl/13C patterns for clozapine.

Results: Related metabolites were detected using a fine isotopic pattern mechanism and the capabilities of increasing the detail of the pattern was determined by adding additional elemental requirements to normal searches. For example, the normal chlorine pattern search for clozapine samples was enhanced further by requiring the

4.550

60

80

100

sity

[cou

nts]

(10^

6)[c

ount

s] (1

0^6)

4.455 4.913

4.671

1

2

3

4

Inten

sity[

coun

ts](1

0̂6) 37Cl / 13C Search

Inte

nsity

[cou

nts]

(10^

6)

y gpresence of a 37Cl/ 2X13C pattern and further by requiring a full 15N/37Cl/ 2X13C pattern. These improvements reduced background noise and false positives from the simple chlorine search. In addition, the use of fine isotope pattern searches to determine one and two sulfur containing peaks was achieved for the omeprazole sample analysis showing the ability to find sulfate metabolites (two sulfurs) distinct from other

ResultsIsotope Pattern and Resolution Fine Isotopic Pattern Search on Omeprazole Data

Th i d b li d d i bi i f

4.909

3.677

3.853

3.923

4.856

2 3 4 5 6 7 8

RT [min]

0

20

40Inte

nsIn

tens

ity [ 0

4.455 4.913

4.671

1

2

3

4

ntens

it y[co

unts]

(10̂

6)

15N / 37Cl / 13C Search

Demethylation Oxidation

Parent

nsity

[cou

nts]

(10^

6)

metabolites (one sulfur).

IntroductionIsotopic patterns arising from natural isotopic abundances have been utilized in mass

The isotope pattern of any molecule is the result of its constituent elements and their number as well as the relative abundance of (typically heavier) isotopes. These isotopes have small mass differences that can be resolved to directly detect the elements’ presence (Figure 2). The ability to resolve this fine structure formed the basis of the searches performed.

The isotope traces were compared to metabolites detected using a combination of combinatorial metabolism search, MMDF, control comparison, and Fragment Ion Searching (FISh). Results for the one-sulfur search are shown in Figure 4 and for the two-sulfur search in Figure 5. In each case, there is very good overlap between the fine isotopic sulfur trace and the metabolites expected.

In both isotope searches, additional peaks were detected (blue arrows). These peaks could be the result of metabolism not detected by any of the other orthogonal approaches used or could be from endogenous sources which is also likely The simple chlorine pattern search, even though the pattern itself is very significant

Note: Metabolites include Sulfation, Oxidation + Sulfation, and Demethylation + Sulfation1 2 3 4 5 6 7 8 9 10

RT [min]

0

InIn

ten

spectrometric measurements for many years. As resolution capabilities have increased, instruments have been able to resolve the fine isotopic pattern, the separation of extremely close isobars in typically unresolved isotopic pattern members. This additional elemental information can be useful for definitive elemental composition determination in complex de novo applications. In addition, this fine isotope data can b d t f d d i t tt h th t t ibl ith

p

FIGURE 2. Omeprazole Isotope Pattern at Increasing Resolutions.

13C Resolution30 000

FIGURE 4. One-Sulfur Trace vs. Metabolites for Omeprazole Urine (0–3 hr).

approaches used or could be from endogenous sources, which is also likely considering the human urinary nature of the sample.

Using Fine Isotopes to Refine Abundant Isotope Searches

Some elements have abundant isotopes that have been used in the past as isotope

and the matrix not complex, had significant background. The addition of fine isotopic refinement using the 13C signal in the A2 isotope removed nearly all the background while the addition of 15N in A1 resulted in a search that detected only the three related peaks in the sample.

C l i1.2

One 34S Tracebe used to perform more advanced isotope pattern searches that are not possible with normal high resolution accurate mass data. Here we demonstrate the use of very high resolution to extract metabolites in biological samples.

Methods 70

80

90

100

ce

345.1142

40

60

80

100

ativ

e Ab

unda

nce

33S

15N 2H

30,000450,000A0

Some elements have abundant isotopes that have been used in the past as isotope trace tools (chlorine and bromine). Isotope labeling with stable label enrichment has been used in a similar fashion. Both of these approaches may benefit from the inclusion of fine isotope patterns. For this approach, we used clozapine and metabolites in human liver microsomes. Clozapine is shown in Figure 6 and the isotope pattern detail in Figure 7

ConclusionWe have demonstrated the utility of very high resolution to gain access to fine isotopic data and refine isotopic searches with this additional data. The use of fine isotopic data for analysis provides a number of benefits:

0.4

0.6

0.8

1.0

One S Trace

Inte

nsity

[cou

nts]

(10^

9)

Sample Preparation

Samples of omeprazole and metabolites in human urine were collected at 0–3 hr, 3–5 hr, and 5–7 hr post dosing. Sample preparation by SPE was followed by analysis by UHPLC-HRAM MS using a Q Exactive instrument coupled to a Thermo Scientific™ 30

40

50

60

Rel

ativ

e Ab

unda

nc

346.10 346.11 346.12 346.13m/z

0

20Rel

a isotope pattern detail in Figure 7.

FIGURE 6. Clozapine.

NH

Cl

Increased confidence in the elemental composition by direct observation of elements

Increased specificity in isotopic searches by utilizing multiple signals

Robustness against metabolism – searches can be performed on isotopic pattern

2 3 4 5 6 7 8RT [min]

0.0

0.2

y g pAccela™ UHPLC system. Accurate mass data was acquired using alternating full scan MS (70,000 resolution FWHM at m/z 200). Samples of clozapine and metabolites from an incubation with human liver microsomes (0.5 mg/mL protein, 1 uM substrate) were prepared at 0, 15, 30, and 45 minutes. UHPLC separation was achieved with a gradient of ACN and water with 0.1% on a Thermo Scientific™ Hypersil GOLD™

345.0 345.5 346.0 346.5 347.0m/z

0

10

20 346.1171

347.1135

A1

A2

N

N

N

members that are not enzymatically lost as can happen with oxidative dechlorination

Orthogonal detection mechanism to increase confidence that no related peak is missed

C f

4.926

0.6

0.8

1.0

unts

] (10

^9)

Metabolites

ount

s] (1

0^9)

aQ C-18 column (2×100mm, 1.9um).

