Structure-Based Drug Discovery

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出版者:Springer Verlag 作者:Hubbard, Roderick E. (EDT) 出品人: 页数:278 译者: 出版时间:2006-4 价格:$ 240.69 装帧:HRD isbn号码:9780854043514 丛书系列:
图书标签
  • 药物发现
  • 结构生物学
  • 计算化学
  • 分子对接
  • 药物设计
  • 蛋白质结构
  • 虚拟筛选
  • 先导化合物
  • 药物化学
  • 结构基因组学
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具体描述

Structure-based drug discovery is a collection of methods that exploits the ability to determine and analyse the three dimensional structure of biological molecules. These methods have been adopted and enhanced to improve the speed and quality of discovery of new drug candidates. After an introductory overview of the principles and application of structure-based methods in drug discovery, this book then describes the essential features of the various methods. Chapters on X-ray crystallography, NMR spectroscopy, and computational chemistry and molecular modelling describe how these particular techniques have been enhanced to support rational drug discovery, with discussions on developments such as high throughput structure determination, probing protein-ligand interactions by NMR spectroscopy, virtual screening and fragment-based drug discovery. The concluding chapters complement the overview of methods by presenting case histories to demonstrate the major impact that structure-based methods have had on discovering drug molecules. Written by international experts from industry and academia, this comprehensive introduction to the methods and practice of structure-based drug discovery not only illustrates leading-edge science but also provides the scientific background for the non-expert reader. The book provides a balanced appraisal of what structure-based methods can and cannot contribute to drug discovery. It will appeal to industrial and academic researchers in pharmaceutical sciences, medicinal chemistry and chemical biology, as well as providing an insight into the field for recent graduates in the biomolecular sciences.

这本图书《Structure-Based Drug Discovery》聚焦于药物研发中的一个关键环节,即利用分子结构信息指导和优化新药的设计与开发。它详细介绍了从初始靶点识别到最终药物候选物筛选的一整套科学流程,强调计算方法、实验验证以及多学科交叉的重要性。内容深入探讨了如何通过三维结构分析来理解分子间的相互作用,从而为化学家提供更精准的设计策略。这本书不仅解析了经典技术手段,还展示了现代人工智能和大数据在药物发现中的潜力,帮助读者了解新兴工具如何提升传统方法的效率。 书中通过大量案例分析展示了从小分子到靶向蛋白质的结构导向策略,并详细描述了计算建模、分子对接和虚拟筛选等核心技术的具体操作步骤。这些内容使读者能够系统地理解药物设计的逻辑路径,以及每一步所需的专业知识。此外,作者特别强调了实验验证在理论研究中的不可替代性,指出计算模型需要结合实际数据进行校准和优化。 本书还深入讨论了新兴技术的发展趋势,包括机器学习与高通量实验的融合,提供了对未来药物研发方向的见解。整个内容结构清晰、逻辑严谨,适合希望掌握药物开发科学原理及其实践应用的读者。通过系统性的学习,参与者将能够更好地应对复杂的分子设计问题,为新药研发贡献智慧和力量。这本书不仅是一本技术指南,更是一种思维导入,帮助读者建立对结构与功能之间关系的深刻理解。

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