Computer aided drug design principles (18 Ergebnisse)

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Taschenbuch. Zustand: Neu. Neuware - Drug discovery is undergoing a fundamental shift from empirical experimentation to precise, data-driven design powered by computational science. Computer-Aided Drug Design presents a structured and application-focused approach to modern drug development, integrating core concepts with advanced computational methodologies.The book systematically covers key domains including QSAR modeling, molecular modeling, docking, virtual screening, bioinformatics, and chemoinformatics. The content is enriched with more than 90 illustrations that present concepts with clear visual support.Emphasizing mechanistic understanding and workflow integration, the text connects molecular-level interactions with data-driven decision-making, enabling readers to understand not only how methods work but why they are applied.Each topic is presented with clarity and technical depth, reflecting current industry practices and research standards.Designed for students of B.Pharm, M.Pharm, and Pharm.D, as well as researchers and professionals, this book serves as a reliable guide for mastering computational strategies in drug discovery. It stands as a practical and forward-looking resource for those seeking to engage with the evolving landscape of rational drug design. …

Taschenbuch. Zustand: Neu. Neuware - Drug discovery has evolved from empirical experimentation into a data-driven, computation-intensive discipline, yet challenges of high attrition, rising costs, and translational failure persist. Addressing this complexity demands a mechanistic and predictive approach to molecular design.Computer-Aided Drug Design: Principles, Methods, and Applications in Drug Discovery presents a rigorous and integrated framework for modern CADD, encompassing molecular modeling, QSAR, docking, molecular dynamics, virtual screening, pharmacophore modeling, and fragment-based design. Rather than isolating techniques, the text connects algorithms, physicochemical principles, and biological systems to explain how computational methods guide rational drug development .Designed for postgraduate pharmacy students, doctoral researchers, and professionals, the book delivers conceptual clarity and algorithmic understanding while supporting structured academic responses and practical workflow competence.Its distinguishing strength lies in mechanistic depth and decision-focused reasoning-each method is examined in terms of its assumptions, parameter sensitivity, and real-world applicability, bridging computational prediction with pharmaceutical relevance.As drug discovery increasingly integrates artificial intelligence and large-scale data, this work provides a clear intellectual pathway to navigate and advance the future of rational therapeutic design.…

Buch. Zustand: Neu. Neuware - Drug discovery is undergoing a fundamental shift from empirical experimentation to precise, data-driven design powered by computational science. Computer-Aided Drug Design presents a structured and application-focused approach to modern drug development, integrating core concepts with advanced computational methodologies.The book systematically covers key domains including QSAR modeling, molecular modeling, docking, virtual screening, bioinformatics, and chemoinformatics. The content is enriched with more than 90 illustrations that present concepts with clear visual support.Emphasizing mechanistic understanding and workflow integration, the text connects molecular-level interactions with data-driven decision-making, enabling readers to understand not only how methods work but why they are applied.Each topic is presented with clarity and technical depth, reflecting current industry practices and research standards.Designed for students of B.Pharm, M.Pharm, and Pharm.D, as well as researchers and professionals, this book serves as a reliable guide for mastering computational strategies in drug discovery. It stands as a practical and forward-looking resource for those seeking to engage with the evolving landscape of rational drug design.…

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Buch. Zustand: Neu. Neuware - 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.…