Data Analysis

Data was analyzed using Compound Discoverer software. The program uses a customizable workflow construction approach (Figure 1) where processing steps, or

d bl d k i kfl A kfl d

Fine Isotopic Pattern Search on Omeprazole Data

Isotope searches in the omeprazole data were performed using two different approaches. Since the resolution of the data was high enough to expose the 34S to 2X

FIGURE 7. Clozapine Isotope Pattern and Fine Isotope Detail.37Cl13C

Can be applied to stable label patterns for more complex analysis

3.7473.4237.4503.7743.546

3.975

4.690

5.697 6.232

4.515

5.530

5.083

4.979

5.916

2 3 4 5 6 7 80.0

0.2

0.4Inte

nsity

[co

Inte

nsity

[co

nodes, are assembled to make a processing workflow. A workflow was constructed using multiple isotope pattern nodes to test different approaches. In addition, metabolite detection was also performed by classical means (combined metabolite search, MMDF, and fragment search) to confirm the results from isotope pattern searches.

13C pattern, two search filters were made. The first searched for compounds having one sulfur (ratio based on A0). This filter would find related metabolites regardless of biotransformation. The second filter was specific to two sulfur peaks and was designed to find sulfation products. The editor for setting the pattern is shown in Figure 3 with settings for a one-sulfur general search. A tolerance was included for b th d i t it f h i t

Note: Metabolites include all combinations of Phase I and Phase II metabolic events that do not add sulfur.

70

80

90

100343.1320

20

40

60

80

100

15N 2X13C20

40

60

80

1002 3 4 5 6 7 8

RT [min]

both mass accuracy and intensity for each isotope.

20

30

40

50

60

70

Rel

ativ

e Ab

unda

nce

345.1291

344.1354

00

All trademarks are the property of Thermo Fisher Scientific and its subsidiaries

343.0 343.5 344.0 344.5 345.0 345.5m/z

0

10

20 All trademarks are the property of Thermo Fisher Scientific and its subsidiaries.

This information is not intended to encourage use of these products in any manners that might infringe the intellectual property rights of others.

PO64100-EN 0614S

3Thermo Scientific Poster Note • PN64100-EN 1114S

New Approach for Compound Identification Using Fine Isotopic Pattern SearchNew Approach for Compound Identification Using Fine Isotopic Pattern SearchCaroline Ding1, Tim Stratton1, Hans Pfaff2, Hans Grensemann2, Christoph Henrich2, 1Thermo Fisher Scientific, San Jose, USA; 2Thermo Fisher Scientific, Bremen, GermanyThermo Fisher Scientific, San Jose, USA; Thermo Fisher Scientific, Bremen, Germany

OverviewPurpose: To demonstrate the use of very high resolution accurate mass full scan data with novel data processing software for fine isotopic pattern recognition to aid in small molecule identification

FIGURE 1. Compound Discoverer Workflow Editor. FIGURE 3. Isotope Search Interface – One-Sulfur Trace. FIGURE 5. Two-Sulfur Trace vs. Metabolites for Omeprazole Urine (0–3 hr).

300

350 Two 34S Trace

An initial search using a classic chlorine approach was performed looking for the abundant 37Cl signal in A2. Subsequent searches were refined first by requiring both the 37Cl and 2X 13C signal in A2 and then by requiring the 15N A1 as well as the 37Cl and 2X 13C in A2. The results of these searches are shown in Figure 8 with the known metabolites labeledmolecule identification.

Methods: Samples analyzed consisted of human urine samples acquired post-dose with omeprazole and human liver microsomal incubates of clozapine. Samples were analyzed by LC-MS using very high resolution on either a Thermo Scientific™ Q Exactive™ hybrid quadrupole-Orbitrap mass spectrometer or a Thermo Scientific™ 100

150

200

250

300 metabolites labeled.

FIGURE 8. Comparison of Clozapine Searches

Inte

nsity

[cou

nts]

(10^

6)

4.67146̂) Simple Cl Search0^

6)

Orbitrap Fusion™ Tribrid™ mass spectrometer. Data processing was performed using a novel processing platform, Thermo Scientific™ Compound Discoverer™ software, specifically for fine isotope pattern detection of related components to determine the ability to specifically detect related peaks with increasing isotope pattern options. Briefly, related peaks were found by detecting the 34S/13C patterns in different formats f l th 15N/37Cl/13C tt f l i

2 3 4 5 6 7 8RT [min]

0

50

4 550

7.1694.455 4.913

0

1

2

3

4

Inten

sity[

coun

ts](1

0̂ Simple Cl Search

Inte

nsity

[cou

nts]

(10

for omeprazole or the 15N/37Cl/13C patterns for clozapine.

Results: Related metabolites were detected using a fine isotopic pattern mechanism and the capabilities of increasing the detail of the pattern was determined by adding additional elemental requirements to normal searches. For example, the normal chlorine pattern search for clozapine samples was enhanced further by requiring the

4.550

60

80

100

sity

[cou

nts]

(10^

6)[c

ount

s] (1

0^6)

4.455 4.913

4.671

1

2

3

4

Inten

sity[

coun

ts](1

0̂6) 37Cl / 13C Search

Inte

nsity

[cou

nts]

(10^

6)

y gpresence of a 37Cl/ 2X13C pattern and further by requiring a full 15N/37Cl/ 2X13C pattern. These improvements reduced background noise and false positives from the simple chlorine search. In addition, the use of fine isotope pattern searches to determine one and two sulfur containing peaks was achieved for the omeprazole sample analysis showing the ability to find sulfate metabolites (two sulfurs) distinct from other

ResultsIsotope Pattern and Resolution Fine Isotopic Pattern Search on Omeprazole Data

Th i d b li d d i bi i f

4.909

3.677

3.853

3.923

4.856

2 3 4 5 6 7 8

RT [min]

0

20

40Inte

nsIn

tens

ity [ 0

4.455 4.913

4.671

1

2

3

4

ntens

it y[co

unts]

(10̂

6)

15N / 37Cl / 13C Search

Demethylation Oxidation

Parent

nsity

[cou

nts]

(10^

6)

metabolites (one sulfur).

IntroductionIsotopic patterns arising from natural isotopic abundances have been utilized in mass

The isotope pattern of any molecule is the result of its constituent elements and their number as well as the relative abundance of (typically heavier) isotopes. These isotopes have small mass differences that can be resolved to directly detect the elements’ presence (Figure 2). The ability to resolve this fine structure formed the basis of the searches performed.

The isotope traces were compared to metabolites detected using a combination of combinatorial metabolism search, MMDF, control comparison, and Fragment Ion Searching (FISh). Results for the one-sulfur search are shown in Figure 4 and for the two-sulfur search in Figure 5. In each case, there is very good overlap between the fine isotopic sulfur trace and the metabolites expected.

