structure-activity relationships in toxicology: introduction (and a case study) part i. romualdo...
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Structure-Activity Relationships in Toxicology:
Introduction (and a case study)Part I.
Romualdo BenigniRomualdo BenigniIstituto Superiore di Sanita’ RomeIstituto Superiore di Sanita’ Rome
Three Rs:
Replacement, Reduction, and Refinement of animal testing
with the aims of shortening times of toxicity testing, protecting
animal health and welfare, and saving money
Traditional toxicology has been the major source of information
Now, opportunities to accept “alternative” approaches
Traditional toxicology has been the major source of information in EU
Now, opportunities to accept “alternative” approaches
REACH: EU new regulation of chemicals
Registration, Evaluation and Assessment of Chemicals
•non-testing methods, including (Q)SARs, read-across and chemical category approaches will be used more extensively and more systematically than under previous EU legislation….
Read-Across:data gaps filling approach; information for one or more source chemicals is used to make a prediction for a target chemical, considered to be similar in some way.
(Q)SAR:(Quantitative) Structure-Activity Relationships
Chemical category:group of chemicals whose physicochemical and toxicological properties are likely to be similar or follow a regular pattern as a result of structural similarity
OECD Principles
To facilitate the consideration of a (Q)SAR model for regulatory purposes, it should be associated with the following information:
• 1) a defined endpoint
• 2) an unambiguous algorithm
• 3) a defined domain of applicability
• 4) appropriate measures of goodness-of–fit, robustness and predictivity
• 5) a mechanistic interpretation, if possible
A case study: (Q)SARs for mutagens and carcinogens
• Theory more advanced than in other toxicological fields (e.g., knowledge on action mechanisms)
• Suitable to show the different approaches to (Q)SAR
Chemical mutagens and carcinogens:background information
Mechanistic findings at the basis of the science and regulation of mutagens and carcinogens
• Millers’ electrophilic (DNA-) reactivity theory of carcinogenesis (not including nongenotoxic carcinogens)
• Chemical mutagenicity: Malling’s in vitro metabolic activation (S30, S9); Salmonella, or Ames’ test for DNA-reactive chemicals
• Structure-Activity (carcinogenicity) Relationships (Ashby’s Structural Alerts)
Mechanistic findings at the basis of the science and regulation of mutagens and carcinogens
• Because of the success of Millers’ electrophilic reactivity theory of carcinogenesis, and of Ames’ test:
major research efforts on the hypothesis Mutation = Cancer
• Later on, recognition of nongenotoxic carcinogens
Looking for further mutagenicity Short-Term Tests (STT) to predict carcinogenicity
• Hypothesis to cover the spectrum of cancer-relevant factors, use: different genetic endpoints (gene mutation, chromosomal damage), different cells (bacterial, mammalian), and animals (ADME)
• Development of > 100 STTs based on:
mutagenicity (e.g., gene mutation in mammalian cells, chromosomal aberrations, aneuploidy)
other genotoxic events (e.g., DNA damage)
STTs to predict carcinogenicity: state-of-the-art
• Mutagenicity = Carcinogenicity ? Only within a limited area of the chemical space, i.e., DNA-reactive
chemicals
• DNA-reactive chemicals induce cancer, and a wide spectrum of mutations
• Most predictive mutagenicity-based assay: Ames test
• Other in vitro assays (e.g., clastogenicity), when Ames-negative : no correlation with carcinogenicity
• No reliable in vivo STTs (e.g., micronucleus) available
Benigni R. et al., Exp.Opinion Drug Metab.Toxicol., 2010, 6: 1-11. Zeiger E Regulat.Pharmacol.Toxicol. 1998;28:85-95.
