the category approach for predicting mutagenicity and carcinogenicity

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Laboratory of Mathematical Chemistry, University “Prof. As. Zlatarov”, Bourgas, Bulgaria The Category Approach for Predicting Mutagenicity and Carcinogenicity

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The Category Approach for Predicting Mutagenicity and Carcinogenicity. Laboratory of Mathematical Chemistry, University “Prof. As. Zlatarov”, Bourgas, Bulgaria. Toolbox General Scheme. Input. IUCLID5 interface: XML, Web Services Transfer of data from IUCLID 5 to Toolbox. - PowerPoint PPT Presentation

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Laboratory of Mathematical Chemistry, University “Prof. As. Zlatarov”, Bourgas, Bulgaria

The Category Approach for Predicting Mutagenicity and Carcinogenicity

Toolbox

General Scheme

Input •IUCLID5 interface: XML, Web Services

•Transfer of data from IUCLID 5 to Toolbox

4

Comparison and visualization functionalities in Toolbox

Functionalities 1: Correlation between the categories of two profiling schemes

5The fist profiler has the categories: Active; Non activeThe second one has the categories: Binding; Non binding

Bar diagram showing the number of chemicals meeting the boundaries of two binary profiles

6

Functionality 2: Correlation between two profiles by analyzing the distribution of the categories of one of the profile across the

categories of the other profile

The fist profile has categories: Strong, Weak, NonThe second one has categories: Category1, Category2, Category3, Category4

7

Functionality 3: Correlation between two profiles by analyzing the distributions of their categories

in case of using category combinations (working with multifunctional chemicals)

When more than one category is assigned simultaneously to a chemical, then unique combinations of such categories are used

8

The proposed stages of the categorization approach

Stage 1. Profiling databases according to endpoint specific profiles

• The following endpoint specific profiles were implemented– Oncologic Primary Classification

– Mutagenicity/carcinogenicity alerts by Benigni/Bossa

– Micronucleus alerts by Benigni/Bossa

• The following databases with mutagenicity and carcinogenicity data were used:– HPV Carcinogenicity containing 216 chemicals and

– ISSCAN containing 1129 chemicals

9

Stage 2. Subcategorization of obtained endpoint specific categories by molecular interaction mechanisms

• Chemical distribution according to endpoint specific profiles is analyzed*

• Categories were selected highly populated by chemicals:• Aromatic amines - consisting of 39 and 271 chemicals in HPV Carcinogenicity and

ISSCAN, respectively• Halogenated linear aliphatic types of compounds - consisting of 27 and 44

chemicals in HPV Carcinogenicity and ISSCAN, respectively

• The Toolbox profiles for DNA and protein binding mechanisms have been used for subcategorization of the endpoint specific categories of Aromatic amines and Halogenated linear aliphatic types of compounds

• The profiling for DNA and protein binding mechanisms were applied without and with using liver rat S9 metabolism

The proposed stages of the categorization approach

*See the presentation for Assessing correlation between the categories of profiling schemes

10

Stage 3. Validating the correlation between mechanistic subcategories based on DNA binding mechanisms and AMES

• The validation is based on comparison of the correlations for selected classes - aromatic amines and halogenated linear aliphatic types of compounds derived from:

– HPV Carcinogenicity and – ISSCAN

Stage 4. Validating the correlation between mechanistic subcategories based on DNA and protein binding mechanisms and carcinogenicity

• The validation is based on comparison of the correlations for selected classes - aromatic amines and halogenated linear aliphatic types of compounds derived from:

– HPV Carcinogenicity and – ISSCAN

The proposed stages of the categorization approach

11

Stage 5. Identifying the boundaries of the combined endpoint specific and binding mechanism categories providing >75% correlation with genotoxic effects and carcinogenicity

• Along with AMES and carcinogenicity the correlation with other genotox effects was also studied, such as CA, MNT and CTA

Stage 6. Coding boundaries of the combined categories highly correlating with the genotox and/or carcinogenicity effects