In both isotope searches, additional peaks were detected (blue arrows). These peaks could be the result of metabolism not detected by any of the other orthogonal approaches used or could be from endogenous sources which is also likely The simple chlorine pattern search, even though the pattern itself is very significant

Note: Metabolites include Sulfation, Oxidation + Sulfation, and Demethylation + Sulfation1 2 3 4 5 6 7 8 9 10

RT [min]

0

InIn

ten

spectrometric measurements for many years. As resolution capabilities have increased, instruments have been able to resolve the fine isotopic pattern, the separation of extremely close isobars in typically unresolved isotopic pattern members. This additional elemental information can be useful for definitive elemental composition determination in complex de novo applications. In addition, this fine isotope data can b d t f d d i t tt h th t t ibl ith

p

FIGURE 2. Omeprazole Isotope Pattern at Increasing Resolutions.

13C Resolution30 000

FIGURE 4. One-Sulfur Trace vs. Metabolites for Omeprazole Urine (0–3 hr).

approaches used or could be from endogenous sources, which is also likely considering the human urinary nature of the sample.

Using Fine Isotopes to Refine Abundant Isotope Searches

Some elements have abundant isotopes that have been used in the past as isotope

and the matrix not complex, had significant background. The addition of fine isotopic refinement using the 13C signal in the A2 isotope removed nearly all the background while the addition of 15N in A1 resulted in a search that detected only the three related peaks in the sample.

C l i1.2

One 34S Tracebe used to perform more advanced isotope pattern searches that are not possible with normal high resolution accurate mass data. Here we demonstrate the use of very high resolution to extract metabolites in biological samples.

Methods 70

80

90

100

ce

345.1142

40

60

80

100

ativ

e Ab

unda

nce

33S

15N 2H

30,000450,000A0

Some elements have abundant isotopes that have been used in the past as isotope trace tools (chlorine and bromine). Isotope labeling with stable label enrichment has been used in a similar fashion. Both of these approaches may benefit from the inclusion of fine isotope patterns. For this approach, we used clozapine and metabolites in human liver microsomes. Clozapine is shown in Figure 6 and the isotope pattern detail in Figure 7

ConclusionWe have demonstrated the utility of very high resolution to gain access to fine isotopic data and refine isotopic searches with this additional data. The use of fine isotopic data for analysis provides a number of benefits:

0.4

0.6

0.8

1.0

One S Trace

Inte

nsity

[cou

nts]

(10^

9)

Sample Preparation

Samples of omeprazole and metabolites in human urine were collected at 0–3 hr, 3–5 hr, and 5–7 hr post dosing. Sample preparation by SPE was followed by analysis by UHPLC-HRAM MS using a Q Exactive instrument coupled to a Thermo Scientific™ 30

40

50

60

Rel

ativ

e Ab

unda

nc

346.10 346.11 346.12 346.13m/z

0

20Rel

a isotope pattern detail in Figure 7.

FIGURE 6. Clozapine.

NH

Cl

Increased confidence in the elemental composition by direct observation of elements

Increased specificity in isotopic searches by utilizing multiple signals

Robustness against metabolism – searches can be performed on isotopic pattern

2 3 4 5 6 7 8RT [min]

0.0

0.2

y g pAccela™ UHPLC system. Accurate mass data was acquired using alternating full scan MS (70,000 resolution FWHM at m/z 200). Samples of clozapine and metabolites from an incubation with human liver microsomes (0.5 mg/mL protein, 1 uM substrate) were prepared at 0, 15, 30, and 45 minutes. UHPLC separation was achieved with a gradient of ACN and water with 0.1% on a Thermo Scientific™ Hypersil GOLD™

345.0 345.5 346.0 346.5 347.0m/z

0

10

20 346.1171

347.1135

A1

A2

N

N

N

members that are not enzymatically lost as can happen with oxidative dechlorination

Orthogonal detection mechanism to increase confidence that no related peak is missed

C f

4.926

0.6

0.8

1.0

unts

] (10

^9)

Metabolitesou

nts]

(10^

9)

aQ C-18 column (2×100mm, 1.9um).

Data Analysis

Data was analyzed using Compound Discoverer software. The program uses a customizable workflow construction approach (Figure 1) where processing steps, or

d bl d k i kfl A kfl d

Fine Isotopic Pattern Search on Omeprazole Data

Isotope searches in the omeprazole data were performed using two different approaches. Since the resolution of the data was high enough to expose the 34S to 2X

FIGURE 7. Clozapine Isotope Pattern and Fine Isotope Detail.37Cl13C

Can be applied to stable label patterns for more complex analysis

3.7473.4237.4503.7743.546

3.975

4.690

5.697 6.232

4.515

5.530

5.083

4.979

5.916

2 3 4 5 6 7 80.0

0.2

0.4Inte

nsity

[co

Inte

nsity

[co

nodes, are assembled to make a processing workflow. A workflow was constructed using multiple isotope pattern nodes to test different approaches. In addition, metabolite detection was also performed by classical means (combined metabolite search, MMDF, and fragment search) to confirm the results from isotope pattern searches.

13C pattern, two search filters were made. The first searched for compounds having one sulfur (ratio based on A0). This filter would find related metabolites regardless of biotransformation. The second filter was specific to two sulfur peaks and was designed to find sulfation products. The editor for setting the pattern is shown in Figure 3 with settings for a one-sulfur general search. A tolerance was included for b th d i t it f h i t

Note: Metabolites include all combinations of Phase I and Phase II metabolic events that do not add sulfur.

70

80

90

100343.1320

20

40

60

80

100

15N 2X13C20

40

60

80

1002 3 4 5 6 7 8

RT [min]

both mass accuracy and intensity for each isotope.

20

30

40

50

60

70

Rel

ativ

e Ab

unda

nce

345.1291

344.1354

00

All trademarks are the property of Thermo Fisher Scientific and its subsidiaries

343.0 343.5 344.0 344.5 345.0 345.5m/z

0

10

20 All trademarks are the property of Thermo Fisher Scientific and its subsidiaries.

This information is not intended to encourage use of these products in any manners that might infringe the intellectual property rights of others.

PO64100-EN 0614S

4 New Approach for Compound Identification Using Fine Isotopic Pattern Search

New Approach for Compound Identification Using Fine Isotopic Pattern SearchNew Approach for Compound Identification Using Fine Isotopic Pattern SearchCaroline Ding1, Tim Stratton1, Hans Pfaff2, Hans Grensemann2, Christoph Henrich2, 1Thermo Fisher Scientific, San Jose, USA; 2Thermo Fisher Scientific, Bremen, GermanyThermo Fisher Scientific, San Jose, USA; Thermo Fisher Scientific, Bremen, Germany

OverviewPurpose: To demonstrate the use of very high resolution accurate mass full scan data with novel data processing software for fine isotopic pattern recognition to aid in small molecule identification

FIGURE 1. Compound Discoverer Workflow Editor. FIGURE 3. Isotope Search Interface – One-Sulfur Trace. FIGURE 5. Two-Sulfur Trace vs. Metabolites for Omeprazole Urine (0–3 hr).

