Revolutionizing Drug Discovery: Cutting-Edge Computational Techniques

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· Advances in Pharmacology 103권 · Academic Press
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Revolutionizing Drug Discovery: Cutting-Edge Computational Techniques, Volume 103 is an essential guide for professionals, researchers, and students in the pharmaceutical and biotech industries, providing an in-depth look at how computational methods transform drug development. Chapters in this new release include Innovative Computational Approaches in Drug Discovery and Design, Advanced Molecular Modeling of Proteins: Methods, Breakthroughs, and Future Prospects, Predictive Cavity and Binding Site Identification: Techniques and Applications, ADMET Tools in the Digital Era: Applications and Limitations, Essential Database Resources for Modern Drug Discovery, Deep Learning for Drug Design and Development, and much more.Other sections cover Molecular Docking and Structure-Based Drug Design: From Theory to Practice, Molecular Dynamics Simulations: Insights into Protein and Protein-Ligand Interactions, Targeting Disease: Computational Approaches for Drug Target Identification, High-throughput computational Screening for Lead Discovery and Development, Harnessing Machine Learning for Rational Drug Design, Identifying Novel Drug Targets with Computational Precision, Computational Exploration of Viral Cell Membrane Structures for Identifying Novel Therapeutic Target, and many more interesting topics. - Offers expert insights from leading authorities on computational techniques in drug discovery, ensuring readers gain accurate, cutting-edge knowledge - Includes illustrative graphics and case studies to enhance comprehension and engagement for readers across disciplines - Provides forward-looking perspectives on the role of computational methods in drug development, highlighting both current advancements and future trends

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