In Silico Toxicology Principles and Applications Edited by Mark T. D. Cronin and Judith C. Madden Liverpool John Moores University, Liverpool, UK RSC Publishing
Contents Chapter 1 In Silico Toxicology An Introduction 1 M. T. D. Cronin and J. C. Madden 1.1 Introduction 1 1.2 Factors that Have Impacted on In Silico Toxicology: the Current State-of-the-Art 3 1.3 Types of In Silico Models 8 1.4 Uses of In Silico Models 8 1.5 How to Use this Book 8 1.6 Acknowledgements 9 References 9 Chapter 2 Introduction to QSAR and Other In Silico Methods to Predict Toxicity 11 J. C. Madden 2.1 Introduction 11 2.2 Building an In Silico Model 15 2.3 Assessing the Validity of the Model 23 2.4 Reviewing and Updating the Model 25 2.5 Using the Model 26 2.6 Consideration of Mitigating Factors 26 2.7 Documenting the Process 27 2.8 Pitfalls in Generating and Using QSAR Models 28 2.9 Conclusions 28 2.10 Acknowledgements 29 References 29 Issues in Toxicology No.7 In Silico Toxicology: Principles and Applications Edited by Mark T. D. Cronin and Judith C. Madden The Royal Society of Chemistry 2010 Published by the Royal Society of Chemistry, www.rsc.org
Chapter 3 Finding the Data to Develop and Evaluate (Q)SARs and Populate Categories for Toxicity Prediction 31 M. T. D. Cronin 3.1 Introduction 31 3.2 Which Data Can be Used for In Silico Modelling? 31 3.3 Uses of Data 32 3.4 How Many Data are Required? 33 3.5 Sources of Data 35 3.6 Retrieving Publicly Available Toxicity Data and Information for In Silico Modelling 37 3.7 Ongoing Data Compilation Activities 48 3.8 Ensuring Success in Using Toxicity Data in In Silico Models: Hierarchy of Data Consistency and Quality 50 3.9 Case Studies 51 3.10 Conclusions and Recommendations 55 3.11 Acknowledgements 56 References 56 Chapter 4 Data Quality Assessment for In Silico Methods: A Survey of Approaches and Needs 59 M. Nendza, T. Aldenberg, E. Benfenati, R. Benigni, M.T.D. Cronin, S. Escher, A. Fernandez, S. Gabbert, F. Giralt, M. Hewitt, M. Hrovat, S. Jeram, D. Kroese, J. C. Madden, I. Mangelsdorf, R. Rallo, A. Roncaglioni, E. Rorije, H. Segner, B. Simon-Hettich and T. Vermeire 4.1 Introduction 59 4.2 Principles of Data Quality Assessment 60 4.3 Biological Data Variability 74 4.4 Checklist Approach 75 4.5 Endpoint-Specific Considerations of Inherent Data Variability 77 4.6 Integration of Data with Distinct Degrees of Reliability 96 4.7 Cost-Effectiveness Analysis of Tests and Testing Systems 108 4.8 Acknowledgements 111 References 111 Chapter 5 Calculation of Physico-Chemical and Environmental Fate Properties 118 T. H. Webb and L. A. Morlacci 5.1 Introduction 118 5.2 Getting the Most Out of Estimation Methods 119
5.3 Selected Software for the Estimation of Physico-Chemical and Environmental Fate Properties 122 5.4 Physico-Chemical Property Estimations 124 5.5 Environmental Fate Properties 136 5.6 Conclusions 143 References 144 Chapter 6 Molecular Descriptors from Two-Dimensional Chemical Structure 148 U. Maran, S. Sild, I. Tulp, K. Takkis and M. Moosus 6.1 Introduction 148 6.2 Mathematical Foundation of 2-D Descriptors 151 6.3 Navigation Among 2-D Descriptors 153 6.4 Examples of Use 166 6.5 Interpretation of 2-D Descriptors 180 6.6 Sources for the Calculation of 2-D Descriptors 184 6.7 Conclusions 186 6.8 Literature for In-Depth Reading 187 6.9 Acknowledgements 188 References 189 Chapter 7 The Use of Frontier Molecular Orbital Calculations in Predictive Reactive Toxicology 193 S. J. Enoch 7.1 Introduction 193 7.2 Mechanistic Chemistry 194 7.3 Commonly Utilised Quantum Mechanical Descriptors and Levels of Computational Theory 195 7.4 Descriptors Derived from Frontier Molecular Orbitals 196 7.5 Isomers and Conformers 205 7.6 Chemical Category Formation and Read-Across 206 7.7 Quantum Chemical Calculations 206 7.8 Conclusions 207 7.9 Acknowledgements 207 References 207 Chapter 8 Three-Dimensional Molecular Modelling of Receptor-Based Mechanisms in Toxicology 210 J. C. Madden and M. T. D. Cronin 8.1 Introduction 210 8.2 Background to 3-D Approaches 211 8.3 Modelling Approaches for Receptor-Mediated Toxicity 213
