
Molecular Docking for Computer-Aided Drug Design
Fundamentals, Techniques, Resources and Applications
- 1st Edition - February 17, 2021
- Imprint: Academic Press
- Editor: Mohane S. Coumar
- Language: English
- Paperback ISBN:9 7 8 - 0 - 1 2 - 8 2 2 3 1 2 - 3
- eBook ISBN:9 7 8 - 0 - 1 2 - 8 2 2 3 1 3 - 0
Molecular Docking for Computer-Aided Drug Design: Fundamentals, Techniques, Resources and Applications offers in-depth coverage on the use of molecular docking for drug design… Read more

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Request a sales quoteMolecular Docking for Computer-Aided Drug Design: Fundamentals, Techniques, Resources and Applications offers in-depth coverage on the use of molecular docking for drug design. The book is divided into three main sections that cover basic techniques, tools, web servers and applications. It is an essential reference for students and researchers involved in drug design and discovery.
- Covers the latest information and state-of-the-art trends in structure-based drug design methodologies
- Includes case studies that complement learning
- Consolidates fundamental concepts and current practice of molecular docking into one convenient resource
Graduate students and researchers in pharmacy, pharmacology, biochemistry and molecular biology as well as those in bioinformatics, medicinal chemistry, computational chemistry, structural biology, and biophysics
Industry professionals working in drug design
- Cover image
- Title page
- Table of Contents
- Copyright
- Dedication
- List of Contributors
- Preface
- Acknowledgments
- Part I. Foundations and Basic Techniques of Docking
- Chapter 1. Modern Tools and Techniques in Computer-Aided Drug Design
- 1. Overview of Computer-Aided Drug Design
- 2. Chemical Libraries
- 3. Structure-Based Approaches and Screening
- 4. Ligand-Based Approaches and Screening
- 5. Applications of CADD in Drug Discovery
- 6. Conclusions
- Chapter 2. Biomolecular Talks—Part 1: A Theoretical Revisit on Molecular Modeling and Docking Approaches
- 1. Biomolecules and Their Interactions
- 2. Computational Approaches to Study Biomolecular Interactions
- 3. Molecular Docking
- 4. Conclusion
- Chapter 3. Post-processing of Docking Results: Tools and Strategies
- 1. Introduction
- 2. Scoring Functions
- 3. Representation of Ligand–receptor Complexes
- 4. Post-processing Strategies
- 5. Conclusions
- Chapter 4. Best Practices for Docking-Based Virtual Screening
- 1. Introduction
- 2. Docking-Based Virtual Screening
- 3. Best Practices in Molecular Docking for Virtual Screening
- 4. Incorporating Protein Flexibility
- 5. Molecular Docking in Fragment-Based Drug Discovery
- 6. Case Studies of DBVS
- 7. Concluding Remarks and Future Directions
- Chapter 5. Virtual Libraries for Docking Methods: Guidelines for the Selection and the Preparation
- 1. Introduction
- 2. Data Collection Within the Vast Chemical Space
- 3. Database Preparation
- 4. Conclusion
- List of Abbreviations
- Part II. Methods For Generating 3d Structures of Targets
- Chapter 6. 3D Structural Determination of Macromolecules Using X-ray Crystallography Methods
- 1. Introduction
- 2. Protein Purification
- 3. Protein Crystallization
- 4. X-ray, Synchrotron, and XFELS
- 5. Data Collection and Processing
- 6. Solving Phases in MR, SIR/MIR, and SAD/MAD Methods
- 7. Structure Solution
- 8. Structure Refinement and Model Building
- 9. Characterization and Cross-Validation of Solved 3D Structures
- 10. Structure Validation
- 11. Conclusion
- Chapter 7. Electron Microscopy and Single Particle Analysis for Solving Three-Dimensional Structures of Macromolecules
- 1. Introduction
- 2. The Major Techniques in Structural Biology
- 3. Electron Microscope
- 4. Outline of Single Particle Analysis
- 5. Remarkable Results From Single Particle Analysis
- 6. Single Particle Analysis and Drug Discovery
