Introduction to OECD QSAR Toolbox

Introduction to QSARWelcome to this online introduction of QSAR

which gives a basic understanding of QSAR and why a QSAR Toolbox is needed

Risk assessments are based on test data, and QSAR is not needed if you have lot’s of data

However, if data gaps exist, one can defer the hazard assessment or use QSAR

Introduction

Fewer than 10,000 chemicals have been tested for the major hazards

The world inventory of produced chemicals exceeds 160,000 chemicals

The world capacity for SIDS initial hazard assessments is only ~500 chemicals/year

IntroductionTherefore, even initial assessments based on

test ing discrete chemicals is not possible for most chemicals

Also, priority setting for 130,000 chemicals will require faster testing or better models

In QSAR, estimating behavior of untested chemicals has been used for >60 years

An Overview of QSARChemistry is based on the premise that similar

chemicals will behave similarly

Like most systems, the behavior of a chemical is derived from its structure

Chemical behavior in biological systems is described as biological activity of chemicals

An Overview of QSAR

QSAR research searches for relationships between chemical structure and activity

QSAR is the acronym for Quantitative Structure-Activity Relationship

log LC50 (rat, 4hr) = 0.69 log VP + 1.54 is an example of QSAR for lethality in rats

An Overview of QSAR

Here, “VP” is the vapor pressure which is measured or estimated from the structure

There are more than 15,000 published QSARs for biological activity endpoints

The term “quantitative” most often pertains to the statistical quality of the “relationship”

An Overview of QSARQSARs are always associated with endpoint

( i.e.LC50) and an toxicity mechanism (i.e. narcosis, AChE inhib)

Only chemicals causing common toxicity mechanisms lead to a reliable QSAR

Therefore, QSAR must group chemical behavior in terms of toxicity mechanisms

Overview ConclusionsQSAR predicts biological activity (endpoints)

directly from models of chemical structure

Each QSAR predicts a specific endpoint and only for chemicals with the same mechanism

Errors of choosing the wrong QSAR (mechanism) are larger than model errors

Process for Creating QSAR 1. Choose a well-defined endpoint for biological

activity needed in your work2. Compile measured values using consistent

methods for the endpoint --OR3. Select a series of relevant chemicals and

systematically test all for the endpoint4. Identify “molecular descriptors” which

quantify structural attributes for endpoint5. Statistically evaluate the molecular

descriptor-- endpoint relationships (QSAR)

Example for Lethality in Mice

• Compile data for 30-minute lethality with mice from the anesthesiology literature

• Data restricted to alkyl ethers to increase likelihood of a similar toxicity mechanism

• Estimate or measure vapor pressure as molecular descriptor (selected from theory or by trial-n-error)

• Correlate LC50 with VP to get: log LC50 = 0.57 x log VP + 2.08

Table 1. LC50-30 min of aliphatic ethers in mice

Chemical name CAS MWVP

(mmHg)LC50

(mmol/m3)

Diisobutyl ether 628-55-7 130.2 15 1200

Disec-butyl ether 6863-58-7 130.2 17 1000

Diethyl ether 60-29-7 74.1 537 6000

Diisopropyl ether 108-20-3 102.2 170 1500

Dimethyl ether 115-10-6 46.1 4450 37000

Dipropyl ether 111-43-3 102.2 60 1600

Divinyl ether 109-93-3 70.1 684 4700

Ethyl amyl ether 17952-11-3 116.2 18 1000

Ethyl butyl ether 628-81-9 102.2 52 1500

Ethyl cyclopropyl ether 5614-38-0 86.1 150 1000

Ethyl isoamyl ether 628-04-6 116.2 30 1000

Ethyl isobutyl ether 627-02-1 102.2 98 1500

Ethyl isopropyl ether 625-54-7 88.1 250 2500

Ethyl propyl ether 628-32-0 88.1 185 2500

Ethyl- sec-butyl ether 2679-87-0 102.2 98 1400

Ethyl tert-amyl ether 919-94-8 116.2 43 700

Ethyl tert-butyl ether 637-92-3 102.2 155 1200

Ethyl vinyl ether 109-92-2 72.1 500 4500

Methyl amyl ether 628-80-8 102.2 55 1300

Methyl butyl ether 628-28-4 88.1 160 2000

Methyl cyclopropyl ether 540-47-6 72.1 410 1750

Methyl ethyl ether 540-67-0 60.1 1493 18000

Methyl isobutyl ether 625-44-5 88.1 210 1600

Methyl isopropyl ether 598-53-8 74.1 550 5500

Methyl propyl ether 557-17-5 74.1 500 3500

Methyl sec-butyl ether 6795-87-5 88.1 230 1600

Methyl tert-butyl ether 1634-04-4 88.1 244 1600Propyl isopropyl ether 627-08-7 102.2 85 1500

Example• Notice the dependence on VP (slope) is

almost the same as with the rat QSAR

• Notice the intercept is about 0.5 log units greater for 30 min mouse vs 4 hr rat LC50

• Can you suggest reasons for the greater LC50 (lower toxicity) for 30 min mouse ?

