Organization for Economic Co-operation and Development QSAR Application Toolbox -filling data gaps using available information- McKim Conference, September 2007, Duluth, MN QSAR Application Toolbox Organization for Economic Co-operation and Development First organized discussions Red Lobsters, Duluth filling data gaps using available information- 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 Toolbox Organization 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 Bob Diderich Gilman Veith Terry Schultz Take Fukushima Environment Directorate OECD Paris Special thanks to: DG Environment European Chemicals Bureau Danish Ministry of the Environment US EPA Environment Canada NITE Japan CEFIC MultiCase (USA) SRC (USA) A collaborative effort of all member countries and stakeholders Developers of the system: Laboratory of Mathematical Chemistry, Bourgas, Bulgaria 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 Fill data gaps in a chemical category using: read-across, trend analysis or QSAR models Report the results: Work history Export the data matrix IUCLID 5 harmonized templates Typical Queries included in the (Q)SAR Application Toolbox System Workflow Chemical input ProfilingCategory Definition Filling data 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/Inventory B. Group of chemicals User List Inventory Specialized Databases Chemical input ProfilingCategory Definition Filling data gap ReportEndpoints Logical sequence of components usage Presentation of species according to their taxonomic rank Consistency between CAS and structure across inventories and databases User Alternatives for Chemical ID: A. Single target chemical Name CAS# SMILES/InChi Draw Chemical Structure Select from User List/Inventory B. Group of chemicals User List/Inventory Specialized Databases Chemical input ProfilingCategory Definition Filling data gap ReportEndpoints Logical sequence of components usage Toolbox Inventories: US EPA TSCA Canadian DSL OECD HPVCs, US EPA HPVCs EU EINECS Japanese MITI DANISH EPA General characterization by the following grouping schemes: Substance information Predefined Mechanistic Empirical Custom Metabolism Chemical input ProfilingCategory Definition Filling data gap ReportEndpoints Logical sequence of components usage General characterization by the following grouping schemes: Substance information: CAS Name Structural formula OECD Global portal Chemical input ProfilingCategory Definition Filling data gap ReportEndpoints Logical sequence of components usage 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 Chemical input ProfilingCategory Definition Filling data gap ReportEndpoints Logical sequence of components usage 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 Chemical input ProfilingCategory Definition Filling data gap ReportEndpoints Logical sequence of components usage General characterization by the following grouping schemes: Substance information Predefined Mechanistic: Acute Toxicity MOA Protein binding (OASIS) DNA binding (OASIS) Electron reach fragments (Superfragments) BioBite Cramer Classification Tree (ToxTree) Veerhar/Hermens reactivity rules (ToxTree) Lipinski rules (MultiCase) Chemical input ProfilingCategory Definition Filling data gap ReportEndpoints Logical sequence of components usage General characterization by the following grouping schemes: Substance information Predefined Mechanistic: Acute Toxicity MOA (OASIS) Protein binding (OASIS) DNA binding (OASIS) Electron reach fragments (Superfragments) BioBite Cramer Classification Tree (ToxTree) Veerhar/Hermens reactivity rules (ToxTree) Lipinski rules (MultiCase) Chemical input ProfilingCategory Definition Filling data gap ReportEndpoints Logical sequence of components usage General characterization by the following grouping schemes: Substance information Predefined Mechanistic Empirical: Chemical elements Groups of elements Natural functional groups AIM (EPA/SRC) Chemical input ProfilingCategory Definition Filling data gap ReportEndpoints Logical sequence of components usage General characterization by the following grouping schemes: Substance information Predefined Mechanistic Empirical Custom: Mechanistic boundaries example (aldehydes forming Shiff base but not Michael type addition) Chemical input ProfilingCategory Definition Filling data gap ReportEndpoints Logical sequence of components usage General characterization by the following grouping schemes: Substance information Predefined Mechanistic Empirical Custom Metabolism: Documented: microbial, liver Simulated: microbial, liver, GI tract, skin Chemical input ProfilingCategory Definition Filling data gap ReportEndpoints Logical sequence of components usage Chemical input ProfilingCategory