300

350 Two 34S Trace

An initial search using a classic chlorine approach was performed looking for the abundant 37Cl signal in A2. Subsequent searches were refined first by requiring both the 37Cl and 2X 13C signal in A2 and then by requiring the 15N A1 as well as the 37Cl and 2X 13C in A2. The results of these searches are shown in Figure 8 with the known metabolites labeledmolecule identification.

Methods: Samples analyzed consisted of human urine samples acquired post-dose with omeprazole and human liver microsomal incubates of clozapine. Samples were analyzed by LC-MS using very high resolution on either a Thermo Scientific™ Q Exactive™ hybrid quadrupole-Orbitrap mass spectrometer or a Thermo Scientific™ 100

150

200

250

300 metabolites labeled.

FIGURE 8. Comparison of Clozapine Searches

Inte

nsity

[cou

nts]

(10^

6)

4.67146̂) Simple Cl Search0^

6)

Orbitrap Fusion™ Tribrid™ mass spectrometer. Data processing was performed using a novel processing platform, Thermo Scientific™ Compound Discoverer™ software, specifically for fine isotope pattern detection of related components to determine the ability to specifically detect related peaks with increasing isotope pattern options. Briefly, related peaks were found by detecting the 34S/13C patterns in different formats f l th 15N/37Cl/13C tt f l i

2 3 4 5 6 7 8RT [min]

0

50

4 550

7.1694.455 4.913

0

1

2

3

4

Inten

sity[

coun

ts](1

0̂ Simple Cl Search

Inte

nsity

[cou

nts]

(10

for omeprazole or the 15N/37Cl/13C patterns for clozapine.

Results: Related metabolites were detected using a fine isotopic pattern mechanism and the capabilities of increasing the detail of the pattern was determined by adding additional elemental requirements to normal searches. For example, the normal chlorine pattern search for clozapine samples was enhanced further by requiring the

4.550

60

80

100

sity

[cou

nts]

(10^

6)[c

ount

s] (1

0^6)

4.455 4.913

4.671

1

2

3

4

Inten

sity[

coun

ts](1

0̂6) 37Cl / 13C Search

Inte

nsity

[cou

nts]

(10^

6)

y gpresence of a 37Cl/ 2X13C pattern and further by requiring a full 15N/37Cl/ 2X13C pattern. These improvements reduced background noise and false positives from the simple chlorine search. In addition, the use of fine isotope pattern searches to determine one and two sulfur containing peaks was achieved for the omeprazole sample analysis showing the ability to find sulfate metabolites (two sulfurs) distinct from other

ResultsIsotope Pattern and Resolution Fine Isotopic Pattern Search on Omeprazole Data

Th i d b li d d i bi i f

4.909

3.677

3.853

3.923

4.856

2 3 4 5 6 7 8

RT [min]

0

20

40Inte

nsIn

tens

ity [ 0

4.455 4.913

4.671

1

2

3

4

ntens

it y[co

unts]

(10̂

6)

15N / 37Cl / 13C Search

Demethylation Oxidation

Parent

nsity

[cou

nts]

(10^

6)

metabolites (one sulfur).

IntroductionIsotopic patterns arising from natural isotopic abundances have been utilized in mass

The isotope pattern of any molecule is the result of its constituent elements and their number as well as the relative abundance of (typically heavier) isotopes. These isotopes have small mass differences that can be resolved to directly detect the elements’ presence (Figure 2). The ability to resolve this fine structure formed the basis of the searches performed.

The isotope traces were compared to metabolites detected using a combination of combinatorial metabolism search, MMDF, control comparison, and Fragment Ion Searching (FISh). Results for the one-sulfur search are shown in Figure 4 and for the two-sulfur search in Figure 5. In each case, there is very good overlap between the fine isotopic sulfur trace and the metabolites expected.

In both isotope searches, additional peaks were detected (blue arrows). These peaks could be the result of metabolism not detected by any of the other orthogonal approaches used or could be from endogenous sources which is also likely The simple chlorine pattern search, even though the pattern itself is very significant

Note: Metabolites include Sulfation, Oxidation + Sulfation, and Demethylation + Sulfation1 2 3 4 5 6 7 8 9 10

RT [min]

0

InIn

ten

spectrometric measurements for many years. As resolution capabilities have increased, instruments have been able to resolve the fine isotopic pattern, the separation of extremely close isobars in typically unresolved isotopic pattern members. This additional elemental information can be useful for definitive elemental composition determination in complex de novo applications. In addition, this fine isotope data can b d t f d d i t tt h th t t ibl ith

p

FIGURE 2. Omeprazole Isotope Pattern at Increasing Resolutions.

13C Resolution30 000

FIGURE 4. One-Sulfur Trace vs. Metabolites for Omeprazole Urine (0–3 hr).

approaches used or could be from endogenous sources, which is also likely considering the human urinary nature of the sample.

Using Fine Isotopes to Refine Abundant Isotope Searches

Some elements have abundant isotopes that have been used in the past as isotope

and the matrix not complex, had significant background. The addition of fine isotopic refinement using the 13C signal in the A2 isotope removed nearly all the background while the addition of 15N in A1 resulted in a search that detected only the three related peaks in the sample.

C l i1.2

One 34S Tracebe used to perform more advanced isotope pattern searches that are not possible with normal high resolution accurate mass data. Here we demonstrate the use of very high resolution to extract metabolites in biological samples.

Methods 70

80

90

100

ce

345.1142

40

60

80

100

ativ

e Ab

unda

nce

33S

15N 2H

30,000450,000A0

Some elements have abundant isotopes that have been used in the past as isotope trace tools (chlorine and bromine). Isotope labeling with stable label enrichment has been used in a similar fashion. Both of these approaches may benefit from the inclusion of fine isotope patterns. For this approach, we used clozapine and metabolites in human liver microsomes. Clozapine is shown in Figure 6 and the isotope pattern detail in Figure 7

ConclusionWe have demonstrated the utility of very high resolution to gain access to fine isotopic data and refine isotopic searches with this additional data. The use of fine isotopic data for analysis provides a number of benefits:

0.4

0.6

0.8

1.0

One S Trace

Inte

nsity

[cou

nts]

(10^

9)

Sample Preparation

Samples of omeprazole and metabolites in human urine were collected at 0–3 hr, 3–5 hr, and 5–7 hr post dosing. Sample preparation by SPE was followed by analysis by UHPLC-HRAM MS using a Q Exactive instrument coupled to a Thermo Scientific™ 30

40

50

60

Rel

ativ

e Ab

unda

nc

346.10 346.11 346.12 346.13m/z

0

20Rel

a isotope pattern detail in Figure 7.