Some Important Lessons• Vapor pressure correlates with LC50, but

many molecular descriptors would not correlate

• This QSAR implies vapor pressure is important to the lethality mechanism for these chemicals

• Chemicals with other mechanisms (i.e. acrolein, phosgene) will appear as statistical outliers

• QSAR provides insights into chemical similarity in terms of common “effect” mechanisms

Some Important Lessons• QSAR is an exploration of chemical

attributes which reliably predicts their biological activity (biological effects) under specific test conditions

• QSAR is also a tool to group chemicals which can be expected to behave similarity (same toxicity pathway under specific test conditions

The Chemical Category Solution• Grouping chemicals by similar behavior

extrapolates from tested to untested chemicals within a given chemical category

• Entire categories of chemicals can be assessed when only a few are tested

• Filling missing data (gaps) involves read-across & trend or correlation analysis

What do we mean by Chemical Categories?A group of chemicals that have some features

that are commonStructurally similar e.g. common substructureProperty e.g. similar physicochemical,

topological, geometrical, or surface propertiesBehaviour e.g. (eco)toxicological response

underpinned by common modes of actionFunctionality e.g. preservatives, flavourings,

detergents, fragrances

Substances whose physicochemical, toxicological and ecotoxicological properties are likely to be similar or follow a regular pattern as a result of structural similarity may be considered as a group, or “category” of substances.

Application of the group concept requires that physicochemical properties, human health effects and environmental effects or environmental fate may be predicted from data for a reference substance within the group by interpolation to other substances in the group (read-across approach). This avoids the need to test every substance for every endpoint.

Annex IX of REACH

OECD Definition of Category

• A chemical category is a group of chemicals whose

physicochemical and toxicological properties are likely to

be similar or follow a regular pattern as a result of

structural similarity

• These structural similarities may create a predictable

pattern in any or all of the following parameters:

physicochemical properties, environmental fate and

environmental effects, and human health effects

OECD Manual for Investigation of High Production Volume (HPV) Chemicals.

Forming Chemical CategoriesChemical categories have boundary

conditions which vary with endpoints

Without detailed understanding of metabolism or mechanisms, grouping similarity of behavior is difficult to define.

Ironically, examining data trends with different category boundaries is a flexible way to define categories

Canonical Ordering

ChemicalAmyl amineAmyl chlorideDibromobenzeneEthyl bromiden-HeptanolMethacroleinMethyl-p-anisylketonen-Octanen-Nonane

Boiling Point °C103-498-9219-238.419268267-9126151

Canonical Ordering

ChemicalEthyl bromideMethacroleinAmyl chlorideAmyl aminen-Octanen-Nonanen-HeptanolDibromobenzeneMethyl-p-anisylketone

Boiling Point °C38.46898-9103-4126151192219-2267-9

1 2 3 4 5 N < 10,000…....

1/LC50(Moles/L)

TOXICITY “MECHANISMS”

10-8

10_4

10_2

10+2

10 0

10_6

Modeling Chemical Potency

It is not uncommon to find endpointvalues spanning 6-10 orders for a single toxicity mechanism

0 2 4 6 8

1/LC50(ChemicalActivity)

LOG K o/w

10-8

10_4

10_2

10+2

10 0

10_6

Modeling Chemical Potency

QSAR Methods

QSAR fills data gaps by first grouping chemicals and then using existing data within a group to estimate missing values

When the chemical group is identified by a common mechanism, QSAR models can accurately describe the trends

Why Do We Need the QSAR Toolbox

Defining category boundaries requires the calculation of complex attributes of chemicals to determine which best explains available data

In many cases, metabolic simulators are needed to provide metabolic maps and active metabolites

To do trend analysis, hundreds of available data must be compiled and flexibly analyzed for trends

Simulated 2-Acetylaminofluorene

Metabolism

NH

O

NH

O

OH

NH

O

O

NH2

O

HO

O

NHOH

O

N+HO

NH

OHO

NH

O

O

NH

O

O

NH

OHO

NH

OHO

OHNH

OHO

OH

NH

OHO

O

NH

OHO

O

N+H

HO

ON+H

OH

O

. . . . . .

NHX

OO

X = H, OH,

O

Activated metabolites

Which Metabolite should we use in modeling interactions?

MolecularInitiating Event

Speciation,MetabolismReactivityEtc.