Stage 7. Screening of inventories for chemicals falling in the domains of highly correlating combined categories for searching data to support the boundaries of these categories

The proposed stages of the categorization approach

12

Stage 1. Profiling databases according to endpoint specific profiles

HPV Carcinogenicity database profiled according to Oncologic Primary Classifications

13

Stage 1. Profiling databases according to endpoint specific profiles

ISSCAN database profiled according to Oncologic Primary Classifications

14

Stage 2. Subcategorization of obtained endpoint specific categories by molecular interaction mechanisms

Analysis of the distribution of HPV carcinogenicity database (216) according to Oncologic Primary Classification

15

Aromatic amines as one of all categories with the biggest number of chemicals.

Total number 39 chemicals

Stage 2. Subcategorization of obtained endpoint specific categories by molecular interaction mechanisms

Highly populated categories are identified

16

Stage 2. Subcategorization of obtained endpoint specific categories by molecular interaction mechanisms

Distribution of 39 Aromatic amines across Ames experimental data

17

Stage 2. Subcategorization of obtained endpoint specific categories by molecular interaction mechanismsSequence of steps to analyze the distribution of 39 Aromatic amines across DNA

binding and Ames data

18

Sorted by descending order of correlation

Stage 2. Subcategorization of obtained endpoint specific categories by molecular interaction mechanisms

Distribution of 39 Aromatic amines across DNA binding and Ames data

19

Stage 2. Subcategorization of obtained endpoint specific categories by molecular interaction mechanisms

Sequence of steps to analyze the distribution of 39 Aromatic amines across DNA binding taking into account liver metabolism and Ames data

20

Stage 2. Subcategorization of obtained endpoint specific categories by molecular interaction mechanisms

Distribution of 39 Aromatic amines across DNA binding taking into account liver metabolism and Ames data

Sorted by Positive data

Sorted by descending order of correlation

21

Stage 2. Subcategorization of obtained endpoint specific categories by molecular interaction mechanisms

Distribution of 39 Aromatic amines across DNA binding taking into account liver metabolism and Ames data

Highlight chemical to see detailed information for generated metabolites

Detailed information for generated metabolites.

22

Right click

Detailed information for metabolically generated metabolites.

Stage 2. Subcategorization of obtained endpoint specific categories by molecular interaction mechanisms

Distribution of 39 Aromatic amines across DNA binding taking into account liver metabolism and Ames data

23

Detailed information for metabolically generated metabolites.

Click Explain to see detailed info.

Stage 2. Subcategorization of obtained endpoint specific categories by molecular interaction mechanisms

Distribution of 39 Aromatic amines across DNA binding taking into account liver metabolism and Ames data

24

Detailed information for metabolically generated metabolites.

Click Details to see the categories of generated metabolites

Stage 2. Subcategorization of obtained endpoint specific categories by molecular interaction mechanisms

Distribution of 39 Aromatic amines across DNA binding taking into account liver metabolism and Ames data

25

Detailed information for metabolically generated metabolites.

The target chemical has 9 generated metabolites falling into 8 categories

Stage 2. Subcategorization of obtained endpoint specific categories by molecular interaction mechanisms

Distribution of 39 Aromatic amines across DNA binding taking into account liver metabolism and Ames data

26

Detailed information for metabolically generated metabolites.

Highlight metabolite then click Details to see why the metabolite falls into this

category

Stage 2. Subcategorization of obtained endpoint specific categories by molecular interaction mechanisms

Distribution of 39 Aromatic amines across DNA binding taking into account liver metabolism and Ames data

27

Detailed information for metabolically generated metabolites.