- 7. Conclusions and Future Directions
- Chapter 8. Computational Modeling of Protein Three-Dimensional Structure: Methods and Resources
- 1. Introduction
- 2. Protein Structural Organization
- 3. Sequence–Structure–Function Relationship
- 4. Experimental Approaches to Determine Structures
- 5. Computational Approaches for Predicting Protein Structures
- 6. Case Study and Resources for Modeling Protein Structures
- 7. Conclusions and Future Directions
- Part III. Tools, Web Servers, Resources, and a Step-By-Step Guide for Docking
- Chapter 9. Resources for Docking-Based Virtual Screening
- 1. Drug Discovery
- 2. A Brief View of Docking and Its Use
- 3. Resources for Docking
- 4. Conclusion
- Chapter 10. Do It Yourself—Dock It Yourself: General Concepts and Practical Considerations for Beginners to Start Molecular Ligand–Target Docking Simulations
- 1. Introduction
- 2. Selecting the Docking Program and Associated Tools
- 3. Installing and Launching ADV, ADT, SPDBV, and Vega ZZ
- 4. Creating the Virtual Docking Laboratory
- 5. Preparing the Input Structures of the Target Proteins
- 6. Preparing the Small Organic Compound Ligands
- 7. Generating the Search Space and Running the Docking Simulations
- 8. Analyzing the Graphical Docking Results
- 9. Analyzing the Numerical Docking Results
- 10. Synopsis of the Input, Processing, and Output Steps for ADV Docking
- 11. Solutions for Problems With the Programs (Trouble Shooting)
- 12. Applicability of the Presented Docking Procedures
- 13. Conclusion
- Part IV. Applications and Case Studies of Docking
- Chapter 11. Use of Molecular Docking as a Decision-Making Tool in Drug Discovery
- 1. Introduction
- 2. Molecular Docking Simulation
- 3. Integrated Computational Methods Involving Molecular Docking
- 4. Conclusion and Outlook
- Chapter 12. Biomolecular Talks—Part 2: Applications and Challenges of Molecular Docking Approaches
- 1. Introduction
- 2. Applications of Molecular Docking
- 3. Challenges in Molecular Docking Studies
- 4. Computational Tools/Servers Available for Docking
- 5. Conclusion
- Chapter 13. Application of Docking for Lead Optimization
- 1. Introduction
- 2. Approaches to Lead Optimization
- 3. Structure-Based Lead Optimization
- 4. Molecular Docking for Lead Optimization
- 5. Methods for Calculating Binding Affinities for Lead Optimization
- 6. Machine Learning–Based Lead Optimization
- 7. Limitations of Molecular Docking for Lead Optimization
- 8. Predictive Toxicity Using Docking and Machine Learning
- 9. Case Studies
- 10. Conclusion
- Chapter 14. Multi-Target Drugs as Master Keys to Complex Diseases: Inverse Docking Strategies and Opportunities
- 1. Introduction
- 2. Computational Strategies for Multi-Target Drug Design
- 3. Case Examples
- 4. Concluding Remarks and Future Perspectives
- Chapter 15. Drug Repositioning: Principles, Resources, and Application of Structure-Based Virtual Screening for the Identification of Anticancer Agents
- 1. Introduction
- 2. Computer-Aided Virtual Screening
- 3. Drug Repositioning
- 4. Conclusion
- Chapter 16. Design and Discovery of Kinase Inhibitors Using Docking Studies
- 1. Introduction
- 2. Protein Kinases as Drug Targets
- 3. Structure of Protein Kinases
- 4. Dynamics of Protein Kinases
- 5. Types of Inhibitors
- 6. Molecular Docking in Design and Discovery of Kinase Inhibitors
- 7. Structure-Guided Strategies for Overcoming Kinase Inhibitors Resistance
- 8. Molecular Dynamics in Design and Discovery of Kinase Inhibitors
- 9. Molecular Dynamics Approaches to Enhance Docking
- 10. Application of Molecular Dynamics to Describe Allostery
- 11. Machine Learning Approaches to Enhance Docking
- 12. Conclusion
- Chapter 17. Docking Approaches Used in Epigenetic Drug Investigations
- 1. Epigenetics
- 2. Epigenetics and Diseases
- 3. Drug Discovery of Epigenetic Modulators with Docking
- 4. Conclusion and Future Perspectives
