Pharmaceutical Science & Technology

Computational Drug Design Modeling Tools, Techniques, and Informatics Approaches Editor: Mithun Rudrapal, PhD Ordering Info/Buy Book

In Production Pub Date: Forthcoming June 2027 Hardback Price: $200 US | £150 UK Hard ISBN: 9781779648730 E-Book ISBN: 978-1-77964-874-7 Pages: Est 286 pp w index Binding Type: Hardback / ebook Notes: 12 color and 22 b/w illustrations

This new volume, Computational Drug Design: Modeling Tools, Techniques, and Informatics Approaches, provides a timely and comprehensive overview of modern strategies for transforming drug discovery and development. As new diseases emerge, drug resistance increases, and the demand for safer, more affordable therapeutics grows, the need for innovative and efficient drug design approaches has become more urgent than ever. Computational methods have significantly enabled faster identification, optimization, and evaluation of novel drug candidates while reducing cost and time.

This volume brings together recent developments in computational modeling, predictive tools, bioinformatics, and artificial intelligence (AI) that are reshaping pharmaceutical research. It explores in silico drug-likeness profiling, pharmacokinetics, virtual screening, ligand similarity searches, pharmacophore modeling, scaffold hopping, and computational toxicity prediction. The book also highlights multi-omics approaches, target fishing, genome editing, and the growing roles of AI, machine learning (ML), and generative AI in designing next-generation therapeutics.

Special attention is given to the discovery of novel drug molecules, drug repurposing, and improving selectivity, affinity, metabolic stability, and oral bioavailability. From cancer therapy and multidrug-resistant bacterial infections to neurological disorders and viral diseases, the volume demonstrates how computational tools are being applied across diverse therapeutic areas.

Key features:
• Explores AI, ML, and generative AI applications in drug discovery
• Describes virtual screening, scaffold hopping, and pharmacophore modeling
• Examines computational toxicity prediction and drug-likeness profiling
• Provides modern informatics approaches for faster, cost-effective therapeutics

Written by international experts, this book serves as a valuable resource for medicinal chemists, pharmacologists, toxicologists, biotechnologists, discovery scientists, and R&D professionals seeking practical and forward-looking insights into modern drug design.

CONTENTS:
Preface

1. Computational Modeling, Predictive Tools, and Drug Design
Jenson Jacob and Tripti Sharma

2. Informatics and Multi-Omics Approaches in Drug Discovery
Koyel Kar, Rahul Choudhury, Priyanka Chakraborty, Sougata Neogi, Snehasish Ojha, Pritam Kamilla, Ria Dutta, Sailee Chowdhury, and Rishav Maji

3. In-Silico Drug-Likeness and Pharmacokinetics Profiling in Drug Design
Kratika Singh, Anmol Gupta, and Yogesh Kumar

4. Databases, Computational Software, and Web-Based Resources in Drug Discovery
Karishma Vivek Kathpalia and Awadhesh Kumar Verma

5. Ligand Similarity Search, Virtual Screening, and Drug Discovery
Kundan Dutta, Pallab Pramanik, Bidhya Sharma, Dipankar Nath, and Dipak Chetia

6. AI/ML-Based Tools and Approaches in Drug Design
Manish Kumar Tripathi, Gaurav Kumar, and Avanish Tripathi

7. Data Mining and ML Approaches in Drug Design
Kevser Kubra Kirboga

8. Generative AI and Predictive Modeling in Drug Discovery
Kevser Kubra Kirboga, Burcu Tekin, Ecir Ugur Kuçuksille, and Emre Aktas

9. Computational Methods in Predicting Drug Toxicity
Kratika Singh, Niharika Pandey, and Yogesh Kumar

10. DEL Screening and Genome (Gene) Editing in Drug Discovery
Samiksha Garse, Mrunal Gokhale, Vaishnavi Thakur, and Aayushi Kadam

11. Computational Target Fishing Approaches and Drug Discovery
Rahul Ghosh, Aditi De, Gourav Rakshit, Sharanya Roy, Sheikh Murtuja, and Mohammed Tahir Ansari

12. Molecular Design and Scaffold Hopping in Drug Design
André M. Oliveira and Mithun Rudrapal

13. Pharmacophore-Based Approaches, Screening, and Drug Design
Neelanjan Chowdhury, Abhimannu Shome, Anwesha Das, and Arijit Nandi

14. Role of Artificial Intelligence and Machine Learning in Health Monitoring Sensors and Drug Modeling
Maheswaran Baskaran, Karuppasamy Muthuvel Prasath, and Jeyaraj Pandiarajan

Index

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