Definition Filling data 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 Logical sequence of components usage Chemical input ProfilingCategory Definition Filling data gap Report Extracting SIDS and Other Endpoints Selecting Data Base(s): Internal databases Publicly available Proprietary databases Toolbox Links to External Databases (DSSTOX) Selecting type of extracting data: Measured Data Estimated Data Both Endpoints Logical sequence of components usage Measured data summary of the Current Toolbox 1.Biodegradation DB 745 chemicals 2.Genotox DB chemicals 3.ISSCAN Genotox 873 chemicals 4.Skin sensitization DB chemicals 5.Estrogen RBA chemicals 6.Bioaccumulation DB 700 chemicals 7.ECOTOX database 5071 chemicals 8.ECETOC database 777 chemicals Estimated Data Summary of the Current Toolbox 1. Danish EPA DB - data for chemicals Chemical input ProfilingCategory Definition Filling data 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 Logical sequence of components usage Chemical input ProfilingCategory Definition Filling data gap ReportEndpoints Logical sequence of components usage Categorization and QSAR Basic Concept Each QSAR estimate is a result of two predictions: Qualitative prediction of predominant interaction mechanisms and hazard identification (defined by category) Quantitative prediction of the intensity (potency) of the specific mechanisms of interaction (predicted by QSAR) Wrong selection of the mechanism could cause greater errors than the potency estimate by the QSAR model Example: Phenols are polar narcotics, uncouplers or electrophilic chemicals. QSAR models for each mechanism have comparable uncertainty The potency of the electrophilic mechanism can be orders of magnitude greater than polar narcotics Wrong categorization of chemicals could cause significant errors in defining the potency Categorization and QSAR Basic Concept The logic for selecting a specific model for a specific chemical (category) is the cornerstone of regulatory acceptance Categorization and QSAR Basic Concept OECD QSAR AD-Hoc group meeting,Madrid, April 2007 Forming and Pruning Categories: Predefined Mechanistic Empirical Custom Metabolism Chemical input ProfilingCategory Definition Filling data gap ReportEndpoints Logical sequence of components usage Forming and Pruning Categories: Predefined OECD categorization US EPA categorization Inventory affiliation Database affiliation Substance type Chemical input ProfilingCategory Definition Filling data gap ReportEndpoints Logical sequence of components usage Chemical input ProfilingCategory Definition Filling data gap ReportEndpoints Current categorization status of chemical inventories OECD CategoriesUS EPA Categories HPVCs 4843 substances Forming and Pruning Categories: Predefined Mechanistic Acute Toxicity MOA Protein binding DNA binding Electron reach fragments (Superfragments) Cramer Classification Tree Veerhar/Hermens reactivity rules Lipinski rules Chemical input ProfilingCategory Definition Filling data gap ReportEndpoints Logical sequence of components usage Example Target chemical: hexanal Target endpoint: Acute Toxicity to Fish Monoaldehydes: Formation of Schiff bases with amino groups [1-4] Aldehydes having ,-configuration with another - bond: Michael-type addition at carbon-carbon double bond [3-5] Aldehydes having halogen atoms at -position [3-5]: Nucleophilic substitution 1. Kamlet JJ, Doherty RM, Veith GD, Taft RW, Abraham MH Environ Sci Technol 20: Kamlet JJ, Doherty RM, Taft RW, Abraham MH, Veith GD, Abraham JD Environ Sci Technol 21: Lipnick, RL In Hermens JLM, Opperhuizer A, eds, QSAR in Environmental Toxicology IV. Elsevier, Amsterdam, The Netherlands, pp Karabunarliev S, Mekenyan OG, Karcher W, Russom CL, Bradbury SP Quant Struct-Act Relat 15: Hermens, JLM Electrophiles and Acute Toxicity to Fish, Environ Health Perspec 87: Logical sequence of components usage Chemical input ProfilingCategory Definition Filling data gap ReportEndpoints US EPA Aldehydes Schiff base formationMichael type addition Subcategory Mechanism US EPA Aldehydes acting by Schiff - base formation, only Existing categoryProtein binding category Forming and Pruning Categories: Predefined Mechanistic Empirical: Chemical elements Groups of elements Natural functional groups Structural similarity AIM (EPA/SRC) Chemical input ProfilingCategory Definition Filling data gap ReportEndpoints Logical sequence of components usage Forming and Pruning Categories: Predefined Mechanistic Empirical Custom: Mechanistic boundaries example (Shiff base but not Michael addition) Metabolism boundaries example (having specific fragment in parents and/or metabolites) Chemical input ProfilingCategory Definition Filling data gap ReportEndpoints Logical