The current metabolite has fragment highlighted in red corresponding to the

category of Aromatic Amines

Click on Amines to see mechanistic justification of the category

Stage 2. Subcategorization of obtained endpoint specific categories by molecular interaction mechanisms

Distribution of 39 Aromatic amines across DNA binding taking into account liver metabolism and Ames data

28

Click on Advance to see structural boundaries of each category

Stage 2. Subcategorization of obtained endpoint specific categories by molecular interaction mechanisms

Distribution of 39 Aromatic amines across DNA binding taking into account liver metabolism and Ames data

29

Stage 2. Subcategorization of obtained endpoint specific categories by molecular interaction mechanisms

Distribution of 39 Aromatic amines across combined DNA and Protein binding categories and Carcinogenicity data

Sorted by descending order of correlation

30

Stage 2. Subcategorization of obtained endpoint specific categories by molecular interaction mechanisms

Distribution of 39 Aromatic amines across combined DNA and Protein binding categories taking into account liver metabolism, and Carcinogenicity data

Sorted by descending order of correlation

31

Distribution of ISSCAN Carcinogenicity database (1129)according to Oncologic Primary Classification

32

Aromatic amines is one of the categories with the highest population of chemicals.

Total number 271 chemicals

Stage 2. Subcategorization of obtained endpoint specific categories by molecular interaction mechanisms

Highly populated categories are identified

33

Stage 2. Subcategorization of obtained endpoint specific categories by molecular interaction mechanisms

Distribution of 271 Aromatic amines category across Ames experimental data

34

Stage 2. Subcategorization of obtained endpoint specific categories by molecular interaction mechanisms

Adding Aromatic amines as target list

Highlight Aromatic amines

Click on Add as a target list button

35

Stage 2. Subcategorization of obtained endpoint specific categories by molecular interaction mechanisms

Aromatic amines as a target list

36

Sorted by descending order of correlation

Stage 2. Subcategorization of obtained endpoint specific categories by molecular interaction mechanisms

Distribution of 271 Aromatic amines according to DNA binding and Ames data

Categories highly correlating with Ames data

37

Stage 2. Subcategorization of obtained endpoint specific categories by molecular interaction mechanisms

Distributing of 271 Aromatic amines across DNA binding taking into account liver metabolism and Ames data

Categories highly correlating with Ames data accounting for liver metabolism

Sorted by descending order of correlation

38

Stage 2. Subcategorization of obtained endpoint specific categories by molecular interaction mechanisms

Distribution of 271 Aromatic amines according to combined DNA and Protein binding categories and Carcinogenicity data

Categories highly correlating with Carcinogenicity data

Sorted by descending order of correlation

39

Stage 2. Subcategorization of obtained endpoint specific categories by molecular interaction mechanisms

Distributing of 271 Aromatic amines across DNA and Protein binding categories taking into account liver metabolism and Carcinogenicity data

Categories highly correlating with Carcinogenicity data accounting liver metabolism

Sorted by descending order of correlation

40

Stage 3. Validating the correlation between mechanistic subcategories based on DNA binding mechanisms and AMES data

Aromatic amines (39 chemicals) Aromatic amines (271 chemicals)

41

Stage 3. Validating the correlation between mechanistic subcategories based on DNA binding taking into account liver metabolism and AMES data

Aromatic amines (39 chemicals) Aromatic amines (271 chemicals)

42Aromatic amines (39 chemicals) Aromatic amines (271 chemicals)

Stage 4. Validating the correlation between mechanistic subcategories based on DNA and Protein binding mechanisms and Carcinogenicity data

43

Stage 4. Validating the correlation between mechanistic subcategories based on DNA and Protein binding taking into account liver metabolism and

Carcinogenicity data

Aromatic amines (39 chemicals) Aromatic amines (271 chemicals)

44Aromatic amines (39 chemicals) Aromatic amines (271 chemicals)

Category 1

Common categories identified in both sets of chemicals

Stage 5. Identifying category boundaries in terms of endpoint specific classes and binding mechanisms providing >75% correlation with genotoxic effects and

carcinogenicity

45Aromatic amines (39 chemicals) Aromatic amines (271 chemicals)

