Computational Drug Design: A Guide for Computational and Medicinal Chemists / Edition 1

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Overview

Helps you choose the right computational tools and techniques to meet your drug design goals

Computational Drug Design covers all of the major computational drug design techniques in use today, focusing on the process that pharmaceutical chemists employ to design a new drug molecule. The discussions of which computational tools to use and when and how to use them are all based on typical pharmaceutical industry drug design processes.

Following an introduction, the book is divided into three parts:

  • Part One, The Drug Design Process, sets forth a variety of design processes suitable for a number of different drug development scenarios and drug targets. The author demonstrates how computational techniques are typically used during the design process, helping readers choose the best computational tools to meet their goals.
  • Part Two, Computational Tools and Techniques, offers a series of chapters, each one dedicated to a single computational technique. Readers discover the strengths and weaknesses of each technique. Moreover, the book tabulates comparative accuracy studies, giving readers an unbiased comparison of all the available techniques.
  • Part Three, Related Topics, addresses new, emerging, and complementary technologies, including bioinformatics, simulations at the cellular and organ level, synthesis route prediction, proteomics, and prodrug approaches.

The book's accompanying CD-ROM, a special feature, offers graphics of the molecular structures and dynamic reactions discussed in the book as well as demos from computational drug design software companies.

Computational Drug Design is ideal for both students and professionals in drug design, helping them choose and take full advantage of the best computational tools available.

Note: CD-ROM/DVD and other supplementary materials are not included as part of eBook file.

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Editorial Reviews

From the Publisher
"In conclusion, this book provides a comprehensive introduction to computational drug design for scientists (e.g. medicinal chemists and pharmacologists, particularly at industrial level) who are not familiar with computational methods and who wish to discuss simulation outcomes with colleagues from computational departments. It provides a similarly comprehensive introduction for students, while also covering aspects not usually touched on by other computational textbooks. Students will then need to deepen their mathematical and theoretical background to become robust computational drug designers." (ChemMedChem, 2010)

“The book has been written in very lucid and readable language.” (Journal of Medicinal Chemistry, August 2009)

“As the author states, ‘this book is very industry-centric’ and was designed to explore the drug design process through the computational techniques that are used in a typical pharmaceutical industry.” (JACS Book Reviews, June 2009)

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Product Details

  • ISBN-13: 9780470126851
  • Publisher: Wiley
  • Publication date: 2/12/2009
  • Edition number: 1
  • Pages: 344
  • Product dimensions: 6.30 (w) x 9.30 (h) x 1.20 (d)

Meet the Author

David C. Young, PhD, is HPC Computational Specialist for Computer Sciences Corp., under contract to the Alabama Supercomputer Authority, where he heads user and application support for research and educational activities. Dr. Young has extensive experience in designing drugs and writing drug design software. He is the author of Computational Chemistry: A Practical Guide for Applying Techniques to Real World Problems, also published by Wiley.

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Table of Contents

Preface.

Acknowledgements.

About the Author.

Symbols Used in This Book.

Book Abstract.

1. Introduction.

Part I: The Drug Design Process.

2. Properties that Make a Molecule a Good Drug.

3. Target Identification.

4. Target characterization.

5. The Drug Design Process for a Known Protein target.

6. The Drug Design Process for an Unknown target.

7. Drug Design for Other targets.

8. Compound Library Design.

Part II: computational Tools and Techniques.

9. Homology Model Building.

10. Molecular Mechanics.

11. Protein Folding.

12. Docking.

13. Pharmacophore Models.

14. QSAR.

15. 3D-QSAR.

16. Quantum Mechanics in Drug Design.

17. De novo and Other AI Techniques.

18. Cheminformatics.

19. ADMET.

20. Multiobjective Optimization.

21. Automation of Tasks.

Part III: Related Topics.

22. Bioinformatics.

23. Simulations at the Cellular and Organ Level.

24. Synthesis Route Prediction.

25. Proteomics.

26. Prodrug Approaches.

27. Future Developments in Drug design.

Appendix: About the CD.

Glossary.

Index.

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