Computer-Aided Drug Design

Principles, Techniques, and Applications
1. Auflage 2026
ISBN: 978-1-394-37108-2
Verlag: John Wiley & Sons Inc

Buch, Englisch, 448 Seiten

Integrate QSAR, molecular docking, AI, and nanotechnology into drug design

Computational approaches now drive critical decisions at every stage of drug discovery and development. Computer-Aided Drug Design: Principles, Techniques, and Applications provides an in-depth treatment of CADD methodologies, from QSAR and molecular docking to pharmacophore mapping and virtual screening. Written by Ajmer Singh Grewal, a pharmaceutical chemistry researcher with nearly 13 years of experience, each chapter links theoretical foundations directly to real-world drug design applications.

Computer-Aided Drug Design covers molecular and quantum mechanics, energy minimization, ADMET prediction, de novo drug design, and homology modeling. The book integrates artificial intelligence, machine learning, and nanotechnology into its treatment of contemporary drug discovery workflows. Case studies demonstrate practical use of computational tools, connecting technique-level detail to tangible outcomes in anticancer, anti-diabetic, anti-inflammatory, and Alzheimer’s therapeutic research programs.

Readers will also find: - Detailed coverage of QSAR modeling, molecular docking protocols, and pharmacophore mapping with step-by-step computational methodologies for each technique
- Integration of artificial intelligence and machine learning approaches into structure-based and ligand-based drug design workflows
- Practical guidance on ADMET prediction tools and their application to optimizing drug candidate selectivity and efficacy
- Real-world case studies linking computational modeling to therapeutic outcomes across multiple disease areas including oncology and neurodegeneration
- Coverage of de novo drug design, homology modeling, and virtual screening techniques with current computational tools and software platforms

Designed for pharmaceutical scientists, computational chemists, bioinformatics and cheminformatics professionals, and advanced postgraduate students, this reference connects foundational CADD principles with current AI-driven and nanotechnology-enhanced approaches. It serves as a practical resource for researchers and drug developers seeking to apply computational methods across the drug discovery pipeline.

Autoren/Hrsg.

Grewal, Ajmer Singh

Lather, Viney

Deswal, Geeta

Guarve, Kumar

Fachgebiete

• Naturwissenschaften Chemie Organische Chemie Biochemie
• Naturwissenschaften Chemie Chemie Allgemein Pharmazeutische Chemie, Medizinische Chemie
• Naturwissenschaften Chemie Chemie Allgemein Chemometrik, Chemoinformatik

Inhaltsverzeichnis

About the Editors vii
List of Contributors ix
Preface xvii

1 Introduction to Computer-aided Drug Design 1
Deepika Choudhary, Priya Singh, Sejal Agrawal, Jyoti Monga, Minky Mukhija, and Rajender Kumar

2 Quantitative Structure–Activity Relationships (QSARs): Principles and Applications 21
Abhinav, Prabhjot Kaur, Ajmer Singh Grewal, and Mimoza Basholli Salihu

3 Molecular Mechanics and Quantum Mechanics in Drug Design and Energy Minimization 39
Vijay Kotra, B. N. B. Vaidehi, and A. Sree Gayatri

4 Molecular Docking in Drug Discovery: Techniques and Applications 65
Azizeh Shadidizaji, Ahmet Hacýmüftüoðlu, and Mohamad Warda

5 Computational Approaches to Drug–Receptor Binding Analysis 87
Rahul Pandey, Ujjwal Nautiyal, Abhishek Chandola, and Firoz Anwar

6 Decoding Drug Discovery: Pharmacophore Mapping and Ligand-based Design 115
Anu Sharma, Deepak Kumar Yadav, Krishan Kumar Verma, Saurabh Agrawal, and Amrendra Pratap Singh

7 Homology Modeling, AI-based Protein Structure Prediction, and 3D Protein Modeling 129
Pooja Gupta, Arsh Chanana, Ravindra Pal Singh, and Ajay Bilandi