Category 2

Common categories identified in both set of chemicals

Stage 5. Identifying category boundaries in terms of endpoint specific classes and binding mechanisms providing >75% correlation with genotoxic effects and

carcinogenicity

46Aromatic amines (39 chemicals) Aromatic amines (271 chemicals)

Category 3

Common categories identified in both set of chemicals

Stage 5. Identifying category boundaries in terms of endpoint specific classes and binding mechanisms providing >75% correlation with genotoxic effects and

carcinogenicity

47Aromatic amines (39 chemicals) Aromatic amines (271 chemicals)

Common categories identified in both set of chemicals

Stage 5. Identifying category boundaries in terms of endpoint specific classes and binding mechanisms providing >75% correlation with genotoxic effects and

carcinogenicity

Category 4 is based on partial overlapping between two sets

48Aromatic amines (39 chemicals) Aromatic amines (271 chemicals)

Common categories identified in both set of chemicals

Stage 5. Identifying category boundaries in terms of endpoint specific classes and binding mechanisms providing >75% correlation with genotoxic effects and

carcinogenicity

Category 5 is based on partial overlapping between two sets

49

Building profilers for screening inventories based on Oncologic classification and DNA alerts without metabolism

Oncologic class 1 and DNA boundaries 1Oncologic class 1 and DNA boundaries 2Oncologic class 1 and DNA boundaries 3

…………………………..Oncologic class 2 and DNA boundaries 1Oncologic class 2 and DNA boundaries 2Oncologic class 2 and DNA boundaries 3……………………………………………Oncologic class n and DNA boundaries1Oncologic class n and DNA boundaries2Oncologic class n and DNA boundaries3

Stage 6. Building profiles for categories highly correlating with the genotox and carcinogenicity effects

50

Building profilers for screening inventories based on Oncologic classification and DNA alerts with metabolism

Oncologic class 1 and DNA boundaries with metabolism 1Oncologic class 1 and DNA boundaries with metabolism 2Oncologic class 1 and DNA boundaries with metabolism 3

…………………………..Oncologic class 2 and DNA boundaries with metabolism 1Oncologic class 2 and DNA boundaries with metabolism 2Oncologic class 2 and DNA boundaries with metabolism 3……………………………………………Oncologic class n and DNA boundaries with metabolism 1Oncologic class n and DNA boundaries with metabolism 2Oncologic class n and DNA boundaries with metabolism 3

Stage 6. Building profiles for categories highly correlating with the genotox and carcinogenicity effects

51

Building profilers for screening inventories based on Mutagenicity/carcinogenicity alerts by Benigni/Bossa and DNA alerts without metabolism

Benigni/Bossa class 1 and DNA boundaries 1 Benigni/Bossa class 1 and DNA boundaries 2 Benigni/Bossa class 1 and DNA boundaries 3

………………………….. Benigni/Bossa class 2 and DNA boundaries 1 Benigni/Bossa class 2 and DNA boundaries 2 Benigni/Bossa class 2 and DNA boundaries 3…………………………………………… Benigni/Bossa class n and DNA boundaries 1 Benigni/Bossa class n and DNA boundaries 2 Benigni/Bossa class n and DNA boundaries 3

Stage 6. Building profiles for categories highly correlating with the genotox and carcinogenicity effects

52

Building profilers for screening inventories based on Mutagenicity/carcinogenicity alerts by Benigni/Bossa and DNA alerts with metabolism

Benigni/Bossa class 1 and DNA boundaries with metabolism 1 Benigni/Bossa class 1 and DNA boundaries with metabolism 2 Benigni/Bossa class 1 and DNA boundaries with metabolism 3

………………………….. Benigni/Bossa class 2 and DNA boundaries with metabolism 1 Benigni/Bossa class 2 and DNA boundaries with metabolism 2 Benigni/Bossa class 2 and DNA boundaries with metabolism 3…………………………………………… Benigni/Bossa class n and DNA boundaries with metabolism 1 Benigni/Bossa class n and DNA boundaries with metabolism 2 Benigni/Bossa class n and DNA boundaries with metabolism 3

