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eBook Computer-Aided Drug Design

Principles, Techniques, and Applications 스마트한 PDF 필기 기능을 사용해 보세요!

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Wiley 2026.08.13.

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

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저자 소개

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.