sequence of components usage Forming and Pruning Categories: Predefined Mechanistic Empirical Custom Metabolism Documented: microbial, liver Simulated: microbial, liver, GI tract, skin Chemical input ProfilingCategory Definition Filling data gap ReportEndpoints Logical sequence of components usage Use of Metabolism in Chemical Categories Identifying and pruning anomalous metabolism Subcategory formation based on common metabolites Category definition without metabolism Generate Metabolites Search for specific metabolites/pathways Revised Category pruning Logical sequence of components usage Chemical input ProfilingCategory Definition Filling data gap ReportEndpoints CAS # , Phenol,_2-ethoxy- US EPA Category: Phenols MW < 1000 log Kow < 7.4 Free radical protein adduct formation Michael-type nucleophilic addition Subcategory of phenols - binding with proteins after skin metabolism CAS # , Phenol,_2-ethoxy- US EPA Category: Phenols MW < 1000 log Kow < 7.4 Number of chemicals Nucleophilic substitution of haloalkanes Schiff base formation Nucleophilic substitution of cyclic dicarbonyls Michael-type nucleophilic addition Nucleophilic heterocycle ring opening Free radical protein adduct formation N-hydrohylamine condensation with proteins Nucleophilic addition to ketones Subcategory of phenols: - binding with proteins after skin metabolism 44 chemicals - not binding with proteins as parents or metabolites 83 chemicals Total number 127 chemicals US EPA Category: Phenols MW < 1000 log Kow < 7.4 Number of chemicals Nucleophilic substitution of haloalkanes Schiff base formation Nucleophilic substitution of cyclic dicarbonyls Michael- type nucleophilic addition Nucleophilic heterocycle ring opening Free radical protein adduct formation N- hydrohylamine condensation with proteins Nucleophilic addition to ketones Subcategory of phenols: - binding with proteins after skin metabolism 44 chemicals - not binding with proteins as parents or metabolites 83 chemicals Total number 127 chemicals US EPA Category: Phenols MW < 1000 log Kow < 7.4 Logical sequence of components usage Chemical input ProfilingCategory Definition Filling data gap ReportEndpoints Category formation Defining New Categories Category editor Defining New Categories: Setting boundaries: - Structural - Parametric - Mechanistic - Metabolic - Similarity Logical sequence of components usage Chemical input ProfilingCategory Definition Filling data gap ReportEndpoints Structural boundaries: - Presence of fragment - Absence of fragment Parametric boundaries: - MW < LogKow < 6.0 (for acute toxicity to fish and aquatic invertebrates) - LogKow < 6.4 (for toxicity to green algae) - LogKow < 8.0 (for chronic toxicity to aquatic organisms) Logical sequence of components usage Chemical input ProfilingCategory Definition Filling data gap ReportEndpoints Mechanistic boundaries: Logical sequence of components usage Chemical input ProfilingCategory Definition Filling data gap ReportEndpoints Yes Schiff base formation No Michael type addition No Nucleophilic substitution No Non binding with proteins Metabolic boundaries: OECD Category: Mono and Di methyltins Representatives: CAS # ; CAS # ; CAS # ; CAS # ; CAS # ; CAS # ; CAS # Subcategory: Monomethyltin chloride and selected esters Logical sequence of components usage Chemical input ProfilingCategory Definition Filling data gap ReportEndpoints Common metabolite after gastric metabolism Simulated gastric metabolism of MMT(2-EHMA)/(IOMA) R1 = CH(CH2CH3)CH2CH2CH2CH3 . MMT(2-EHMA) R2 = CH2CH2CH2CH2CH(CH3)CH3 MMT(IOMA) Common metabolite Data gaps filling approaches Read-across Trend analysis QSAR models Chemical input ProfilingCategory Definition Filling data gap Report Endpoints Logical sequence of components usage Data gaps filling approaches Read-across Trend analysis QSAR models Chemical input ProfilingCategory Definition Filling data gap Report Endpoints Logical sequence of components usage TetrahymenaPyriformis LC50, 96 h Example Target chemical: hexanal Target endpoint: Acute Toxicity to Ciliate Example Target chemical: hexanal Target endpoint: Acute Toxicity to Ciliate Subcategory: Based on Interaction Mechanism Aldehydes having ,-configuration with another -bond Michael-type addition at carbon-carbon double bond Monoaldehydes Formation of Schiff bases with amino groups Example Target chemical: hexanal Target endpoint: Acute Toxicity to Ciliate Monoaldehydes Formation of Schiff bases with amino groups Subcategory: Based on Interaction Mechanism Target chemicals is interacting by Schiff base formation mechanism 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 Chemical input ProfilingCategory Definition Filling data gap ReportEndpoints Logical sequence of components usage