Ames test neg pos
Carcinogenicity
233 76 Non DNA-reactive 136 34
DNA-reactive 79 277
Results from 835 chemicals in ISSCAN v3a http://www.iss.it/ampp/dati/cont.php?id=233&lang=1&tipo=7
Ames test versus rodent carcinogenicity
Ames identifies DNA-reactive carcinogens
Non carcinogens
Carcinogens
Ames test neg pos
Carcinogenicity
233 76 Non DNA-reactive 136 34
DNA-reactive 79 277
Results from 835 chemicals in ISSCAN v3a http://www.iss.it/ampp/dati/cont.php?
id=233&lang=1&tipo=7
Ames test versus rodent carcinogenicity
Ames mutagen: 80% probability of being a carcinogen
Non carcinogens
Carcinogens
Backing up the mutagenicity STTs with Structure-Activity concepts
•To model / predict the Ames test
•To complement the Ames test
Structure-activity relationship concepts:
application to different issues, through different approaches
Coarse-grain Structure Alerts
Fine-tuned Quantitative Structure-Activity Relationships (QSAR)
Structure Alerts (SA)
Functional groups or Substructures
linked to
toxic (carcinogenic / mutagenic) effects of chemicals
Several Azo-dyes are carcinogenic
Butter yellow
• Food colorant
• Carcinogenic
NH2
N
N
(generation of aromatic amines)
Hydrophilic sulfonic acid groups generate water-soluble compounds
C.I. Food Black 1 (E 151)
• Safe colorant
• All split products are strongly hydrophilic C
NH
NN
N
N
OH
O- O
-
O-
O-
O
O
O O
O
OOO
O
S S
S
S
CH3
SA: Aromatic Diazo
Modulating factor: Hydrophilic sulfonic acid
The modulating factors diminish or abolish the SA effect
CNH
NN
N
N
OH
O- O
-
O-
O-
O
O
O O
O
OOO
O
S S
S
S
CH3
C.I. Food Black 1 (E 151)
Mechanistic findings at the basis of the science and regulation of mutagens and carcinogens
• Millers’ electrophilic reactivity theory of carcinogenesis
• Ames’ test, in vitro model of the carcinogenicity mechanisms
• Ashby’s theoretical model of carcinogenicity (compilation of Structural Alerts)
2
O
NN
N N
CH3
CH3
CH3 N
N
O
CH2 CH CH2
CH2
O
CO NH2
O
NH2
CH2Cl
CH
NH
CH CH2 CH
CH
CH2 CH
CH2
N Cl
NCH2
CH2
Cl
CHCH2
OC
O
CH CH Cl
N
CH2
OH
CH2
CH
CH ONH
N
CH3
CH3
CH2
S OO
OCH3
NO
CH2
CH2
Cl
Ashby’s
Poly-carcinogen
Ashby (1995) Environ.Mutag. 7: 919-921
Some alerts accompanied by detoxifying (modulating) factors
2
O
NN
N N
CH3
CH3
CH3 N
N
O
CH2 CH CH2
CH2
O
CO NH2
O
NH2
CH2Cl
CH
NH
CH CH2 CH
CH
CH2 CH
CH2
N Cl
NCH2
CH2
Cl
CHCH2
OC
O
CH CH Cl
N
CH2
OH
CH2
CH
CH ONH
N
CH3
CH3
CH2
S OO
OCH3
NO
CH2
CH2
Cl
J Ashby and Tennant R W (1988) Mutat Res 204:17-115
Further elaboration for, e.g., :
• Aromatic amino, substituted amino
• Aromatic nitro
• Aromatic –NR2
• Chlorinated olefins
• PAH
etc…
Ashby J (1978) Cancer 37:904-923
SA: chemical class that provokes toxic effects through one or few
shared mechanisms of action
direct-acting carcinogens: e.g., epoxides, aziridines, sulfur and
nitrogen mustards, α-haloethers, and lactones
C C
O
C C+
O- DNA
Strained ring Carbonium ion Alkylation
Metabolically activated carcinogens: e.g., aromatic amines
Ac
N
Ac
OAc
N
H
O SO3
N
Ac
O
N
H
Ac
N
OH
Ac
Acetyl CoA
Cytochrome P450s
Trans-acetylases
Electrophilic metabolites
Covalent binding to DNA
Toxic effect (mutation and/or cancer)
NH
OH
NH2
SA: chemical class that provokes toxic effects through one or few
shared mechanisms of action
SA: chemical class that provokes toxic effects through one or few
shared mechanisms of action
complex carcinogens: e.g., aliphatic halogens
From genotoxic to epigenetic, with increasing degree of halogenation and depending on the carbon skeleton
Short-chain monohalogenated alkanes (and alkenes) direct-acting alkylating agents;
Dihalogenated alkanes: alkylating or cross-linking agents.