- Chapter 18. Molecular Docking for Natural Product Investigations: Pitfalls and Ways to Overcome Them
- 1. Introduction
- 2. Peculiarities in Natural Product Investigations
- 3. Molecular Docking for Natural Product Investigations
- 4. Other Computational Methods for Natural Product Investigations
- 5. Recent Examples of Docking in Natural Product Research
- 6. Conclusions
- Chapter 19. Advances in Docking-Based Drug Design for Microbial and Cancer Drug Targets
- 1. Introduction
- 2. Structure-Based Drug Design
- 3. Ligand-Based Virtual Screening
- 4. In Silico Fragment-Based Drug Design
- 5. In Silico Drug Repurposing
- 6. Reverse or Inverse Drug Designing
- 7. Antibiotic Resistance and Drug Designing Through Docking
- 8. Conclusion
- Chapter 20. Role of Bioinformatics in Subunit Vaccine Design
- 1. Introduction
- 2. Basics of Vaccine
- 3. Properties of an Ideal Vaccine and Its Components
- 4. Bioinformatics in Vaccine Design
- 5. Computational Design of Vaccine Constructs
- 6. Computational Prediction of Physicochemical Properties of Designed Vaccine Construct/s
- 7. Structure Prediction, Protein–Protein Interactions, and Complex Stability Analysis
- 8. An Overview of Successful Vaccine Design Using Bioinformatics
- 9. Conclusion
- Chapter 21. Computational Approaches Toward Development of Topoisomerase I Inhibitor: A Clinically Validated Target
- 1. Introduction
- 2. Structure of Human Topoisomerase I
- 3. Inhibitors of Human Topoisomerase I
- 4. Computational Approaches for the Discovery of Topoisomerase I Inhibitors
- 5. Conclusion
- Chapter 22. Docking-Based Virtual Screening Using PyRx Tool: Autophagy Target Vps34 as a Case Study
- 1. Introduction
- 2. PyRx 0.8 as a Docking-Based Virtual Screening Tool
- 3. Case Study: DBVS to Identify Small Molecule Inhibitors of Vps34
- 4. Discussion
- 5. Conclusion
- Chapter 23. Molecular Docking: A Contemporary Story About Food Safety
- 1. Introduction
- 2. Food Safety
- 3. Databases and Big Data in Food Safety
- 4. In silico Methods
- 5. Case Studies
- 6. Conclusions
- Index
- Edition: 1
- Published: February 17, 2021
- Imprint: Academic Press
- No. of pages: 520
- Language: English
- Paperback ISBN: 9780128223123
- eBook ISBN: 9780128223130
MC
Mohane S. Coumar
Dr. S. Mohane Coumar has over 15 years of research experience in the design and discovery of drugs in India and Taiwan. Since 2010 he is working as Assistant Professor at the Centre for Bioinformatics, Pondicherry University, India, and has received his Ph.D. (Pharmaceutical Sciences, 2003) from Panjab University, Chandigarh, India. He briefly worked as a Research Officer at Regional Research Lab, Jammu, and as Research Scientist at Ranbaxy Research Labs - New Drug Discovery Unit, Gurgaon, before moving to Taiwan for Postdoctoral Research. He has over six years (2004-2010) research training at National Health Research Institutes, Taiwan on anti-cancer drug design & development. His research efforts have led to several international patents and publications. Two of his inventions are in clinical development for the treatment of cancer in Taiwan.
At Pondicherry University, his efforts are focused on applying chemical and biological knowledge to the design and development of drugs using computational approaches such as computer-aided drug design (CADD), NGS data analysis, and systems biology. He has guided/co-guided seven Ph.D. scholars in Bioinformatics and interdisciplinary research programs, and has over 80 research/review articles with an H-index of 23 (Scopus data). His current research areas include anti-cancer and anti-microbial drug discovery with a focus to overcome drug resistance.
Affiliations and expertise
Assistant Professor, Centre for Bioinformatics, School of Life Sciences, Pondicherry University, Kalapet, Puducherry, IndiaRead Molecular Docking for Computer-Aided Drug Design on ScienceDirect