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Recent Advances in Molecular Docking

Methods, Tools, and Applications

  • 1st Edition - September 30, 2026
  • Latest edition
  • Editor: Khalid Raza
  • Language: English

Recent Advances in Molecular Docking: Methods, Tools, and Applications offers an authoritative guide to modern molecular docking techniques, emphasizing the integration of artifi… Read more

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Description

Recent Advances in Molecular Docking: Methods, Tools, and Applications offers an authoritative guide to modern molecular docking techniques, emphasizing the integration of artificial intelligence and machine learning. The volume covers foundational principles, computational workflows, and advanced scoring functions, providing researchers and practitioners with practical tools to improve drug-target interaction predictions. It highlights applications across pharmaceuticals, including cancer, neurological disorders, and infectious diseases, which are all supported by real-world case studies. Challenges in docking accuracy, reproducibility, validation, and ethical and regulatory considerations are also covered.

Authored by international experts, it bridges theoretical knowledge with practical applications, making it an essential resource for computational biologists, pharmacologists, and drug developers aiming to leverage AI-driven docking in precision medicine.

Key features

  • Explores state-of-the-art molecular docking methods that integrate AI and machine learning
  • Provides practical guidance on docking workflows, scoring functions, and benchmarking tools
  • Covers applications in drug discovery, precision therapeutics, and multi-omics integration
  • Includes case studies on cancer, neurological diseases, and infectious diseases
  • Addresses ethical, legal, and regulatory perspectives in computational drug design

Readership

Pharmacologists; Computational Biologists; Drug Discovery Scientists; Bioinformaticians

Table of contents

Section I: Fundamentals of Molecular Docking

1. Fundamentals of Molecular Docking: Concepts, Terminology, Docking Types, and Scoring Functions

2. Protein–Ligand Interaction and Binding Site Prediction

3. Databases for Molecular Docking: PDB, ChEMBL, ZINC, PubChem

Section II: Computational Methods and Workflows

4. Molecular Docking Workflows and Pipelines

5. Molecular Docking Tools and Their Benchmarking: A Practical Guide for Interdisciplinary Researchers

6. Quantum Mechanics and Molecular Mechanics (QM/MM) in Docking

7. Molecular Dynamics and Its Integration with Docking Studies

Section III: Advanced Techniques and Integrative Approaches

8. Docking Against GPCRs, Ion Channels, and Membrane Proteins

9. Ensemble and Multi-Target Docking Approaches for Polypharmacology in Drug Discovery

10. Virtual Screening and High-Throughput Docking: Finding Inhibitors Against P-gp Transporter for Treating Hepatocellular Carcinoma (HCC)

Section IV: Artificial Intelligence and Machine Learning in Docking

11. AI-Driven Molecular Docking: Machine Learning Models, Deep Learning Scoring, and Advanced Docking Frameworks

12. TAMARIND: A Unified Framework for Efficient and Accurate Ligand Docking via Deep Learning

13. Unifying AI Systems and Elastic Clouds for Scalable CUDA-Based Molecular Docking Using Task Dependency Trees

Section V: Applications in Drug Discovery and Therapeutics

14. Advances in Structure-Based Drug Design: Principles and Case Studies in Therapeutic Development

15. Docking in Cancer, Neurological Disorders, and Infectious Diseases

16. Drug Repurposing Using Docking Approaches

17. In Silico Study of Phytochemical, Synthetic, and Marine Compounds for Anti-Tubercular (Mycobacterium tuberculosis) Activity

18. Structure-Based Drug Designing Using Plant-Derived Compounds: Case Studies

19. Molecular Docking Meets Multi-Omics and Systems Biology: A New Era of Precision Therapeutics

20. Leveraging Digital Twin Technology with Multi-Omics and Molecular Docking for Precision Oncology

Section VI: Validation, Platforms, and Future Perspectives

21. Challenges in Docking Accuracy and Reproducibility

22. Correlation of Computational Molecular Docking Predictions with Experimental Outcomes

23. Cloud and HPC Platforms for Molecular Docking and Simulation

24. Ethical, Legal, and Regulatory Perspectives in Computational Drug Design

Product details

  • Edition: 1
  • Latest edition
  • Published: September 30, 2026
  • Language: English

About the editor

KR

Khalid Raza

Dr. Khalid Raza is an Associate Professor at the Department of Computer Science, Jamia Millia Islamia, New Delhi, India, and an Adjunct Professor at UCSI University, Malaysia. He has over 14 years of teaching and research experience and previously served as an ICCR Chair Visiting Professor at Ain Shams University, Egypt. Dr. Raza has published more than 160 peer-reviewed papers and authored/edited over 15 books with Springer, Elsevier, and CRC Press. He serves as Academic Editor of PLoS ONE, BMC Artificial Intelligence, and Guest Editor of npj Precision Oncology, JoVE, and several other journals. Recipient of Clarivate’s (Web of Science) India Excellence Research Citation Award 2025, Dr. Raza is consistently featured in the World’s Top 2% Scientists list (2022–2025). His research focuses on AI, bioinformatics, and health informatics

Affiliations and expertise
Department of Computer Science, Jamia Millia Islamia (Central University), Jamia Nagar, New Delhi, India