FIGURE 6. Clozapine.

NH

Cl

Increased confidence in the elemental composition by direct observation of elements

Increased specificity in isotopic searches by utilizing multiple signals

Robustness against metabolism – searches can be performed on isotopic pattern

2 3 4 5 6 7 8RT [min]

0.0

0.2

y g pAccela™ UHPLC system. Accurate mass data was acquired using alternating full scan MS (70,000 resolution FWHM at m/z 200). Samples of clozapine and metabolites from an incubation with human liver microsomes (0.5 mg/mL protein, 1 uM substrate) were prepared at 0, 15, 30, and 45 minutes. UHPLC separation was achieved with a gradient of ACN and water with 0.1% on a Thermo Scientific™ Hypersil GOLD™

345.0 345.5 346.0 346.5 347.0m/z

0

10

20 346.1171

347.1135

A1

A2

N

N

N

members that are not enzymatically lost as can happen with oxidative dechlorination

Orthogonal detection mechanism to increase confidence that no related peak is missed

C f

4.926

0.6

0.8

1.0

unts

] (10

^9)

Metabolites

ount

s] (1

0^9)

aQ C-18 column (2×100mm, 1.9um).

Data Analysis

Data was analyzed using Compound Discoverer software. The program uses a customizable workflow construction approach (Figure 1) where processing steps, or

d bl d k i kfl A kfl d

Fine Isotopic Pattern Search on Omeprazole Data

Isotope searches in the omeprazole data were performed using two different approaches. Since the resolution of the data was high enough to expose the 34S to 2X

FIGURE 7. Clozapine Isotope Pattern and Fine Isotope Detail.37Cl13C

Can be applied to stable label patterns for more complex analysis

3.7473.4237.4503.7743.546

3.975

4.690

5.697 6.232

4.515

5.530

5.083

4.979

5.916

2 3 4 5 6 7 80.0

0.2

0.4Inte

nsity

[co

Inte

nsity

[co

nodes, are assembled to make a processing workflow. A workflow was constructed using multiple isotope pattern nodes to test different approaches. In addition, metabolite detection was also performed by classical means (combined metabolite search, MMDF, and fragment search) to confirm the results from isotope pattern searches.

13C pattern, two search filters were made. The first searched for compounds having one sulfur (ratio based on A0). This filter would find related metabolites regardless of biotransformation. The second filter was specific to two sulfur peaks and was designed to find sulfation products. The editor for setting the pattern is shown in Figure 3 with settings for a one-sulfur general search. A tolerance was included for b th d i t it f h i t

Note: Metabolites include all combinations of Phase I and Phase II metabolic events that do not add sulfur.

70

80

90

100343.1320

20

40

60

80

100

15N 2X13C20

40

60

80

1002 3 4 5 6 7 8

RT [min]

both mass accuracy and intensity for each isotope.

20

30

40

50

60

70

Rel

ativ

e Ab

unda

nce

345.1291

344.1354

00

All trademarks are the property of Thermo Fisher Scientific and its subsidiaries

343.0 343.5 344.0 344.5 345.0 345.5m/z

0

10

20 All trademarks are the property of Thermo Fisher Scientific and its subsidiaries.

This information is not intended to encourage use of these products in any manners that might infringe the intellectual property rights of others.

PO64100-EN 0614S

5Thermo Scientific Poster Note • PN64100-EN 1114S

New Approach for Compound Identification Using Fine Isotopic Pattern SearchNew Approach for Compound Identification Using Fine Isotopic Pattern SearchCaroline Ding1, Tim Stratton1, Hans Pfaff2, Hans Grensemann2, Christoph Henrich2, 1Thermo Fisher Scientific, San Jose, USA; 2Thermo Fisher Scientific, Bremen, GermanyThermo Fisher Scientific, San Jose, USA; Thermo Fisher Scientific, Bremen, Germany

OverviewPurpose: To demonstrate the use of very high resolution accurate mass full scan data with novel data processing software for fine isotopic pattern recognition to aid in small molecule identification

FIGURE 1. Compound Discoverer Workflow Editor. FIGURE 3. Isotope Search Interface – One-Sulfur Trace. FIGURE 5. Two-Sulfur Trace vs. Metabolites for Omeprazole Urine (0–3 hr).

300

350 Two 34S Trace

An initial search using a classic chlorine approach was performed looking for the abundant 37Cl signal in A2. Subsequent searches were refined first by requiring both the 37Cl and 2X 13C signal in A2 and then by requiring the 15N A1 as well as the 37Cl and 2X 13C in A2. The results of these searches are shown in Figure 8 with the known metabolites labeledmolecule identification.

Methods: Samples analyzed consisted of human urine samples acquired post-dose with omeprazole and human liver microsomal incubates of clozapine. Samples were analyzed by LC-MS using very high resolution on either a Thermo Scientific™ Q Exactive™ hybrid quadrupole-Orbitrap mass spectrometer or a Thermo Scientific™ 100

150

200

250

300 metabolites labeled.

FIGURE 8. Comparison of Clozapine Searches

Inte

nsity

[cou

nts]

(10^

6)

4.67146̂) Simple Cl Search0^

6)

Orbitrap Fusion™ Tribrid™ mass spectrometer. Data processing was performed using a novel processing platform, Thermo Scientific™ Compound Discoverer™ software, specifically for fine isotope pattern detection of related components to determine the ability to specifically detect related peaks with increasing isotope pattern options. Briefly, related peaks were found by detecting the 34S/13C patterns in different formats f l th 15N/37Cl/13C tt f l i

2 3 4 5 6 7 8RT [min]

0

50

4 550

7.1694.455 4.913

0

1

2

3

4

Inten

sity[

coun

ts](1

0̂ Simple Cl Search

Inte

nsity

[cou

nts]

(10

for omeprazole or the 15N/37Cl/13C patterns for clozapine.

