Book description
A key resource for toxicologists across a broad spectrum of fields, this book offers a comprehensive analysis of molecular modelling approaches and strategies applied to risk assessment for pharmaceutical and environmental chemicals.
• Provides a perspective of what is currently achievable with computational toxicology and a view to future developments
• Helps readers overcome questions of data sources, curation, treatment, and how to model / interpret critical endpoints that support 21st century hazard assessment
• Assembles cutting-edge concepts and leading authors into a unique and powerful single-source reference
• Includes in-depth looks at QSAR models, physicochemical drug properties, structure-based drug targeting, chemical mixture assessments, and environmental modeling
• Features coverage about consumer product safety assessment and chemical defense along with chapters on open source toxicology and big data
Table of contents
- Cover
- Title Page
- List of Contributors
- Preface
- Acknowledgments
-
Part I: Computational Methods
- Chapter 1: Accessible Machine Learning Approaches for Toxicology
-
Chapter 2: Quantum Mechanics Approaches in Computational Toxicology
- 2.1 Translating Computational Chemistry to Predictive Toxicology
- 2.2 Levels of Theory in Quantum Mechanical Calculations
- 2.3 Representing Molecular Orbitals
- 2.4 Hybrid Quantum and Molecular Mechanical Calculations
- 2.5 Representing System Dynamics
- 2.6 Developing QM Descriptors
- 2.7 Rational Design of Safer Chemicals
- References
-
Part II: Applying Computers to Toxicology Assessment: Pharmaceutical, Industrial and Clinical
- Chapter 3: Computational Approaches for Predicting hERG Activity
- Chapter 4: Computational Toxicology for Traditional Chinese Medicine
-
Chapter 5: Pharmacophore Models for Toxicology Prediction
- 5.1 Introduction
- 5.2 Antitarget Screening
- 5.3 Prediction of Liver Toxicity
- 5.4 Prediction of Cardiovascular Toxicity
- 5.5 Prediction of Central Nervous System (CNS) Toxicity
- 5.6 Prediction of Endocrine Disruption
- 5.7 Prediction of ADME
- 5.8 General Remarks on the Limits and Future Perspectives for Employing Pharmacophore Models in Toxicological Studies
- References
-
Chapter 6: Transporters in Hepatotoxicity
- 6.1 Introduction
- 6.2 Basolateral Transporters
- 6.3 Canalicular Transporters
- 6.4 Data Sources for Transporters in Hepatotoxicity
- 6.5 In Silico Transporters Models
- 6.6 Ligand-Based Approaches
- 6.7 OATP1B1 and OATP1B3
- 6.8 NTCP
- 6.9 OCT1
- 6.10 OCT2
- 6.11 MRP1, MRP3, and MRP4
- 6.12 BSEP
- 6.13 MRP2
- 6.14 MDR1/P-gp
- 6.15 MDR3
- 6.16 BCRP
- 6.17 MATE1
- 6.18 ASBT
- 6.19 Structure-Based Approaches
- 6.20 Complex Models Incorporating Transporter Information
- 6.21 In Vitro Models
- 6.22 Multiscale Models
- 6.23 Outlook
- Acknowledgments
- References
-
Chapter 7: Cheminformatics in a Clinical Setting
- 7.1 Introduction
- 7.2 Similarity Analysis Applied to Drug of Abuse/Toxicology Immunoassays
- 7.3 Similarity Analysis Applied to Therapeutic Drug Monitoring Immunoassays
- 7.4 Similarity Analysis Applied to Steroid Hormone Immunoassays
- 7.5 Cheminformatics Applied to “Designer Drugs”
- 7.6 Relevance to Antibody-Ligand Interactions
- 7.7 Conclusions and Future Directions
- Acknowledgment
- References
- Part III: Applying Computers to Toxicology Assessment: Environmental and Regulatory Perspectives
-
Part IV: New Technologies for Toxicology, Future Perspectives
- Chapter 11: Big Data in Computational Toxicology: Challenges and Opportunities
- Chapter 12: HLA-Mediated Adverse Drug Reactions: Challenges and Opportunities for Predictive Molecular Modeling
- Chapter 13: Open Science Data Repository for Toxicology
- Chapter 14: Developing Next Generation Tools for Computational Toxicology
- Index
- End User License Agreement
Product information
- Title: Computational Toxicology
- Author(s):
- Release date: February 2018
- Publisher(s): Wiley
- ISBN: 9781119282563
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