Polyhaloalkanes: by free radical or nongenotoxic mechanisms, or reductive dehalogenation to yield haloalkenes.
Halogenated cycloalkanes (and cycloalkenes): possibly epigenetic or direct alkylation after metabolic transformation
Toxtree: Rulebase for mutagens / carcinogens
Structure-based approach consisting of:
-New compilation of Structure Alerts (genotox (DNA-reactive) and non-genotox)
-Three mechanistically-based QSARs for congeneric classes (aromatic amines, aldehydes)
Expert system Toxtree (version 1.6)
Open-source, freely available: http://ecb.jrc.it/qsar/qsar-tools/index.php?c=TOXTREE
Primary aromatic amine
Frequency (%)
0 5 10 15 20 25 30 35
Various alkylating
Epoxides and aziridines
Aliphatic halogens
Simple aldehyde
Quinones
Hydrazines
Aliphatic azo and azoxy
Isocyanate and isothiocyanate groups
Alkyl carbamate and thiocarbamate
Polycyclic Aromatic Hydrocarbons
Alkyl and aryl N-nitroso groups
Aliphatic N-nitro group
Aromatic nitroso
Nitro-aromatic
Aromatic amines
Coumarins and Furocoumarins
Non genotoxic SAs
NoSAs
Profile of the Kirkland’s database on carcinogens
Toxtree 2.5 update:
more rulebases
Many Toxtree rulebases
included in the
OECD (Q)SAR Toolbox
Checking the agreement between
SAs and experimental results
A chemical with a SA (with no modulating factors)
is predicted as potentially toxic
ROC graph
False Positive rate
0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0
Tru
e P
ositi
ve R
ate
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1.0
Perfect
Random
Horrible
Perfect
Random
Horrible
ROC graph: A simple, graphical way of comparing predictions with results
True positive rate = (Positives predicted as positive) / (Real positives)
= Sensitivity
False Positive Rate = (Negatives predicted as positive) / (Real negatives)
= 1 - Specificity
False positive rate
True positive rate
Toxtree SAs: agreement with Carcinogenicity and Salmonella (Ames)
ISSCAN v3a database
SAs identify Ames-mutagens with 80% accuracy, comparable to inter-laboratory variability (80-85%)
Perfect
Random
All wrongs
False Positive Rate
0.0 0.2 0.4 0.6 0.8 1.0
Tru
e P
ositi
ve R
ate
0.0
0.2
0.4
0.6
0.8
1.0
STY
SA_BB & STY
SA_BB
Carcinogenicity prediction: Salmonella (Ames) versus SAs
SAL + SAs
SAs
SAL
ISSCAN v3a database
Salmonella and SAs identify genotoxic
(DNA-reactive) carcinogens with similar accuracy,
and are not complementary to each other
Knowledge on DNA-reactivity (coded in SAs):
• Reliable enough to predict Salmonella results, and identify many carcinogens
• Identify human carcinogens
• Basis for successful priority setting in NTP bioassays (70% carcinogens among structurally suspect chemicals, only 10% among high exposure chemicals)
• Contribution to reduce DNA-reactive carcinogens among synthetic chemicals (pesticides, pharmaceuticals)
Success story: priority setting by human experts
Out of 400 chemicals tested by NCI/NTP:
• 2/3 selected as suspect carcinogens (n=267)
68% carcinogenic (n=187)
• 1/3 selected on production/exposure considerations (n=133)
20% carcinogenic (n=26); 6.8% positive in two species (n=9)
Fung, Barrett, and Huff (1995) Environ.Health Perspect. 103: 680-683
Which use for the Structure Alerts ?
Which use for the Structure Alerts ?
Great tool for coarse-grain characterization of the chemicals:
• Description of sets of chemicals
• Preliminary hazard characterization
• Category formation (e.g., regulation, fine-tuned QSAR, etc…)
• Priority setting (enriching the target)