Results: Related metabolites were detected using a fine isotopic pattern mechanism and the capabilities of increasing the detail of the pattern was determined by adding additional elemental requirements to normal searches. For example, the normal chlorine pattern search for clozapine samples was enhanced further by requiring the

4.550

60

80

100

sity

[cou

nts]

(10^

6)[c

ount

s] (1

0^6)

4.455 4.913

4.671

1

2

3

4

Inten

sity[

coun

ts](1

0̂6) 37Cl / 13C Search

Inte

nsity

[cou

nts]

(10^

6)

y gpresence of a 37Cl/ 2X13C pattern and further by requiring a full 15N/37Cl/ 2X13C pattern. These improvements reduced background noise and false positives from the simple chlorine search. In addition, the use of fine isotope pattern searches to determine one and two sulfur containing peaks was achieved for the omeprazole sample analysis showing the ability to find sulfate metabolites (two sulfurs) distinct from other

ResultsIsotope Pattern and Resolution Fine Isotopic Pattern Search on Omeprazole Data

Th i d b li d d i bi i f

4.909

3.677

3.853

3.923

4.856

2 3 4 5 6 7 8

RT [min]

0

20

40Inte

nsIn

tens

ity [ 0

4.455 4.913

4.671

1

2

3

4

ntens

it y[co

unts]

(10̂

6)

15N / 37Cl / 13C Search

Demethylation Oxidation

Parent

nsity

[cou

nts]

(10^

6)

metabolites (one sulfur).

IntroductionIsotopic patterns arising from natural isotopic abundances have been utilized in mass

The isotope pattern of any molecule is the result of its constituent elements and their number as well as the relative abundance of (typically heavier) isotopes. These isotopes have small mass differences that can be resolved to directly detect the elements’ presence (Figure 2). The ability to resolve this fine structure formed the basis of the searches performed.

The isotope traces were compared to metabolites detected using a combination of combinatorial metabolism search, MMDF, control comparison, and Fragment Ion Searching (FISh). Results for the one-sulfur search are shown in Figure 4 and for the two-sulfur search in Figure 5. In each case, there is very good overlap between the fine isotopic sulfur trace and the metabolites expected.

In both isotope searches, additional peaks were detected (blue arrows). These peaks could be the result of metabolism not detected by any of the other orthogonal approaches used or could be from endogenous sources which is also likely The simple chlorine pattern search, even though the pattern itself is very significant

Note: Metabolites include Sulfation, Oxidation + Sulfation, and Demethylation + Sulfation1 2 3 4 5 6 7 8 9 10

RT [min]

0

InIn

ten

spectrometric measurements for many years. As resolution capabilities have increased, instruments have been able to resolve the fine isotopic pattern, the separation of extremely close isobars in typically unresolved isotopic pattern members. This additional elemental information can be useful for definitive elemental composition determination in complex de novo applications. In addition, this fine isotope data can b d t f d d i t tt h th t t ibl ith

p

FIGURE 2. Omeprazole Isotope Pattern at Increasing Resolutions.

13C Resolution30 000

FIGURE 4. One-Sulfur Trace vs. Metabolites for Omeprazole Urine (0–3 hr).

approaches used or could be from endogenous sources, which is also likely considering the human urinary nature of the sample.

Using Fine Isotopes to Refine Abundant Isotope Searches

Some elements have abundant isotopes that have been used in the past as isotope

and the matrix not complex, had significant background. The addition of fine isotopic refinement using the 13C signal in the A2 isotope removed nearly all the background while the addition of 15N in A1 resulted in a search that detected only the three related peaks in the sample.

C l i1.2

One 34S Tracebe used to perform more advanced isotope pattern searches that are not possible with normal high resolution accurate mass data. Here we demonstrate the use of very high resolution to extract metabolites in biological samples.

Methods 70

80

90

100

ce

345.1142

40

60

80

100

ativ

e Ab

unda

nce

33S

15N 2H

30,000450,000A0

Some elements have abundant isotopes that have been used in the past as isotope trace tools (chlorine and bromine). Isotope labeling with stable label enrichment has been used in a similar fashion. Both of these approaches may benefit from the inclusion of fine isotope patterns. For this approach, we used clozapine and metabolites in human liver microsomes. Clozapine is shown in Figure 6 and the isotope pattern detail in Figure 7

ConclusionWe have demonstrated the utility of very high resolution to gain access to fine isotopic data and refine isotopic searches with this additional data. The use of fine isotopic data for analysis provides a number of benefits:

0.4

0.6

0.8

1.0

One S Trace

Inte

nsity

[cou

nts]

(10^

9)

Sample Preparation

Samples of omeprazole and metabolites in human urine were collected at 0–3 hr, 3–5 hr, and 5–7 hr post dosing. Sample preparation by SPE was followed by analysis by UHPLC-HRAM MS using a Q Exactive instrument coupled to a Thermo Scientific™ 30

40

50

60

Rel

ativ

e Ab

unda

nc

346.10 346.11 346.12 346.13m/z

0

20Rel

a isotope pattern detail in Figure 7.

FIGURE 6. Clozapine.

NH

Cl

Increased confidence in the elemental composition by direct observation of elements

Increased specificity in isotopic searches by utilizing multiple signals

Robustness against metabolism – searches can be performed on isotopic pattern

2 3 4 5 6 7 8RT [min]

0.0

0.2

y g pAccela™ UHPLC system. Accurate mass data was acquired using alternating full scan MS (70,000 resolution FWHM at m/z 200). Samples of clozapine and metabolites from an incubation with human liver microsomes (0.5 mg/mL protein, 1 uM substrate) were prepared at 0, 15, 30, and 45 minutes. UHPLC separation was achieved with a gradient of ACN and water with 0.1% on a Thermo Scientific™ Hypersil GOLD™

345.0 345.5 346.0 346.5 347.0m/z

0

10

20 346.1171

347.1135

A1

A2

N

N

N

members that are not enzymatically lost as can happen with oxidative dechlorination

Orthogonal detection mechanism to increase confidence that no related peak is missed

C f

4.926

0.6

0.8

1.0

unts

] (10

^9)

Metabolites

ount

s] (1

0^9)

aQ C-18 column (2×100mm, 1.9um).

Data Analysis

Data was analyzed using Compound Discoverer software. The program uses a customizable workflow construction approach (Figure 1) where processing steps, or

d bl d k i kfl A kfl d

Fine Isotopic Pattern Search on Omeprazole Data

Isotope searches in the omeprazole data were performed using two different approaches. Since the resolution of the data was high enough to expose the 34S to 2X

FIGURE 7. Clozapine Isotope Pattern and Fine Isotope Detail.37Cl13C

Can be applied to stable label patterns for more complex analysis

3.7473.4237.4503.7743.546

3.975

4.690

5.697 6.232

4.515

5.530

5.083

4.979

5.916

2 3 4 5 6 7 80.0

0.2

0.4Inte

nsity

[co

Inte

nsity

[co

nodes, are assembled to make a processing workflow. A workflow was constructed using multiple isotope pattern nodes to test different approaches. In addition, metabolite detection was also performed by classical means (combined metabolite search, MMDF, and fragment search) to confirm the results from isotope pattern searches.

