In Silico Methods for Predicting Drug Toxicity

This detailed volume explores in silico methods for pharmaceutical toxicity by combining the theoretical advanced research with the practical application of the tools. Beginning with a section covering sophisticated models addressing the binding to receptors, pharmacokinetics and adsorption, metabolism, distribution, and excretion, the book continues with chapters delving into models for specific toxicological and ecotoxicological endpoints, as well as broad views of the main initiatives and new perspectives which will very likely improve our way of modelling pharmaceuticals. Written for the highly successful Methods in Molecular Biology series, chapters include the kind of detailed implementation advice that is key for achieving successful research results.

Authoritative and practical, In Silico Methods for Predicting Drug Toxicity offers the advantage of incorporating data and knowledge from different fields, such as chemistry, biology, -omics, and pharmacology, to achieve goals in this vital area of research.

Table of contents (21 chapters)

·         QSAR Methods

Gini, Giuseppina

Pages 1-20

·         In Silico 3D Modeling of Binding Activities

Moro, Stefano (et al.)

Pages 23-35

·         Modeling Pharmacokinetics

Bois, Frederic Y. (et al.)

Pages 37-62

·         Modeling ADMET

Ghosh, Jayeeta (et al.)

Pages 63-83

·         In Silico Prediction of Chemically Induced Mutagenicity: How to Use QSAR Models and Interpret Their Results

Mombelli, Enrico (et al.)

Pages 87-105

·         In Silico Methods for Carcinogenicity Assessment

Golbamaki, Azadi (et al.)

Pages 107-119

·         VirtualToxLab: Exploring the Toxic Potential of Rejuvenating Substances Found in Traditional Medicines

Smieško, Martin (et al.)

Pages 121-137

·         In Silico Model for Developmental Toxicity: How to Use QSAR Models and Interpret Their Results

Marzo, Marco (et al.)

Pages 139-161

·         In Silico Models for Repeated-Dose Toxicity (RDT): Prediction of the No Observed Adverse Effect Level (NOAEL) and Lowest Observed Adverse Effect Level (LOAEL) for Drugs

Pizzo, Fabiola (et al.)

Pages 163-176

·         In Silico Models for Acute Systemic Toxicity

Burton, Julien (et al.)

Pages 177-200

·         In Silico Models for Hepatotoxicity

Hewitt, Mark (et al.)

Pages 201-236

·         In Silico Models for Ecotoxicity of Pharmaceuticals

Roy, Kunal (et al.)

Pages 237-304

·         Use of Read-Across Tools

Manganelli, Serena (et al.)

Pages 305-322

·         Adverse Outcome Pathways as Tools to Assess Drug-Induced Toxicity

Vinken, Mathieu

Pages 325-337

·         A Systems Biology Approach for Identifying Hepatotoxicant Groups Based on Similarity in Mechanisms of Action and Chemical Structure

Hebels, Dennie G. A. J. (et al.)

Pages 339-359

·         In Silico Study of In Vitro GPCR Assays by QSAR Modeling

Mansouri, Kamel (et al.)

Pages 361-381

·         Taking Advantage of Databases

Myatt, Glenn J. (et al.)

Pages 383-430

·         QSAR Models at the US FDA/NCTR

Hong, Huixiao (et al.)

Pages 431-459

·         A Round Trip from Medicinal Chemistry to Predictive Toxicology

Mangiatordi, Giuseppe Felice (et al.)

Pages 461-473

·         The Use of In Silico Models Within a Large Pharmaceutical Company

Brigo, Alessandro (et al.)

Pages 475-510

·         The Consultancy Activity on In Silico Models for Genotoxic Prediction of Pharmaceutical Impurities

Pavan, Manuela (et al.)

Pages 511-529