8.4 Ligand-Based Approaches 217 8.5 Receptor-Based approaches 221 8.6 Examples of the Application of 3-D Approaches in Predicting Receptor-Mediated Toxicity 222 8.7 Advantages and Disadvantages of 3-D Methods 225 8.8 Conclusions and Future Outlook 225 8.9 Acknowledgements 226 References 226 Chapter 9 Statistical Methods for Continuous Measured Endpoints in In Silico Toxicology 228 P. H. Rowe 9.1 Continuous Measured Endpoints (Interval Scale Data) 228 9.2 Regression Analysis Models in QSAR 228 9.3 Principal Components Regression (PCR) 244 9.4 Partial Least Squares (PLS) Regression 248 9.5 Conclusions 250 References 250 Chapter 10 Statistical Methods for Categorised Endpoints in In Silico Toxicology 252 P. H. Rowe 10.1 Ordinal and Nominal Scale Endpoints and Illustrative Data 252 10.2 Discriminant Analysis 253 10.3 Logistic Regression 262 10.4 k-nearest-neighbour(s) 271 10.5 Choice of Method for Categorised Data 272 10.6 Conclusions 273 References 273 Chapter 11 Characterisation, Evaluation and Possible Validation of In Silico Models for Toxicity: Determining if a Prediction is Valid 275 M. T. D. Cronin 11.1 Introduction 275 11.2 A Very Brief History 276 11.3 OECD and European Chemicals Agency Documents and Further Background Papers and Sources of Information 277 11.4 Definition of Terms 277 11.5 OECD Principles for the Validation of (Q)SARs 283
11.6 Examples of Validation of (Q)SARs from the Literature 287 11.7 Describing a QSAR: Use of the QSAR Model Reporting Format 287 11.8 Case Studies: Application of the OECD Principles 288 11.9 Is the Prediction Valid? 296 11.10 Conclusions and Recommendations 298 11.11 Acknowledgements 298 References 299 Chapter 12 Developing the Applicability Domain of In Silico Models: Relevance, Importance and Methods 301 M. Hewitt and C. M. Ellison 12.1 Introduction 301 12.2 Regulatory Context 302 12.3 Applicability Domain Definition 303 12.4 Case Study 316 12.5 Recommendations 329 12.6 Acknowledgements 330 References 330 Chapter 13 Mechanisms of Toxic Action in In Silico Toxicology 334 D. W. Roberts 13.1 Introduction 334 13.2 Modes and Mechanisms 335 13.3 Reaction Mechanistic Domains 338 13.4 Mechanism-Based Reactivity Parameters for Electrophilic Toxicity 339 13.5 Role of Hydrophobicity in Modelling Electrophilic Toxicity 342 13.6 Conclusions 343 13.7 Acknowledgements 344 References 344 Chapter 14 Adverse Outcome Pathways: A Way of Linking Chemical Structure to In Vivo Toxicological Hazards 346 T. W. Schultz 14.1 Categories in Hazard Assessment 346 14.2 Filling Data Gaps in a Category 348 14.3 Mechanism of Toxic Action 349 14.4 Toxicologically Meaningful Categories (TMCs) 350 14.5 The Concept of the Adverse Outcome Pathway 352 14.6 Weak Acid Respiratory Uncoupling 354
14.7 Respiratory Irritation 355 14.8 Skin Sensitisation 357 14.9 Acetylcholinesterase Inhibition 359 14.10 Receptor Binding Pathways for Phenolic Oestrogen Mimics 360 14.11 Using Pathways to Form TMCs and Reduce Testing 361 14.12 Hazards with Elaborate Datasets 363 14.13 Pathways for Elaborate Hazard Endpoints 364 14.14 Positive Attributes of the Adverse Outcome Pathway Approach 366 14.15 Conclusions: Basic Elements in Developing a Pathway 367 References 368 Chapter 15 An Introduction to Read-Across for the Prediction of the Effects of Chemicals 372 S. Dimitrov and O. Mekenyan 15.1 Read-Across 372 15.2 Basis of Performing Read-Across 372 15.3 Practical Aspects of Read-Across 374 15.4 Example: Read-Across for the Prediction of the Toxicity of 4-Ethylphenol to Tetrahymenapyriformis 379 15.5 Conclusions 383 