13C pattern, two search filters were made. The first searched for compounds having one sulfur (ratio based on A0). This filter would find related metabolites regardless of biotransformation. The second filter was specific to two sulfur peaks and was designed to find sulfation products. The editor for setting the pattern is shown in Figure 3 with settings for a one-sulfur general search. A tolerance was included for b th d i t it f h i t

Note: Metabolites include all combinations of Phase I and Phase II metabolic events that do not add sulfur.

70

80

90

100343.1320

20

40

60

80

100

15N 2X13C20

40

60

80

1002 3 4 5 6 7 8

RT [min]

both mass accuracy and intensity for each isotope.

20

30

40

50

60

70

Rel

ativ

e Ab

unda

nce

345.1291

344.1354

00

All trademarks are the property of Thermo Fisher Scientific and its subsidiaries

343.0 343.5 344.0 344.5 345.0 345.5m/z

0

10

20 All trademarks are the property of Thermo Fisher Scientific and its subsidiaries.

This information is not intended to encourage use of these products in any manners that might infringe the intellectual property rights of others.

PO64100-EN 0614S

6 New Approach for Compound Identification Using Fine Isotopic Pattern Search

New Approach for Compound Identification Using Fine Isotopic Pattern SearchNew Approach for Compound Identification Using Fine Isotopic Pattern SearchCaroline Ding1, Tim Stratton1, Hans Pfaff2, Hans Grensemann2, Christoph Henrich2, 1Thermo Fisher Scientific, San Jose, USA; 2Thermo Fisher Scientific, Bremen, GermanyThermo Fisher Scientific, San Jose, USA; Thermo Fisher Scientific, Bremen, Germany

OverviewPurpose: To demonstrate the use of very high resolution accurate mass full scan data with novel data processing software for fine isotopic pattern recognition to aid in small molecule identification

FIGURE 1. Compound Discoverer Workflow Editor. FIGURE 3. Isotope Search Interface – One-Sulfur Trace. FIGURE 5. Two-Sulfur Trace vs. Metabolites for Omeprazole Urine (0–3 hr).

300

350 Two 34S Trace

An initial search using a classic chlorine approach was performed looking for the abundant 37Cl signal in A2. Subsequent searches were refined first by requiring both the 37Cl and 2X 13C signal in A2 and then by requiring the 15N A1 as well as the 37Cl and 2X 13C in A2. The results of these searches are shown in Figure 8 with the known metabolites labeledmolecule identification.

Methods: Samples analyzed consisted of human urine samples acquired post-dose with omeprazole and human liver microsomal incubates of clozapine. Samples were analyzed by LC-MS using very high resolution on either a Thermo Scientific™ Q Exactive™ hybrid quadrupole-Orbitrap mass spectrometer or a Thermo Scientific™ 100

150

200

250

300 metabolites labeled.

FIGURE 8. Comparison of Clozapine Searches

Inte

nsity

[cou

nts]

(10^

6)

4.67146̂) Simple Cl Search0^

6)

Orbitrap Fusion™ Tribrid™ mass spectrometer. Data processing was performed using a novel processing platform, Thermo Scientific™ Compound Discoverer™ software, specifically for fine isotope pattern detection of related components to determine the ability to specifically detect related peaks with increasing isotope pattern options. Briefly, related peaks were found by detecting the 34S/13C patterns in different formats f l th 15N/37Cl/13C tt f l i

2 3 4 5 6 7 8RT [min]

0

50

4 550

7.1694.455 4.913

0

1

2

3

4

Inten

sity[

coun

ts](1

0̂ Simple Cl Search

Inte

nsity

[cou

nts]

(10

for omeprazole or the 15N/37Cl/13C patterns for clozapine.

Results: Related metabolites were detected using a fine isotopic pattern mechanism and the capabilities of increasing the detail of the pattern was determined by adding additional elemental requirements to normal searches. For example, the normal chlorine pattern search for clozapine samples was enhanced further by requiring the

4.550

60

80

100

sity

[cou

nts]

(10^

6)[c

ount

s] (1

0^6)

4.455 4.913

4.671

1

2

3

4

Inten

sity[

coun

ts](1

0̂6) 37Cl / 13C Search

Inte

nsity

[cou

nts]

(10^

6)

y gpresence of a 37Cl/ 2X13C pattern and further by requiring a full 15N/37Cl/ 2X13C pattern. These improvements reduced background noise and false positives from the simple chlorine search. In addition, the use of fine isotope pattern searches to determine one and two sulfur containing peaks was achieved for the omeprazole sample analysis showing the ability to find sulfate metabolites (two sulfurs) distinct from other

ResultsIsotope Pattern and Resolution Fine Isotopic Pattern Search on Omeprazole Data

Th i d b li d d i bi i f

4.909

3.677

3.853

3.923

4.856

2 3 4 5 6 7 8

RT [min]

0

20

40Inte

nsIn

tens

ity [ 0

4.455 4.913

4.671

1

2

3

4

ntens

it y[co

unts]

(10̂

6)

15N / 37Cl / 13C Search

Demethylation Oxidation

Parent

nsity

[cou

nts]

(10^

6)

metabolites (one sulfur).

IntroductionIsotopic patterns arising from natural isotopic abundances have been utilized in mass

The isotope pattern of any molecule is the result of its constituent elements and their number as well as the relative abundance of (typically heavier) isotopes. These isotopes have small mass differences that can be resolved to directly detect the elements’ presence (Figure 2). The ability to resolve this fine structure formed the basis of the searches performed.

The isotope traces were compared to metabolites detected using a combination of combinatorial metabolism search, MMDF, control comparison, and Fragment Ion Searching (FISh). Results for the one-sulfur search are shown in Figure 4 and for the two-sulfur search in Figure 5. In each case, there is very good overlap between the fine isotopic sulfur trace and the metabolites expected.

In both isotope searches, additional peaks were detected (blue arrows). These peaks could be the result of metabolism not detected by any of the other orthogonal approaches used or could be from endogenous sources which is also likely The simple chlorine pattern search, even though the pattern itself is very significant

Note: Metabolites include Sulfation, Oxidation + Sulfation, and Demethylation + Sulfation1 2 3 4 5 6 7 8 9 10

RT [min]

0

InIn

ten

spectrometric measurements for many years. As resolution capabilities have increased, instruments have been able to resolve the fine isotopic pattern, the separation of extremely close isobars in typically unresolved isotopic pattern members. This additional elemental information can be useful for definitive elemental composition determination in complex de novo applications. In addition, this fine isotope data can b d t f d d i t tt h th t t ibl ith

p

FIGURE 2. Omeprazole Isotope Pattern at Increasing Resolutions.

13C Resolution30 000

FIGURE 4. One-Sulfur Trace vs. Metabolites for Omeprazole Urine (0–3 hr).

approaches used or could be from endogenous sources, which is also likely considering the human urinary nature of the sample.