8 In Silico Pharmacology: Computational Techniques and Applications in Drug Design 167
Priya Sharma, Ravinesh Mishra, Bhartendu Sharma, and Chirag Goda

9 Computational Methods for Predicting ADMET Properties: Tools and Strategies to Minimize Late-stage Drug Failures 187
Kagan Tolga Cinisli

10 In Silico Drug Design and Virtual Screening Techniques 199
Dishank Purandare, Rahul Jawarkar, Bhagwat Nagargoje, Yogeshwar Bachhav, and Satish Polshettiwar

11 De Novo Drug Design: From Fragment-based to AI-driven Approaches 225
Taufik Mulla, Drashti Dave, Vetriselvan Subramaniyan, and Ambika Nand Jha

12 Artificial Intelligence in Computer-aided Drug Design 243
Teena Garg, Shikha Baghel Chauhan, Indu Singh, and Anshuman Sinha,

13 Computational Chemistry and Drug Discovery: Intersection of AI, QSAR, and Molecular Modeling 259
Purna Nagasree Kurre, Murali Krishna Kumar Muthyala, and Mallikarjuna Rao Pichika

14 CADD in Drug Discovery: From Molecular Modeling to AI-powered Insights 281
Sweta Kamboj, Pankaj Kumar, Vandana Chaudhary, Rohit Kamboj, Shikha Kamboj, Rohit Dutt, and Kumar Guarve

15 From Target to Candidate: A Stepwise Guide to Modern Computational Drug Discovery 301
Titirsha Kayal, Soumyadip Ghosh, Reetika Debroy, Sudha Ramaiah, Anand Anbarasu, and Soumya Basu

16 Case Studies: Successful Drug Discovery Using CADD 339
Shaik Asha Begum, Sk. Abdul Rahaman, Anilkumar Adimulapu, and Ajay Bommareddy

17 Practical Guide to Computational Drug Discovery: Tools, Databases, and Workflows 355
Arijit Mondal, Debashis Metya, Sabina Yasmin, Suddhasattya Dey, and Arindam Maity

18 Future Innovations in CADD: AI, Quantum Computing, and Beyond 371
Nasir Vadia, Ramesh Parmar, Ashishkumar Kyada, and Vijaykumar Sutariya

Index 401

Über Autor(innen)

AJMER SINGH GREWAL, PhD, is Professor and Head of the Department of Pharmaceutical Chemistry at Guru Gobind Singh College of Pharmacy, India; with nearly 13 years of experience in pharmaceutical education and research. His research focuses on the structure-based drug design for anticancer, anti-diabetic, anti-inflammatory, and Alzheimer’s therapies using tools including Glide, AutoDock Vina, and Discovery Studio.

VINEY LATHER, PhD, is Professor of Medicinal Chemistry at Amity Institute of Pharmacy, Amity University Uttar Pradesh, India; with over 24 years of experience spanning academia, research, and the pharmaceutical industry. His current research focuses on drug discovery and development of small molecules for cancer, antimicrobial drug resistance, metabolic disorders, neurodegeneration, and autoimmune disease.

GEETA DESWAL, PhD, is Professor and Head of the Pharmacognosy Department at Guru Gobind Singh College of Pharmacy, India; with over 14 years of teaching experience. Her research interests include bioactivity-guided extraction and isolation of phytoconstituents, plant tissue culture, molecular modelling, and natural product-based drug discovery.

KUMAR GUARVE, PhD, currently serves as the Principal of Guru Gobind College of Pharmacy, India; with over 20 years of experience in pharmaceutical education, research and leadership. He has successfully led the institution to Autonomous Status and NAAC/NBA accreditation. His areas of expertise include pharmaceutics, pharmaceutical education, research methodology, quality assurance, regulatory affairs, intellectual property rights, and Ayurvedic drug development.