Stage 6. Building profiles for categories highly correlating with the genotox and carcinogenicity effects

53

Stage 6. Profiler for screening inventories based on Oncologic and DNA alerts without metabolism

Oncologic class + Category 1 (DNA without S9)

Coded boundaries

54

Stage 6. Profiler for screening inventories based on Oncologic and DNA alerts without metabolism

Oncologic class + Category 2 (DNA without S9)

Coded boundaries

55

Stage 6. Profiler for screening inventories based on Oncologic and DNA alerts without metabolism

Oncologic class + Category 3 (DNA without S9)

Coded boundaries

56

Stage 6. Profiler for screening inventories based on Oncologic and DNA alerts without metabolism

Oncologic class + Category 4 (DNA without S9)

Coded boundaries

57

Stage 6. Profiler for screening inventories based on Oncologic and DNA alerts without metabolism

Oncologic class + Category 5 (DNA without S9)

Coded boundaries

58Aromatic amines (39 chemicals) Aromatic amines (271 chemicals)

Category 1

Common categories based on analysis between two sets of aromatic amine

Stage 6. 1. Automatic generation of Profiler for screening inventories based on Oncologic and DNA alerts without metabolism

59Aromatic amines (39 chemicals) Aromatic amines (271 chemicals)

Category 2

Stage 6. 1. Automatic generation of Profiler for screening inventories based on Oncologic and DNA alerts without metabolism

Common categories based on analysis between two sets of aromatic amine

60Aromatic amines (39 chemicals) Aromatic amines (271 chemicals)

Category 3

Stage 6. 1. Automatic generation of Profiler for screening inventories based on Oncologic and DNA alerts without metabolism

Common categories based on analysis between two sets of aromatic amine

61Aromatic amines (39 chemicals) Aromatic amines (271 chemicals)

Common categories identified in both set of chemicals

Stage 5. Identifying category boundaries in terms of endpoint specific classes and binding mechanisms providing >75% correlation with genotoxic effects and

carcinogenicity

Category 4

62Aromatic amines (39 chemicals) Aromatic amines (271 chemicals)

Common categories identified in both set of chemicals

Stage 5. Identifying category boundaries in terms of endpoint specific classes and binding mechanisms providing >75% correlation with genotoxic effects and

carcinogenicity

Category 5

63Aromatic amines (39 chemicals) Aromatic amines (271 chemicals)

Stage 6. 1. Automatic generation of Profiler for screening inventories based on Oncologic and DNA alerts without metabolism

Common categories based on analysis between two sets of aromatic amine

64

Stage 6. 1. Automatic generation of Profiler for screening inventories based on Oncologic and DNA alerts without metabolism

Common categories could be selected by simultaneously clicking on “Ctrl” button and on the beginning of the

corresponding category row

65

Stage 6. 1. Automatic generation of Profiler for screening inventories based on Oncologic and DNA alerts without metabolism

The selected rows with categories are labeled

with “s”

66

Stage 6. 1. Automatic generation of Profiler for screening inventories based on Oncologic and DNA alerts without metabolism

Click on “Create scheme” button

67

Stage 6. 1. Automatic generation of Profiler for screening inventories based on Oncologic and DNA alerts without metabolism

The profiler with expected categories has

been performed

68

Stage 6. 1. Automatic generation of Profiler for screening inventories based on Oncologic and DNA alerts without metabolism

In order to include Aromatic amine as a part of each category,

it is needed to defined new referential boundary

69

Stage 6. 1. Automatic generation of Profiler for screening inventories based on Oncologic and DNA alerts without metabolism

Select Oncologic profiler and add “Aromatic Amines” as a

referential category.