Using Fine Isotopes to Refine Abundant Isotope Searches

Some elements have abundant isotopes that have been used in the past as isotope

and the matrix not complex, had significant background. The addition of fine isotopic refinement using the 13C signal in the A2 isotope removed nearly all the background while the addition of 15N in A1 resulted in a search that detected only the three related peaks in the sample.

C l i1.2

One 34S Tracebe used to perform more advanced isotope pattern searches that are not possible with normal high resolution accurate mass data. Here we demonstrate the use of very high resolution to extract metabolites in biological samples.

Methods 70

80

90

100

ce

345.1142

40

60

80

100

ativ

e Ab

unda

nce

33S

15N 2H

30,000450,000A0

Some elements have abundant isotopes that have been used in the past as isotope trace tools (chlorine and bromine). Isotope labeling with stable label enrichment has been used in a similar fashion. Both of these approaches may benefit from the inclusion of fine isotope patterns. For this approach, we used clozapine and metabolites in human liver microsomes. Clozapine is shown in Figure 6 and the isotope pattern detail in Figure 7

ConclusionWe have demonstrated the utility of very high resolution to gain access to fine isotopic data and refine isotopic searches with this additional data. The use of fine isotopic data for analysis provides a number of benefits:

0.4

0.6

0.8

1.0

One S Trace

Inte

nsity

[cou

nts]

(10^

9)

Sample Preparation

Samples of omeprazole and metabolites in human urine were collected at 0–3 hr, 3–5 hr, and 5–7 hr post dosing. Sample preparation by SPE was followed by analysis by UHPLC-HRAM MS using a Q Exactive instrument coupled to a Thermo Scientific™ 30

40

50

60

Rel

ativ

e Ab

unda

nc

346.10 346.11 346.12 346.13m/z

0

20Rel

a isotope pattern detail in Figure 7.

FIGURE 6. Clozapine.

NH

Cl

Increased confidence in the elemental composition by direct observation of elements

Increased specificity in isotopic searches by utilizing multiple signals

Robustness against metabolism – searches can be performed on isotopic pattern

2 3 4 5 6 7 8RT [min]

0.0

0.2

y g pAccela™ UHPLC system. Accurate mass data was acquired using alternating full scan MS (70,000 resolution FWHM at m/z 200). Samples of clozapine and metabolites from an incubation with human liver microsomes (0.5 mg/mL protein, 1 uM substrate) were prepared at 0, 15, 30, and 45 minutes. UHPLC separation was achieved with a gradient of ACN and water with 0.1% on a Thermo Scientific™ Hypersil GOLD™

345.0 345.5 346.0 346.5 347.0m/z

0

10

20 346.1171

347.1135

A1

A2

N

N

N

members that are not enzymatically lost as can happen with oxidative dechlorination

Orthogonal detection mechanism to increase confidence that no related peak is missed

C f

4.926

0.6

0.8

1.0

unts

] (10

^9)

Metabolites

ount

s] (1

0^9)

aQ C-18 column (2×100mm, 1.9um).

Data Analysis

Data was analyzed using Compound Discoverer software. The program uses a customizable workflow construction approach (Figure 1) where processing steps, or

d bl d k i kfl A kfl d

Fine Isotopic Pattern Search on Omeprazole Data

Isotope searches in the omeprazole data were performed using two different approaches. Since the resolution of the data was high enough to expose the 34S to 2X

FIGURE 7. Clozapine Isotope Pattern and Fine Isotope Detail.37Cl13C

Can be applied to stable label patterns for more complex analysis

3.7473.4237.4503.7743.546

3.975

4.690

5.697 6.232

4.515

5.530

5.083

4.979

5.916

2 3 4 5 6 7 80.0

0.2

0.4Inte

nsity

[co

Inte

nsity

[co

nodes, are assembled to make a processing workflow. A workflow was constructed using multiple isotope pattern nodes to test different approaches. In addition, metabolite detection was also performed by classical means (combined metabolite search, MMDF, and fragment search) to confirm the results from isotope pattern searches.

13C pattern, two search filters were made. The first searched for compounds having one sulfur (ratio based on A0). This filter would find related metabolites regardless of biotransformation. The second filter was specific to two sulfur peaks and was designed to find sulfation products. The editor for setting the pattern is shown in Figure 3 with settings for a one-sulfur general search. A tolerance was included for b th d i t it f h i t

Note: Metabolites include all combinations of Phase I and Phase II metabolic events that do not add sulfur.

70

80

90

100343.1320

20

40

60

80

100

15N 2X13C20

40

60

80

1002 3 4 5 6 7 8

RT [min]

both mass accuracy and intensity for each isotope.

20

30

40

50

60

70

Rel

ativ

e Ab

unda

nce

345.1291

344.1354

00

All trademarks are the property of Thermo Fisher Scientific and its subsidiaries

343.0 343.5 344.0 344.5 345.0 345.5m/z

0

10

20 All trademarks are the property of Thermo Fisher Scientific and its subsidiaries.

This information is not intended to encourage use of these products in any manners that might infringe the intellectual property rights of others.

PO64100-EN 0614S

PN64100-EN 1114S

Africa +43 1 333 50 34 0Australia +61 3 9757 4300Austria +43 810 282 206Belgium +32 53 73 42 41Canada +1 800 530 8447China 800 810 5118 (free call domestic)

400 650 5118

Denmark +45 70 23 62 60Europe-Other +43 1 333 50 34 0Finland +358 9 3291 0200France +33 1 60 92 48 00Germany +49 6103 408 1014India +91 22 6742 9494Italy +39 02 950 591

Japan +81 45 453 9100Korea +82 2 3420 8600Latin America +1 561 688 8700Middle East +43 1 333 50 34 0Netherlands +31 76 579 55 55New Zealand +64 9 980 6700Norway +46 8 556 468 00

Russia/CIS +43 1 333 50 34 0Singapore +65 6289 1190Spain +34 914 845 965Sweden +46 8 556 468 00Switzerland +41 61 716 77 00UK +44 1442 233555USA +1 800 532 4752

www.thermoscientific.com©2014 Thermo Fisher Scientific Inc. All rights reserved. ISO is a trademark of the International Standards Organization. All other trademarks are the property of Thermo Fisher Scientific and its subsidiaries. This information is presented as an example of the capabilities of Thermo Fisher Scientific products. It is not intended to encourage use of these products in any manners that might infringe the intellectual property rights of others. Specifications, terms and pricing are subject to change. Not all products are available in all countries. Please consult your local sales representative for details.

Thermo Fisher Scientific, San Jose, CA USA is ISO 13485 Certified.

ISO 13485