Comprehensive Approaches in Computer-Aided Drug Design: QSAR, Docking, Screening, Homology, Pharmacophore and AI-Driven Insights

Authors

Udaya Kumari Tula
Research scientist, DSK Biopharma Inc, Morrisville, North Carolina, USA
Chinmaya Rath
Lecturer, Usha college of Pharmacy, Dhadkidih, Behind DC Office P.O Madhurpur, Seraikela - 831013, Jharkhand, India
Abhisek Pradhan
Lecturer, Usha college of Pharmacy, Dhadkidih, Behind DC Office P.O Madhurpur, Seraikela - 831013, Jharkhand, India
Udaya Kumari Tula
Research scientist, DSK Biopharma Inc, Morrisville, North Carolina, USA
G. Sumithira
Professor, Department of Pharmacology, The Erode College of Pharmacy and Research Institute, Erode – 638112
VS. Thiruvengadarajan
Professor, KMCH College of Pharmacy, Coimbatore, Tamilnadu, India
S.P.R. Poonkodi
Associate Professor, HOD, Department of Chemistry, Government Arts College for Women, Sivagangai, Tamil Nadu, India.
Leslie V
Professor and Head, Department of Pharmacognosy, St. John’s College of Pharmaceutical Sciences & Research, Kattappana, Idukki, Kerala, India.
Kannan Raman
Professor and Head, Department of Pharmacology, St. John’s College of Pharmaceutical Sciences & Research, Kattapana, Idukki, Kerala, India.
Amareswarapu V Surendra
Assistant Professor, KL college of Pharmacy, Koneru Lakshmaiah Educational Foundation Greenfields, Vaddeswaram, Guntur, Andhra Pradesh-Pin:522302
Sushma.N
Assistant Professor, KL college of Pharmacy, Koneru Lakshmaiah Educational Foundation Greenfields, Vaddeswaram, Guntur, Andhra Pradesh-Pin:522302
Mandava Mahima Swaroopa
KL college of Pharmacy, Koneru Lakshmaiah Educational Foundation Greenfields, Vaddeswaram, Guntur, Andhra Pradesh-Pin:522302
Saravanakumar A
Department of Pharmaceutical Biotechnology, Vellalar College of Pharmacy, Thindal, Erode, Tamil Nadu, India.
Kavin Kumar MC
Department of Pharmaceutical Chemistry, Vellalar College of Pharmacy, Thindal, Erode, Tamil Nadu, India.
Jeevananathan P
Department of Pharmaceutical Chemistry, Vellalar College of Pharmacy, Thindal, Erode, Tamil Nadu, India.
Monisha K
Department of Pharmaceutical Chemistry, Vellalar College of Pharmacy, Thindal, Erode, Tamil Nadu, India.
Kavin Kumar MC
Department of Pharmaceutical Chemistry, Vellalar College of Pharmacy, Thindal, Erode, Tamil Nadu, India.
Saravanakumar A
Department of Pharmaceutical Biotechnology, Vellalar College of Pharmacy, Thindal, Erode, Tamil Nadu, India.
Akalya P
Department of Pharmaceutical Chemistry, Vellalar College of Pharmacy, Thindal, Erode, Tamil Nadu, India.
Lathika S
Department of Pharmaceutical Chemistry, Vellalar College of Pharmacy, Thindal, Erode, Tamil Nadu, India.

Keywords:

Computer-aided drug design, QSAR, molecular docking, pharmacophore modeling, artificial intelligence.

Synopsis

The advent of computer-aided drug design (CADD) has revolutionized the paradigm of pharmaceutical discovery by integrating computational chemistry, molecular biology, pharmacology, and artificial intelligence into a cohesive framework for rational drug development. This book, Comprehensive Approaches in Computer-Aided Drug Design: QSAR, Docking, Screening, Homology, Pharmacophore and AI-Driven Insights, presents an in-depth synthesis of foundational theories, modern algorithms, and translational strategies that define the digital transformation of drug discovery. The twenty chapters collectively explore the evolution of QSAR methodologies from one-dimensional statistical correlations to multidimensional and AI-enhanced models; the principles of molecular docking and dynamics for structure-based design; and the roles of pharmacophore modeling, virtual screening, and chemoinformatics in ligand prioritization. Further sections extend into machine learning, network pharmacology, de novo generative design, and quantum computing, illustrating how these innovations transcend traditional limits of chemical and biological exploration. Each chapter provides theoretical grounding, comparative methodology, and detailed computational workflows, supported by contemporary research evidence, case studies, and future perspectives. By bridging classical concepts with cutting-edge developments such as graph neural networks, diffusion models, and sustainable computational practices this volume aims to equip researchers, educators, and professionals with a unified, methodologically rigorous reference. Ultimately, the book envisions CADD as a cornerstone of next-generation pharmaceutical innovation, enabling predictive, explainable, and ethically responsible drug discovery across diverse therapeutic frontiers.

Computer-Aided Drug Design

Published

October 21, 2025

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