References 383 Chapter 16 Tools for Category Formation and Read-Across: Overview of the OECD (Q)SAR Application Toolbox 385 R. Diderich 16.1 The OECD (Q)SAR Project: From Validation Principles to an Application Toolbox 385 16.2 Workflow of the Toolbox 387 16.3 Example Use Scenarios for Regulatory Application 391 16.4 Conclusions and Outlook 404 References 405 Chapter 17 Open Source Tools for Read-Across and Category Formation 408 N. Jeliazkova, J. Jaworska and A. P. Worth 17.1 Introduction 408 17.2 Open Source, Open Data and Open Standards in Chemoinformatics 412 17.3 Descriptions of the Tools Suitable for Category Formation and Read-Across 417
17.4 Summary and Conclusions 442 17.5 Acknowledgements 442 References 443 Chapter 18 Biological Read-Across: Mechanistically-Based Species-Species and Endpoint-Endpoint Extrapolations 446 M. T. D. Cronin 18.1 Introduction 446 18.2 Extrapolation of Toxicological Information from One Species to Another 447 18.3 Prediction Models 449 18.4 Examples of Extrapolation of Toxicity Between Species: Acute Aquatic Toxicity 449 18.5 Endpoint-to-Endpoint Read-Down of Toxicity: Extrapolation of Toxicity Between Effects 470 18.6 US Environmental Protection Agency Web-Based Inter-species Correlation Estimation (Web-ICE) Application 472 18.7 Recent Developments 473 18.8 Conclusions 473 18.9 Acknowledgments 474 References 474 Chapter 19 Expert Systems for Toxicity Prediction 478 /. C. Dearden 19.1 Introduction 478 19.2 Available Expert Systems 481 19.3 Independent Comparative Assessment of Software Performance 495 19.4 Consensus Modelling 497 19.5 Software Performance with Tetrahymena pyriformis Test Set 498 19.6 Software Performance with Skin Sensitisation Test Set 500 19.7 Conclusions 501 19.8 Acknowledgments 502 References 502 Chapter 20 Exposure Modelling for Risk Assessment 508 J. Marquart 20.1 Introduction: Hazard, Exposure, Risk 508 20.2 Types of Exposure Estimates used in Risk Characterisation in REACH 510
20.3 Methods for Exposure Assessment in Regulatory Processes 512 Models 512 20.4 Types of Human Exposure 20.5 Detailed Description of the Models 515 20.6 Advantages and Disadvantages of the Models 524 20.7 Conclusions 528 References 528 Chapter 21 Toxicokinetic Considerations in Predicting Toxicity 531 /. C. Madden 21.1 Introduction 531 21.2 Internal Exposure 532 21.3 Predicting ADME Parameters 540 21.4 Physiologically-Based Toxicokinetic Modelling 547 21.5 Conclusions and Outlook 553 21.6 Acknowledgements 554 References 554 Chapter 22 Multiple Test In Silico Weight-of-Evidence for Toxicological Endpoints 558 T. Aldenberg and J. S. Jaw orska 22.1 Introduction 558 22.2 Two-Test Training Dataset 559 22.3 One-Test Bayesian Inference 560 22.4 Two-Test Battery Bayesian Inference 566 22.5 Two-Test Data Fitting and Model Selection 574 22.6 Conclusions 580 References 581 Chapter 23 Integrated Testing Strategies and the Prediction of Toxic Hazard 584 M. Balls 23.1 Introduction 584 23.2 Essential Nature and Uses of ITS 585 23.3 Historical Development of the Concept of ITS 586 23.4 ITS and Risk Assessment 592 23.5 In Vitro Methods for Use in ITS 596 23.6 Evaluation and Application of ITS 597 23.7 Securing the Regulatory Acceptance of ITS 600 References 603
Chapter 24 Using In Silico Toxicity Predictions: Case Studies for Skin Sensitisation 606 M. T. D. Cronin and J. C. Madden 24.1 Introduction 606 24.2 Forming a Consensus: Integrating Predictions 607 24.3. Choice of Chemicals for Analysis 608 24.4. In Silico Prediction Methods and In Chemico Data 608 24.5 Existing Data, In Silico Predictions and In Chemico Data for 4-Amino-2-Nitrophenol 610 24.6 In Silico Predictions and In Chemico Data for 1,14-Tetradecanediol 616 24.7 Conclusions and Recommendations 620 24.8 Acknowledgements 620 References 621 Appendix 1 624 Appendix 2 645 Subject Index 659