Development of the Fathead Minnow Narcosis Toxicity Data Base

Transcription

1 Development of the Fathead Minnow Narcosis Toxicity Data Base Larry Brooke 1, Gilman Veith 2, Daniel Call 3, Dianne Geiger 1, and Christine Russom 4 Log 1 96-hr LC 5 (mol/l) Log LC 5 = -1.9 log log ( ) -.79 R 2 =.9986; n = 1 Bilinear Relationship Model for Narcosis I MA (from Veith et al. 1983) Log Water Solubility (mol/l) 1 University of Wisconsin-Superior, 2 QSAR foundation, 3 University of Dubuque, and 4 U.S. EA Mid-Continent Ecology Laboratory Log 1 1

2 Narcosis I Chemicals (Acute Toxicity with Fathead Minnow) Acute Toxicity to Fathead Minnow with Narcosis I & II Chemicals Log 1 LC 5 (moles/l) -2-4 Log 1 LC 5 (moles/l) -2-4 Narcosis I (non-polar) Y = X r 2 =.8944; n = Y = X r 2 =.8944; n = 291 Where: Y = Log 1 LC 5 and X = Log 1-6 Narcosis II (olar) Y = X r 2 =.5599; n = Log 1 Where: Y = Log 1 LC 5 (moles/l) and X = Log Log 1 2

3 Toxicity to Fathead Minnow of Narcosis I, II, and III Chemicals (From the U.S. EA Data Base) 1 Nonpolar Narcotic Chemicals (from Schultz et al. 1998) Log 1 LC 5 (moles/l) -2-4 Log 1 LC 5 (moles/l) Tetrahymena pyriformis Y = X; r 2 =.9442 n = Y = X r 2 =.8559; n = 351 Where: Y = Log1 LC5 (moles/l) and X = Log1-5 imephales promelas Y = X; r 2 =.9569 n = Log Log 3

4 Log 1 LC 5 (moles/l) Nonpolar Narcotic Chemicals (from Schultz et al and U.S. EA) Fathead minnow Tetrahymena pyriformis Log 1 LC 5 or MATC (moles/l) Fathead Minnow Acute and Chronic Toxicity with Narcosis Chemicals Chronic MATC Y = X r 2 =.7576; n = 3 Where: Y= Log 1 LC 5 (moles/l) and X = Log 1 Acute Toxicity Y = X r 2 =.8944; n = Log Log 1 4

5 Applying redictive Data Mining to redictive Toxicology From Narcosis to McKim Conference Chihae Yang 28th June, 26 5

6 Acknowledgment From Meyer-vertone to McKim Conference Gilman Veith, International QSAR Foundation J.F. Rathman, The hio State University Leadscope team hio Technology Action Fund Narcosis toxicity of neutral organics is related to their ability to partition between water and a lipophilic biphase where molecules exert their activity Model system for partition: olive oil/water. Evolution Narcosis Non-polar and polar narcosis Reactivity 6

7 aradigm shift How do we strategically leverage? redictive data mining strategies structural descriptions analogs In silico In vitro In vivo mics How do we read across the species, endpoints, structural classes, different knowledge domains? chemical stressor profile biological/environmental fate Yang, C.; Richard, A.M., Cross, K.. Current Computer-Aided Drug Design, 26, 2,

8 Steps in predictive data mining Data mining analysis methods Focused Data Sets Visualization Analysis Searching latform Structure, data, graphs, models SAR & QSAR rofiling Grouping Hypothesis driven queries Analog searching Read across Chemistry Biology integration Knowledge addition Relational database Compound grouping Analysis rediction Classification attern Recognition rofiling QSAR Classification Rule Extraction Clustering Expert Grouping Large diverse Data Sets 8

