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Understanding the Basics of QSAR for Applications in Pharmaceutical Sciences and Risk Assessment
1st Edition - March 3, 2015
Authors: Kunal Roy, Supratik Kar, Rudra Narayan Das
Language: English
Paperback ISBN:9780128015056
9 7 8 - 0 - 1 2 - 8 0 1 5 0 5 - 6
eBook ISBN:9780128016336
9 7 8 - 0 - 1 2 - 8 0 1 6 3 3 - 6
Understanding the Basics of QSAR for Applications in Pharmaceutical Sciences and Risk Assessment describes the historical evolution of quantitative structure-activity relati…Read more
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Understanding the Basics of QSAR for Applications in Pharmaceutical Sciences and Risk Assessment describes the historical evolution of quantitative structure-activity relationship (QSAR) approaches and their fundamental principles. This book includes clear, introductory coverage of the statistical methods applied in QSAR and new QSAR techniques, such as HQSAR and G-QSAR. Containing real-world examples that illustrate important methodologies, this book identifies QSAR as a valuable tool for many different applications, including drug discovery, predictive toxicology and risk assessment. Written in a straightforward and engaging manner, this is the ideal resource for all those looking for general and practical knowledge of QSAR methods.
Includes numerous practical examples related to QSAR methods and applications
Follows the Organization for Economic Co-operation and Development principles for QSAR model development
Discusses related techniques such as structure-based design and the combination of structure- and ligand-based design tools
New researchers, professors and graduate students across the pharmaceutical sciences (including pharmacology, toxicology and medicinal chemistry); secondary audience of regulatory officials and risk assessors in toxicology and environmental health
Dedication
Foreword
References
Preface
Chapter 1. Background of QSAR and Historical Developments
1.1 Introduction
1.2 Physicochemical Aspects of Biological Activity of Drugs and Chemicals
1.3 Structure–Activity Relationship
1.4 Historical Development of QSARs: A Journey of Knowledge Enrichment
1.5 Applications of QSAR
1.6 Regulatory Perspectives of QSAR
1.7 Overview and Conclusion
References
Chapter 2. Chemical Information and Descriptors
2.1 Introduction
2.2 Concept of Descriptors
2.3 Type of Descriptors
2.4 Descriptors Commonly Used in QSAR Studies
2.5 Overview and Conclusion
References
Chapter 3. Classical QSAR
3.1 Introduction
3.2 The Free–Wilson Model
3.3 The Fujita–Ban Model
3.4 The LFER Model
3.5 Kubinyi’s Bilinear Model
3.6 The Mixed Approach
3.7 Overview and Conclusions
References
Chapter 4. Topological QSAR
4.1 Introduction
4.2 Topology: A Method of Chemical Structure Representation
4.3 Graphs and Matrices: Platforms for the Topological Paradigm
4.4 Topological Indices
4.5 Conclusion and Possibilities
References
Chapter 5. Computational Chemistry
5.1 Introduction
5.2 Computer Use in Chemistry
5.3 Conformational Analysis and Energy Minimization
5.4 Molecular Mechanics
5.5 Molecular Dynamics
5.6 Quantum Mechanics
5.7 Overview and Conclusion
References
Chapter 6. Selected Statistical Methods in QSAR
6.1 Introduction
6.2 Regression-Based Approaches
6.3 Classification-Based QSAR
6.4 Machine Learning Techniques
6.5 Conclusion
References
Chapter 7. Validation of QSAR Models
7.1 Introduction
7.2 Different Validation Methods
7.3 A Practical Example of the Calculation of Common Validation Metrics and the AD
7.4 QSAR model reporting format
7.5 Overview and Conclusion
References
Chapter 8. Introduction to 3D-QSAR
8.1 Introduction
8.2 Comparative Molecular Field Analysis
8.3 Comparative Molecular Similarity Indices Analysis
8.4 Molecular Shape Analysis
8.5 Receptor Surface Analysis
8.6 Other Approaches
8.7 Overview and Conclusions
References
Chapter 9. Newer QSAR Techniques
9.1 Introduction
9.2 HQSAR
9.3 G-QSAR
9.4 Other Approaches
9.5 Overview and Conclusions
References
Chapter 10. Other Related Techniques
10.1 Introduction
10.2 Pharmacophore
10.3 Structure-Based Design–Docking
10.4 Combination of Structure- and Ligand-Based Design Tools
10.5 In Silico Screening of Chemical Libraries: VS
10.6 Overview and Conclusions
References
Chapter 11. SAR and QSAR in Drug Discovery and Chemical Design—Some Examples
11.1 Introduction
11.2 Successful Applications of QSAR and Other In Silico Methods: Representative Examples
11.3 Conclusion
References
Chapter 12. Future Avenues
12.1 Introduction
12.2 Application Areas
12.3 Conclusion
References
Index
No. of pages: 484
Language: English
Edition: 1
Published: March 3, 2015
Imprint: Academic Press
Paperback ISBN: 9780128015056
eBook ISBN: 9780128016336
KR
Kunal Roy
Dr. Kunal Roy is a Professor and Ex-Head in the Department of Pharmaceutical Technology, Jadavpur University, Kolkata, India. He has been a recipient of Commonwealth Academic Staff Fellowship (University of Manchester, 2007) and Marie Curie International Incoming Fellowship (University of Manchester, 2013). The field of his research interest is QSAR and Molecular Modeling with application in Drug Design and Ecotoxicological Modeling. Dr. Roy has published more than 350 research articles in refereed journals (current SCOPUS h index 49). He has also coauthored two QSAR-related books, edited six QSAR books and published more than ten book chapters. Dr. Roy is a Co-Editor-in-Chief of Molecular Diversity (Springer Nature). He also serves as a member of the Editorial Boards of several International Journals.
Affiliations and expertise
Professor, Drug Theoretics and Cheminformatics Lab, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, India
SK
Supratik Kar
Affiliations and expertise
MPharm, Researcher, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, India
RD
Rudra Narayan Das
Affiliations and expertise
MPharm, Researcher, Department of Pharmaceutical Technology, Jadavpur University, Kolkata, India
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