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In Silico Methods for Predicting Drug Toxicity

  • Book
  • © 2016

Overview

Editors:
  1. Emilio Benfenati

    1. Mario Negri Inst for Pharm Rsrch, IRCCS, Milan, Italy

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  • Includes cutting-edge methods and protocols involving in silico techniques
  • Provides step-by-step detail essential for reproducible results
  • Contains key notes and implementation advice from the experts

Part of the book series: Methods in Molecular Biology (MIMB, volume 1425)

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Table of contents (21 protocols)

  1. Front Matter

    Pages i-xi
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  2. QSAR Methods

    • Giuseppina Gini
    Pages 1-20

  3. Modeling a Pharmaceutical in the Human Body

    1. Front Matter

      Pages 21-21
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    2. In Silico 3D Modeling of Binding Activities

      • Stefano Moro, Mattia Sturlese, Antonella Ciancetta, Matteo Floris
      Pages 23-35

    3. Modeling Pharmacokinetics

      • Frederic Y. Bois, Céline Brochot
      Pages 37-62

    4. Modeling ADMET

      • Jayeeta Ghosh, Michael S. Lawless, Marvin Waldman, Vijay Gombar, Robert Fraczkiewicz
      Pages 63-83

  4. The Applications of In Silico Models for the Different Endpoints

    1. Front Matter

      Pages 85-85
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    2. In Silico Prediction of Chemically Induced Mutagenicity: How to Use QSAR Models and Interpret Their Results

      • Enrico Mombelli, Giuseppa Raitano, Emilio Benfenati
      Pages 87-105

    3. In Silico Methods for Carcinogenicity Assessment

      • Azadi Golbamaki, Emilio Benfenati
      Pages 107-119

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

      • Martin SmieÅ¡ko, Angelo Vedani
      Pages 121-137

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

      • Marco Marzo, Alessandra Roncaglioni, Sunil Kulkarni, Tara S. Barton-Maclaren, Emilio Benfenati
      Pages 139-161

    6. 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

      • Fabiola Pizzo, Emilio Benfenati
      Pages 163-176

    7. In Silico Models for Acute Systemic Toxicity

      • Julien Burton, Andrew P. Worth, Ivanka Tsakovska, Antonia Diukendjieva
      Pages 177-200

    8. In Silico Models for Hepatotoxicity

      • Mark Hewitt, Katarzyna Przybylak
      Pages 201-236

    9. In Silico Models for Ecotoxicity of Pharmaceuticals

      • Kunal Roy, Supratik Kar
      Pages 237-304

    10. Use of Read-Across Tools

      • Serena Manganelli, Emilio Benfenati
      Pages 305-322

  5. The Scientific and Society Challenges

    1. Front Matter

      Pages 323-323
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    2. Adverse Outcome Pathways as Tools to Assess Drug-Induced Toxicity

      • Mathieu Vinken
      Pages 325-337

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

      • Dennie G. A. J. Hebels, Axel Rasche, Ralf Herwig, Gerard J. P. van Westen, Danyel G. J. Jennen, Jos C. S. Kleinjans
      Pages 339-359

    4. In Silico Study of In Vitro GPCR Assays by QSAR Modeling

      • Kamel Mansouri, Richard S. Judson
      Pages 361-381
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Keywords

About this book

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.

Editors and Affiliations

  • Mario Negri Inst for Pharm Rsrch, IRCCS, Milan, Italy

    Emilio Benfenati

Bibliographic Information

  • Book Title: In Silico Methods for Predicting Drug Toxicity

  • Editors: Emilio Benfenati

  • Series Title: Methods in Molecular Biology

  • DOI: https://doi.org/10.1007/978-1-4939-3609-0

  • Publisher: Humana New York, NY

  • eBook Packages: Springer Protocols

  • Copyright Information: Springer Science+Business Media New York 2016

  • Hardcover ISBN: 978-1-4939-3607-6Published: 17 June 2016

  • Softcover ISBN: 978-1-4939-8093-2Published: 30 May 2018

  • eBook ISBN: 978-1-4939-3609-0Published: 16 June 2016

  • Series ISSN: 1064-3745

  • Series E-ISSN: 1940-6029

  • Edition Number: 1

  • Number of Pages: XI, 534

  • Number of Illustrations: 37 b/w illustrations, 156 illustrations in colour

  • Topics: Pharmacology/Toxicology

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