Post on 11-Jan-2016
description
transcript
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