9 Applying to predictive tox redictive data mining examples rofiling chem-bio domain Cut across different knowledge domains Find hidden signals and relationships from data Qualify/quantify read-across Complementary to (Q)SAR Build hypothesis driven models Go beyond Yes/No question and answer Biological profile Relationships between fish narcosis and toxicological findings in rat inhalation studies? Fathead minnow EA dataset Rat acute toxicity dataset from RTECS Thermodynamics consideration 9

10 Theoretical bases: Vapor-liquid equilibrium Study sources for rat and FHM correlations Non-ideal Raoult s law: - The equilibrium distribution between liquid and vapor phases for a chemical species i v γ x p = y = partial pressure i i i i i single dose inhalation chamber RTECS dose unit (mg/ml) defined LD rat exposure time 2-8 hours - narcosis EA FHM 617 γ i : activity coefficient x i : mole fraction of i in the liquid phase p iv : vapor pressure of pure liquid i at the same temperature T y i : mole fraction in the vapor phase. 179 LC5 at 96 hr 1

11 rofiling examples Representing structures with Leadscope molecular descriptors Structures Liver Lung UBL GI plc5 Benzenes Ak Rat FHM N present present Functional groups N H present present present present Heterocycles harmacophores Spacers N Any N CC HBA N H N N CC NH 2 H User defined features 11

12 Read-across using structural descriptors profiles of rat organ lesions LC5 FHM Structural descriptors Benzenes 1,2-subst 1,3-subst 1,4-subst % structures liver ubl lung GI.6.7 plc5 FHM Rat Structural descriptors alcohol aldehyde amines carbonyl ether halide ketone alcohol, p-alkyl- alcohol, aryl- ether, alkyl- halide, aryl structural descriptors were selected. 12

13 Liver GI Lung Kidney Liver Lung plc5fhm Liver Liver plc5rat plc5fhm plc5fhm Kidney kidney ubl earson correlations Quantitative read-across Lung GI plc5 Rat plc5 FHM From a surface scientist point of view assive diffusion through lipid bilayer Headgroup interaction Hydrophobic tail interaction Hydrophilic to lipophilic balance (HLB) artition model of molecules in lipid layer : bulk ( species i ) ( species i ) bulk lipid ( i ) = ( i ) activity activity at equilibrium γ x partition coefficient: = γ bulk bulk lipid lipid i i i i K x lipid x i = x γ i γ lipid bulk x bulk lipid i i γ : activity coefficient 13

14 UNIFAC activity coefficient model combinatorial term molecular volume and surface area effects (size, shape, packing) lnγ = lnγ C + lnγ R i i i residual term intermolecular energy effects (interaction) Advantages of UNIFAC model Group contribution method Molecular descriptors-based activity coefficients Flexibility to vary liquid phases compositions octanol/water octanol-water solution/water hexadecane/water lipid/water etc. The properties of Gases & Liquids, 4 th ed., R. Reid, J. rausnitz, B. oling, McGraw Hill,

15 Example: Lipid as a solvent phase Example of activity coefficients in various environment N Solvent Water Log 1 γ 5.23 ctanol.5 H Lipid tail Lipid head Hexadecane Activity coefficients at infinite dilution can be used to model solubility in various phases. 15

16 Reflection measured Log earson correlations against measured Log Log(o/w) Log(ow/w) Log(h/w) Log(dppc/w) Log (ow/w) Log (o/w) Log (h/w) Log (dppc/w) We re committed to nothing less than a point-forpoint transcript of everything there is. nly one problem: the index is harder to use than the book. We ll live to see the day when retrieving from the catalog becomes more difficult than extracting from the world that catalog condenses. The gold bug variations, Richard owers, 24 16

17 Distribution of LC5s for FHM and rats plc5 of FHM pld5 of rats Mean:.669 Mean: 1.52 Log 1 LC 5 (moles/l) LC5 vs Log Solubility vs Log Narcosis I Chemicals Acute Toxicity with Fathead Minnow and Water Solubility of Chemical Log 1 Water Solubility (moles/l) 17