In Vitro and System Effects

In VivoAdverse Outcomes

ParentChemical

Adverse Outcome Pathway ForA Well-Defined Endpoint

Up-Stream Down-Stream CHEMISTRY BIOLOGY Structure-Activity Levels of Organization

Chemical Reactivity Profiles

Receptor, DNA,ProteinInteractions

Mechanistic Profiling

Biological Responses

The Adverse Outcome Pathway

ToxicantMacro-Molecular Interactions

Molecular Initiating Event

NRC Toxicological Pathway






Macro-Molecular Interactions Gene

Activation

Protein Production

Signal Alteration

CellularToxicant

AlteredFunction

Altered Development

Gene Activation

Protein Production

Signal Alteration

Cellular


In Vitro &HTP Screening






Macro-Molecular Interactions

Tissue/ OrganToxicant

Lethality

Sensitization

Birth Defect

Reproductive Impairment

Cancer

AlteredFunction

Altered Development

Gene Activation

Protein Production

Signal Alteration



Structure

Extinction

Cellular Organ


In VivoTesting



Toxicant OrganismMacro-Molecular Interactions


Population

In Vitro &HTP Screening

Major Pathways for Reactive Toxicity from Moderate Electrophiles

Systemic Responses

SkinLiverLung

MichaelAddition

Schiff baseFormation

SN2

Acylation

AtomCentered

Irreversible(Covalent)Binding

InteractionMechanisms

MolecularInitiatingEvents Exposed

SurfaceIrritation

SystemicImmune

Responses

NecrosisWhich

Tissues?

In vivoEndpoints

Pr-S AdductsGSH OxidationGSH DepletionNH2 AdductsRN AdductsDNA Adducts

Oxidative Stress

Dose-Dependent Effects

Organization for Economic Co-operation and Development

QSAR Application Toolbox-filling data gaps using available information-

Training WorkshopBarcelona

• First “organized” discussions – ‘Red Lobsters’, Duluth - 1992

Historical Notes

• Organized actions of EU and OECD – coming with REACH

• The role of the “revolutionary” notions – category, analogues

• OECD and EU Guidance documents on ‘Category’, ‘QSAR’

• Need for translation documents into a working machinery

QSAR Application ToolboxOrganization for Economic Co-operation and Development

-filling data gaps using available information-

QSAR Application ToolboxOrganization for Economic Co-operation and Development

Improve accessibility of (Q)SAR methods and databases

Facilitate selection of chemical analogues and categories

Integrate metabolism/mechanisms with categories/(Q)SAR

Assist in the estimation of missing values for chemicals

-ENV/JM(2006)47

-filling data gaps using available information-

General Objectives

Typical queries included in the (Q)SAR Application Toolbox

Is the chemical included in regulatory inventories or existing chemical categories?

Has the chemical already been assessed by other agencies/organisations?

Would you like to search for available data on assessment endpoints for each chemical?

Explore a chemical list for possible analogues using predefined, mechanistic, empiric and custom built categorization schemes?

Group chemicals based on common chemical/toxic mechanism and/or metabolism?

Design a data matrix of a chemical category?

Typical Queries included in the

(Q)SAR Application Toolbox

QSAR Toolbox Workflow

The workflow in the first version of the QSAR Toolbox is to facilitate hazard assessors in the creating of chemical categories which enable data to be extrapolated from tested chemicals to untested members of categories

Chemicalinput

Profiling CategoryDefinition

Fillingdata gap

ReportEndpoints

Logical sequence of components usage

User Alternatives for Chemical ID:A. Single target chemical• Name• CAS# • SMILES/InChi• Draw Chemical Structure• Select from User List/InventoryB. Group of chemicals• User List• Inventory• Specialized Databases

Chemicalinput


Fillingdata gap

ReportEndpoints


General characterization by the following grouping schemes:• Substance information• Predefined• Mechanistic• Empirical• Custom• Metabolism

Chemicalinput


Fillingdata gap

ReportEndpoints


General characterization by the following grouping schemes:• Substance information• Predefined:

• US EPA categorization• OECD categorization• Database affiliation • Inventory affiliation• Substance type: polymers, mixtures, discrete, hydrolyzing

Chemicalinput


Fillingdata gap

ReportEndpoints


Chemicalinput


Fillingdata gap

Report

Finding Data for SIDS and Other Endpoints• Selecting Data Base(s):

Toolbox databases Publicly available Proprietary databases

Toolbox Links to External Databases (DSSTOX)

• Selecting type of extracting data: Measured Data Estimated Data Both

Endpoints


Forming and Pruning Categories:• Predefined• Mechanistic• Empirical• Custom• Metabolism

Chemicalinput


Fillingdata gap

ReportEndpoints


Forming and Pruning Categories:

• Predefined• OECD categorization• US EPA categorization• Inventory affiliation• Database affiliation• Substance type

Chemicalinput


Fillingdata gap

ReportEndpoints


Data gaps filling approaches• Read-across• Trend analysis• QSAR models

Chemicalinput


Fillingdata gap

ReportEndpoints


Report the results:• QMRF/QPRF• IUCLID 5 Harmonized Templates• SIDS Dossiers (Data matrix)• History of the Toolbox Application• User-Defined Reports• Documentation:

• Description of the system• Description of Category Editor

Chemicalinput


Fillingdata gap

ReportEndpoints


Introduction to OECD QSAR Toolbox

Technology

Transcript of Introduction to OECD QSAR Toolbox