70

Stage 6. 1. Automatic generation of Profiler for screening inventories based on Oncologic and DNA alerts without metabolism

Select two referential boundaries and combined them by logically

“AND”

71

Stage 6. 1. Automatic generation of Profiler for screening inventories based on Oncologic and DNA alerts without metabolism

Save the profile by clicking on “Save as” button

72

Stage 6. 1. Automatic generation of Profiler for screening inventories based on Oncologic and DNA alerts without metabolism

Give the name of the file and click “Save”

73

Stage 6. 1. Automatic generation of Profiler for screening inventories based on Oncologic and DNA alerts without metabolism

The profile has been saved

The automatic generated profiler now could be used for screening.

74

Stage 7. Screening of inventories for chemicals falling in highly correlating categories for searching data to support the boundaries of

these categories

Screening of HPVC EU inventory (4843 chemicals) by the profile: Aromatic Amines (Oncologic) and DNA binding (categories #1-5) highly correlating with AMES data

75

Stage 7. Screening of inventories for chemicals falling in highly correlating categories for searching data to support the boundaries of

these categories

Distribution of HPVC EU inventory across the profile: Aromatic Amines (Oncologic) and DNA binding (categories #1-5) highly correlating with AMES data

76

15 chemicals correspond to this profile

Stage 7. Screening of inventories for chemicals falling in highly correlating categories for searching data to support the boundaries of

these categories

Distribution of HPVC EU inventory across the profile: Aromatic Amines (Oncologic) and DNA binding (categories #1-5) highly correlating with AMES data

77

Experimental AMES data for HPVC chemicals confirming the predictive power of the identified categories

Category/Total 4834 Experimental Ames data*

Positive Negative No data

Summary 15 10 3 2

Ar.amine (Onco) + Category 1 (DNA without S9)

4 2 2

Ar.amine (Onco) + Category 2 (DNA without S9)

2 2

Ar.amine (Onco) + Category 3 (DNA without S9)

9 6 1 2

* No information for S9 metabolism

78

Stage 6. Profiler for screening inventories based on Aromatic Amines (Oncologic) and DNA/Protein binding accounting for metabolism

(categories #1-9)

Oncologic class + DNA/Protein with S9

79

Stage 7. Screening of inventories for chemicals falling in highly correlating categories for searching data to support the boundaries of

these categories

Screening of US HPV Challenge Program inventory (9125 chemicals) by the updated profile: Aromatic Amines (Oncologic) and DNA /Protein binding accounting for

metabolism (categories #1-9) highly correlating with carcinogenicity data

80

Stage 7. Screening of inventories for chemicals falling in highly correlating categories for searching data to support the boundaries of

these categories

Distribution of US HPV Challenge Program inventory across the updated profile: Aromatic Amines (Oncologic) and DNA/Protein binding accounting for metabolism

(categories #1 - 9) highly correlating with carcinogenicity data

81

Stage 7. Screening of inventories for chemicals falling in highly correlating categories for searching data to support the boundaries of

these categories

US HPV Challenge Program (9125) chemicals were screened by the updated profile highly correlating with carcinogenicity These chemicals could be considered as

potential carcinogens

InventoryUS HPV Challenge Program

Total9125

Experimental Carcinogenicity data

ISSCAN

Positive Negative Equivocal No data

Profiled chemicals

581 31* 13** 3*** 534

Detailed information*31_positive.pdf**13_negative.pdf***3_equivocal.pdf

Screening of 581 chemicals from US HPV Challenge Program inventory according to

Mutagenicity/Carcinogenicity alerts by Benigni/Bossa profiler

Distribution of 581 chemicals from US HPV Challenge Program

inventory by Benigni/Bossa profiler

83

Distribution of 581 chemicals from US HPV Challenge Program

inventory by Benigni/Bossa profiler

84

InventoryUS HPV Challenge program

Total581

Mutagenicity/Carcinogenicity

alerts by Benigni/Bossa

SA for genotoxic carcinogenicity

SA for nongenotoxic

carcinogenicity

No alert for carcinogenicity

Profiled chemicals 581 539 0 42

Detailed information*42_No alert.pdf*42_No alert.xls